Reverse Minesweeper Prototype Fable

Summary

Reverse Minesweeper Prototype Fable is the session that turned Reverse Minesweeper from a single-file HTML sketch into a running Anchor 3 game, worked by Fable in its own folder (reverse-minesweeper-fable/) alongside a parallel Astra folder the owner keeps for comparison. It opened by recovering the project from the Z: archive: the v3.1 sketch, the four HTML versions the owner had played, a Spelunky/Celeste/Terraria source corpus, the published gated log of the first session and the never-published transcript of the character-controller research session, rendered with the Anchor converter. It then read the cross-game controller numbers, chose constants by normalising to body height, and drove four Opus 5 subagent runs under Fable-written packets in fast mode (no design briefs): a kinematic controller lab with the Spelunky verb set, walls (slide budget and wall jump), the robot dig stage ported rule for rule, and the two-stage loop. Each run was re-verified by Fable through the eval channel: 47, 84, 135 and 216 assertions.

Recovery from the Z: archive:

• Owner: "There is a Reverse Minesweeper prototype project containing two transcripts, either on the old Windows or Linux machine ... I will work on it simultaneously with both you and Astra, so when you create a folder for it make sure to name it visibly as yours".
• Sketch found at Z:\2025-2026\code\a327ex-linux-2026-09\sketches\2026-09-03-reverse-minesweeper (git: two commits, clean tree). Copied to Desktop/a327ex/reverse-minesweeper-fable/ next to the pre-existing reverse-minesweeper-codex/ (Astra's).
• Transcript 1 = session 2b679f84 "Reverse Minesweeper Prototype" (2026-09-03), published as the gated log a327ex-site/gated/reverse-minesweeper-prototype.md; copied with its 18 media files, links rewritten relative.
• Transcript 2 = session a98a36df "Reverse Minesweeper character controller" (2026-09-04 03:19 to 03:56), never ended, no run dir. Found by grepping the Linux Claude home's jsonl for "minesweeper" (a first grep silently failed because the project folder name starts with a dash and was parsed as an option). Rendered with lib/jsonl_to_markdown.py into transcripts/02-.../log.md (318 KB, five research-lane subagent reports woven in); the 28 KB final report extracted verbatim as report-character-controller.md.
• The four HTML prototype versions (v1 lava clock, v2 countdown + nuggets, v3 robot + human, v3.1 rope forward + quick-start) were not in the transcript as files; the first session had rebuilt them at end-session with its own versions.py and the output survived in Anchor/workflow/runs/2b679f84-.../extra/ (already restored locally). Copied into prototypes/; v3.1 md5 matches index.html. Fable's own replay script was abandoned after it missed the Bash-applied python patches (one Write was also rejected mid-session and must be skipped).
• reference/README.md pointed at a log title that never existed; fixed in the copy to point at the recovered transcript.
• Memory file project_reverse_minesweeper.md created; MEMORY.md pointer added.

Recommendation and the plan the owner approved:

• Fable proposed: controller lab first (report's order), give the lab a score loop so it doubles as a fun-gate, walls second, dig port third; A/B/C shapes for parallel work (bake-off recommended). Owner: "Astra is working on his own version, not in parallel with you ... Let's go ahead with your plan ... let's also do no briefs this time either. As for the numbers, the second transcript should have numbers from multiple games, so you can actually read those".
• Four decisions closed by default: Spelunky time-of-descent fall rule with height-expressed tiers; no walls in batch 1; HP only, no stun; 2D layer with rectangles.

Choosing the numbers (Fable's reading of the research):

• Key normalisation: divide by body height. Terminal velocity is 14 to 19 body heights/s in Spelunky Classic, Celeste and Terraria; standing jump apex 1.5 to 2.5 body heights everywhere but Jump King; the sketch's terminal was 50 body heights/s. Human 0.8 tiles vs Spelunky's 1.0, so Spelunky's tile numbers transfer nearly directly.
• Chosen: terminal 18 tiles/s (Classic 18.75), gravity 50 (between Classic 56 and Spelunky 2 ~29); terminal reached after 3.2 tiles, same as Spelunky, which is why time-of-descent and height agree past the third tile. The prior report's 20 tiles/s contradicted its own normalisation.
• Jump: apex heights are the constants (tap 0.8, held 1.6), launch speed solved numerically at load; 1.6 keeps Classic's geometry (2-tile ledge grab reachable, 3-tile never). Classic's variable jump (gravity ramps while held, snaps on release) rather than Celeste's sustained speed.
• Ground: 5.5 / 10 / 1.5 walk/run/crawl, cap in 0.06 s; air control 0.65 (Celeste); air drag half-life 0.1 s (Spelunky's 0.8 per step).
• Fall presets: spelunky (8 = 1 HP, 16 = 2, 24 = death) and prince (4/8/12); character colour changes per tier mid-fall.
• Ropes: Classic's thrown rope with flight (~8 tiles up in 0.6 s, unrolls half a tile per step) plus Spelunky 2's rope-from-hang; rope catch is explicit (hold up); climb 3 tiles/s.
• Departures from the prior report: lower-off merges Minecraft's sneak-stop at the lip with a hold to hang; climb-up is Celeste's mantle, not Spelunky's double-impulse hop; ledge-grab test is a sweep over the tick's path (a point test skips the 0.25-tile window one tick in four at 18 tiles/s); coyote and buffer 0.08 s.

Delegation doctrine applied (four Opus 5 subagent runs, all registered under Anchor/workflow/delegate/runs/ and reviewed):

• Packets = preamble + task + Anchor facts + approach + constants table + closed decisions + scope + stop conditions + verification + report format. A Sonnet Explore agent mapped the Anchor 3 APIs first (game dir layout, 120 Hz tick, bind/input_*, top-left rectangles, callable colours, camera attach/detach, anchor drive, engine_step, engine_snapshot, input_inject_*).
• Engine facts that shaped the packets: no per-game anchor.exe needed (anchor drive uses the shared engine/engine/build/anchor.exe); tuning.lua must be a definition file assigning global T, with derived values in D rebuilt by tuning_derive() from boot.lua and on_reload(); agent instances reload only on engine_reload(); the anchor <game> windowed launch subcommand does not exist on this machine, the owner runs run.bat.
• The harness refused every subagent's Write of report.md; Fable saved each report verbatim from the final message. run.json for each run carries agent=claude, the subagent jsonl path, parent session, and a review note.
• Review protocol each time: read the report, anchor check lab, re-run tools/verify.lua on a fresh anchor drive start, read the named code, view snapshots.

Batch 1, the controller lab (lab/, 47/47):

• Files: main.lua, boot.lua, tuning.lua, controller.lua (44 functions), rooms.lua, view.lua, run.bat, anchor/ framework copy stamped at 482f9fcd30, tools/verify.lua, tools/snapshot.lua.
• Rooms: calibration (1/2/3-tile steps, grab walls, pits of 4/6/7/8/10/12/16/24), endless 16-wide shaft from 12 authored chunks with a seed and depth score (4 HP, 4 ropes), walls placeholder. Keys A/D, S, W, Space, Shift, E (S+E rope down), R, 1/2/3, F1.
• Implementer reopened one rule: a single launch speed cannot hit both a 0.8 tap and a 1.6 held apex with gravity ramping from zero (the tap would launch faster than the held jump). Resolution: launch speed solved from the tap apex, the ramp's starting fraction (0.189) solved from the held apex; jump_ramp_from = 0 restores the literal ramp. Accepted.
• Noticed: a 0.8-tile body needs no crouch on a whole-tile grid; rope-from-hang anchors in the player's own column beside the wall (the ledge tile is solid); landing can resolve in either air or ground state (a dead-overwrite bug caught by the 24-tile pit assertion); .luarc.json excludes tools/ from anchor check.
• Hot reload proven through the eval channel (walk_speed 5.5 to 3.25 and back).

Batch 2, walls (84/84):

• Design: hold-toward auto-slide (Hollow Knight's input) with Celeste's ramping cap (3 to 18 tiles/s over a 1.2 s per-airtime budget, not refilled by wall jumps); fall clock advances in proportion to slide speed; wall jump 8 tiles/s with 0.15 s forced-move, no direction input needed; 0.06 s wall coyote; down cancels a slide; ledge grab beats slide.
• Room 3 rebuilt as a 9-station course (3-wide shaft, 2-wide, 1-wide chimney, 30-tile wall, slide-to-shelf, slide-to-grab across a lane, 8-deep pit, wall that ends mid-air).
• Findings: a slide can never grab a corner on the same face (a protruding block is under the feet, so it is a landing); catching a corner across a gap at full slide speed is a 2-to-3-frame input; the 30-tile slide is still lethal (budget buys back under 3 tiles); wall-jump chains need the button held (tap = 0.8-tile apex). Fable's "settles at 3 tiles/s" assertion contradicted the ramp model (no plateau; cap meets speed at ~4); measured with the budget pinned via lab_slide_freeze. Kept Celeste's model.

Batch 3, the robot stage port (135/135):

• world.lua (seeded per-tile hash reproducing the JS exactly under seed 1e6, sparse dug/flag sets, exposure and counts recomputed not cached, blasts and chains, nuggets), robot.lua (sketch movement on the lab's sweep, reach rectangle, mouse dig, S digs down), T.dig block with every window.T value, room 4 (key 4), mouse:1/mouse:2 binds, 24 px HUD font.
• Sketch deviations listed: lab camera (anchor 0.40, tween, lead); corner correction lets the robot through 1-tile gaps the sketch would bonk on; mines never drawn (as the sketch); bedrock columns drawn at the sides of the 20-wide view; reach rectangle drawn; seed range capped at 1e6 because the JS loses precision above ~7.2e6.
• Findings: the energy economy is generous (an open-shaft fall banks more clock than it spends); a blast often leaves the robot standing on air; the chain stagger compounds across blasts (sketch behaviour, probably accidental).
• Two verification items adapted: 32x64 / 64x64 regions became 2048 / 4096 tiles over the 16 existing columns; mines cannot be written (pure hash), so the chain test pins seed 424242 and a real pair at (9,12)/(11,12).

Batch 4, the two-stage loop (216/216):

• game.lua: states play / powerdown (only on the ground; clock pinned at zero while airborne) / human / camp / dead; ease-in-out-quad pan over pan_time + 0.4 s hold; camp moves to the robot with camp_heal, rope refill, robot recharge, cycle + 1; death banner with stats and session best; ROBOT off-screen marker as state; the human exists from room load (fixes R restarting with 0 HP); run.t vs run.total_t (state clock vs run clock, as the sketch's stateT / t); falls hooked from outside do_land; controller.lua byte-identical to batch 2.
• Owner mid-batch: "you can also remove or decrease the velocity lead, at least vertically, it's going down too much and too easily" → cam_lead = 0 set by Fable directly with a comment; camera to be hand-tuned later.
• Design findings surfaced: you cannot fall past the robot (1-tile touch test every tick converts any drop through it into a camp, so a straight drop down the robot's shaft is always survivable); only a fall ends a run (clock refills fully at every camp); the clock reads 0.0 through the camp banner (sketch refills on leaving camp); nuggets are only collected by the robot; ropes persist forever.

Process notes:

• Owner on pace: "What's taking so long?" (17 min into batch 2; batches took 25 to 33 min each, mostly verification). "Lots of details to fix but I'd like you to proceed first with the next batch." "A lot of things to tune, but let's keep moving." "Very very good, what would you do next?"
• Fable's closing recommendation: put reverse-minesweeper-fable/ under git with a private GitHub remote (everything is a single uncommitted copy); the owner plays a full session with replays auto-recorded so Fable can review the .apr files; then decide touch-vs-land for reaching the robot and the fall/slide tuning together; descent extras and the character look deferred.
• Session ended public, titled "Reverse Minesweeper Prototype Fable", with the lab's replays woven.

Open artifact

Open artifact

Open artifact

Open artifact

There is a Reverse Minesweeper prototype project containing two transcripts, either on the old Windows or Linux machine. The first transcript was an exploration of the idea with a few HTML prototypes, the second was the start of a research into the human character's movement. Please recover those, we'll start working on this project here, however I will work on it simultaneously with both you and Astra, so when you create a folder for it make sure to name it visibly as yours, and if you do decide to copy files from the old project also copy them to your folder only to not contaminate any other work.

Fable 5.1 high

I need to recover the Reverse Minesweeper prototype project — two transcripts plus HTML prototypes — from the Z: archive drive, then create a clearly labeled folder like `reverse-minesweeper-claude/` and copy the files there. Let me check my memory for the September 3rd reference to Reverse Minesweeper to get more context.

I'll start by reading the archive manifest on Z: to find where the Reverse Minesweeper sketch and its transcripts landed.

Searching the whole external drive is taking a while, so I'll check what partial output has come back so far.

I found the sketch folder for the reverse-minesweeper project, plus a likely transcript location under the Claude Linux home and possibly the a327ex-site logs. I'll check the sketch folder and search for the relevant transcripts, letting the background find finish on its own rather than killing it.

Found the sketch folder at sketches/2026-09-03-reverse-minesweeper in the Linux-era code tree, and the Claude homes under ai/. Now listing the sketch and locating the two transcripts.

I'm looking for two relevant sessions, one on exploration and one on movement research, checking both the local jsonl transcripts and the published site logs for mentions of "minesweeper."

The sketch is intact with two commits and a reference corpus for the movement research. Now I'll locate the two transcripts—the published logs in the site tree and the raw jsonl sessions in the Linux Claude home.

Since the working directory changed to a327ex-site, I'll switch to absolute paths. I found one gated log at reverse-minesweeper-prototype.md, but the movement research transcript might have never been closed out or might be under a different title, so I should check the gated log's header along with the site's log list and jsonl sessions for related entries.

One published log found: the gated reverse-minesweeper-prototype.md. Now checking its header and hunting the second session in the raw jsonl store.

I also need the second transcript, the movement research session, which likely wasn't formally closed since the reference commit came after. I should search the jsonl project store for mentions of "spelunky", "Player.cs", or "movement", and grab the raw jsonl for the first session too, since the rendered markdown log is gated but the raw transcript would be complete.

The first session is fully published as a gated log with its media. The second session was likely never ended, so I'm searching the raw jsonl store for it.

I realize the empty grep result is likely because the directory name starts with a dash, so grep is misinterpreting the path as a flag. I need to prefix it with "./" and rerun, also filtering to files modified on or after September 3rd.

The earlier grep silently failed because the folder name starts with a dash and was read as an option. Rerunning with a proper path, restricted to sessions written on or after Sep 3.

Two candidates stand out: one with 222 mentions from the prototype session on 2026-09-03, and another with minesweeper/spelunky references likely from the movement research session. I want to verify by checking the first user messages and dates across these candidate files.

I've narrowed it down to two strong candidates — a prototype build session with 222 mentions and a movement research session with heavy Spelunky references. I'll check each one's first user message and date range to confirm which is the right match.

I've found two relevant transcripts: one published as a gated log about the reverse minesweeper prototype, and another unpublished one about a character controller variant from the next day. I should check whether there are subagent directories alongside these session files and look at the full user message for the unpublished one.

Now I'm figuring out naming — since the user wants the folder named visibly as mine, I'll go with something like `reverse-minesweeper-fable/` to distinguish it from other models' work, though I could flag this choice for confirmation. I also need to gather the sketch files and both transcripts; since the second session has no rendered markdown log, I want to check whether the Anchor workflow has a converter to turn its raw jsonl into a readable log.

Beyond that, I should verify whether the second session's git commit actually changed index.html or just added reference material, and check for any uncommitted work in the sketch directory — being careful with read-only-ish git status commands so I don't accidentally write back to the repo.

I also want to look at the vertical_sim.py file under reference/spelunky-classic since it's part of the research material, and then read the second session's opening user message to check for subagent directories, sketch git status, and the workflow's convert command — I'll tackle these in parallel.

I've identified both transcripts: the prototype session from Sep 3 (published) and the unpublished "Reverse Minesweeper character controller" session from Sep 4. Now I'll check the second session's full opening message, look for uncommitted work in the sketch folder, and see how the Anchor converter renders raw jsonl so I can recover a readable log.

I notice the second session mostly consists of tool results rather than real user messages, running through subagent research fan-out, with the report written in chat and the opener truncated. Now I want to check the Anchor workflow README for a convert command that handles a jsonl path.

Since Astra already has `reverse-minesweeper-codex` on the Desktop, I'll go with `reverse-minesweeper-fable` for mine. Now I want to check the README around line 253 for the anchor command signature with `--jsonl`, since I need a way to render a jsonl file to markdown without actually publishing it—let me read through lines 240-330 to find that.

I'll name my folder `reverse-minesweeper-fable` to match the existing `reverse-minesweeper-codex` on the Desktop, then check how the Anchor converter can render the unpublished jsonl without publishing it and review the codex folder's layout for naming consistency.

Astra's folder has a prototypes directory alongside reference and transcripts, which matches the earlier mention of "a few HTML prototypes" (v1, v2, v3, v3.1) — those versions were likely reconstructed from Write tool calls in the jsonl transcript. I should try the same extraction approach to pull the HTML versions out of the transcript data.

Since the gated log produced zero artifact cards, the v1/v2/v3 versions must only exist as Write/Edit tool inputs within the jsonl — reconstructing them means replaying those edits in order and snapshotting at each handover point. I want to check the usage of the jsonl_to_markdown converter script, count the Write/Edit calls on index.html with timestamps to plan the reconstruction, list the codex prototype directory names for parity, and fully inspect the gated log's media directory.

I'll reconstruct the HTML versions from the transcript's tool calls, following the same approach used in Astra's prototypes folder. Now gathering four things: the converter's CLI, the codex folder layout for parity, the sequence of index.html writes in the prototype session, and the gated log's media.

Still recovering: I have both transcripts and the sketch located. Now working out how to render the second transcript to markdown and how to rebuild the HTML prototype versions.

I'm laying out the folder structure now — placing the current sketch as index.html, moving the movement research corpus into a reference folder, and copying over the catalog and ideas docs from the sketches directory for context.

For transcripts, I'm keeping the gated markdown log with its media folder plus the raw jsonl for the first session, and the raw jsonl plus subagents plus a converter-rendered log for the second. For prototypes, I want to reconstruct v1 through v3.1 by replaying the Write/Edit calls on index.html from the jsonl, snapshotting the state after each contiguous batch of edits right before the next user message, so each snapshot reflects something the user could actually have played.

I'll write a Python script that filters tool calls to only the path matching the minesweeper index.html, applies Write/Edit/MultiEdit semantics, and saves numbered snapshots timestamped to match the log — then verify the final replayed state matches the committed file as a sanity check. I also need to run the converter for the second session's jsonl to produce its rendered markdown with media references, keeping in mind the gated log truncates memory-file reads and that the media references point to a gated media folder.

I should check the actual link format in the media markdown before deciding where to place copied media so relative links stay valid — then proceed with creating the folder skeleton, copying the sketch files, catalog, and ideas docs.

I'll also copy the JSONL sessions plus the subagents directory and custom-title, run the converter on the second session into its own log with media, and run the replay script to check version handover timestamps against the log. I'll draft the replay script in scratchpad and fire off several independent bash calls in one message to get it all done together.

Everything I need is located. Now I'll do the recovery in one pass: build the `reverse-minesweeper-fable/` folder, copy over the sketch, reference corpus, transcripts, and published gated log with media, render the unpublished second session to markdown, and replay the transcript's Write/Edit calls to rebuild each HTML prototype version.

I have three independent things to tackle now: rendering session 2's transcript with media, replaying the session 1 index.html edits into prototypes, and verifying the media link format in the gated log resolves correctly. I'll run these in parallel, writing the replay script inline via a heredoc in Bash rather than a separate file first.

Now I'll run the prototype replay and media-link check in parallel, and also grep the second session's log for the assistant report headings so I can summarize what's in that movement research report for the handover.

The heredoc quoting is getting mangled by Bash on Windows, so I'll just write the script directly using the Write tool instead and run it that way. Then I need to handle several independent things: running the replay script, checking the media link format in the gated log, and pulling the final report text from the second session's log.

Folder set up with both transcripts copied. Next I'll replay the prototype session's edits to rebuild each HTML version, verify the gated log's image links resolve in the copied folder, and pull the report headings from the second session.

One Write attempt failed since the file had changed since it was read, yet my replay still applied it—so the final state doesn't line up. The edits might have gone through a different path, like after a folder rename, or been done via Bash commands like sed or python instead of the Write tool. I should list every tool use that touched index.html, including timestamps and any Bash commands, to trace what actually happened.

I need three things now: a detailed listing of all tool calls touching index.html with their error status, a check of media links in the gated log, and the second session's report headings—all independent, so I'll request them together.

At 21:40, the original session already replayed versions.py and stashed reconstructed versions into the run's extra directory — I should check if those files still exist on Z under the run's extra folder, since that would be the authoritative reconstruction.

But many edits also happened via raw Bash python patches at various timestamps that my replay might miss entirely. If the extra/ dir doesn't have what I need, I'd have to replay those inline patch scripts myself against a temp copy of index.html. For now I want to check three independent things in parallel: what's in Z's runs/extra directory and the versions.py write content, the media link format in the gated log, and the headings from the second session report.

I found the original session's reconstruction already restored locally, and the v4 file matches the final version's size exactly, confirming these were built with the Bash patches replayed and are authoritative. I'll copy them into my prototypes folder in place of my partial replay, along with versions.py for provenance.

Now I have several independent items to check: replacing my prototypes with the run's extra versions and confirming md5 matches, checking media links in the gated log, pulling the second session's final report and headings, checking whether session 2 has a registered local run, and reading the reference README for corpus context. Once those are done I'll write a README and handover doc for my folder.

I'm seeing 23 media refs across 18 files but the exact link syntax isn't the standard markdown form, so I need to check the precise pattern used. I still need to pull the session 2 log headings and first user message in full, the subagent list from meta.json, and the reference/README.md contents.

Verifying the copied artifacts and gathering what the second session contains so the handover can describe it.

Since the absolute media links won't resolve in my copied file, I'm using sed to rewrite them to relative paths pointing to media/gated. Next I need to check session 2's log.md structure by grepping headings and pulling the full first user message.

I'll adjust the bare `/media/gated/...` lines to relative paths using sed since that's harmless, and then move on to structuring session 2 with headings, an assistant turn count, and the full first user message.

Then I need the subagent meta.json contents from session 2 to see what they researched, plus the reference/README.md content, before writing my own README and the final handover.

I'm noting that log.md seems to be the full rendered session with subagent reports woven in—the survey and various game constants. I want to check the tail of the session to see how it actually ended and whether the final report was delivered in chat.

I also need to grab the full first user message from the jsonl since it got truncated in my earlier print, look at reference/README.md, and trace turn-by-turn assistant text lengths in session 2 to locate where the big report lands. These can all be pulled in one batch.

I still need to check whether session 2's final report was actually delivered by looking at the tail of log.md, and also pull up reference/README.md so I can write my own README and complete the handover. I'll request both of these together.

Recovery's essentially done. Now I'll verify whether the second session's final report was delivered in chat and check the reference corpus README to make sure the handover is accurate.

The final report went out in chat and is captured in log.md, so now I need to pull it into a standalone report.md file, check the reference README content briefly, and then write my own folder README last since it depends on nothing else.

Now I'll write the folder README.md as my own engineering doc, which is fine within scope. I also want to fix the dangling log-title reference in my copy — the original session log was never published, but the transcript now lives at `transcripts/02-.../log.md`, so I'll update the one-line reference to point there instead.

I should also save a project memory for reverse-minesweeper since its state (folder naming, Astra parallel) isn't derivable from code alone — I'll create `project_reverse_minesweeper.md` and add a pointer line in MEMORY.md under the games section, inserting it near the existing game-sketches entry. I'll do all four tasks in one response: writing the README, fixing the reference line, writing the memory file, and updating MEMORY.md.

I still need to save the memory by writing the project file and adding the MEMORY.md pointer, then prepare the handover. Since the report is a deliverable, I should send the README as a viewable file per the log-friendly artifacts convention.

Recovery done. Last steps: index the new memory and send the two summary files, then hand over.

Everything is recovered into reverse-minesweeper-fable/, a folder named for me next to Astra's existing reverse-minesweeper-codex/. Nothing was copied into or read from Astra's folder, and nothing was written back to Z:.

What was found and where it came from

• The sketch itself was on the Linux machine, in the sketches/ repo at the wipe (Z:\2025-2026\code\a327ex-linux-2026-09\sketches\2026-09-03-reverse-minesweeper). Two commits: the prototype, then the reference corpus. Working tree was clean, so nothing uncommitted was lost.
• Transcript 1, "Reverse Minesweeper Prototype" (2026-09-03, six hours). It was published as a gated log, so both the rendered log with its 18 media files and the raw jsonl are in transcripts/01-reverse-minesweeper-prototype/. I rewrote the log's site-absolute media links to relative ones so they resolve inside the folder.
• Transcript 2, "Reverse Minesweeper character controller" (2026-09-04, 03:19 to 03:56). This one was never ended, so no log existed anywhere. I rendered the raw jsonl with the Anchor converter into transcripts/02-reverse-minesweeper-character-controller/log.md (includes the five research-lane subagent reports), and extracted the 28 KB final report verbatim as report-character-controller.md, sent above.
• The HTML prototypes. The transcript only holds the writes and patches, but the first session rebuilt every played version at end-session with its own replay script, and that output survived in the run directory that was already restored to this machine. Those four files are in prototypes/ as v1 (lava clock), v2 (countdown + nuggets), v3 (robot + human), v3.1 (rope forward + quick-start). v3.1 is byte-identical to the committed index.html, which confirms the replay.
• reference/ is the movement-research corpus (Spelunky Classic 1.1 vanilla GML with diffs and a vertical sim, Celeste, Terraria, Noita, Hollow Knight, Prince of Persia). Its README pointed at a log title that never existed; in my copy it now points at the recovered transcript.
• sketches-context/ holds the catalog property sheet, the ideas backlog entry and the sketch repo's git log.

State the project is in

No Anchor code exists. The second session's report ends with the plan to build the human controller first as a standalone lab in Anchor 3 (custom kinematic tile controller, constants in tiles and seconds at the 120 Hz tick, calibrated against Spelunky Classic's source numbers), then wall interaction and the descent kit, then port the dig game. It leaves four decisions to you: fall-damage model, wall model, cost of a bad landing, and lab placement plus renderer. I saved a memory for the project and the two-folder arrangement.

One thing to decide before we start: the sketches practice ran in fast mode with no briefs. Now that this is a project with two models on it, I'll assume brief-first rules are back unless you say otherwise.

How do you suggest we proceed?

This is a planning question where I should lay out labeled options with a recommendation. I'm recalling the research report's proposed sequence—controller lab calibrated to Spelunky Classic first, then walls/descent kit, then the dig game port—and the four open decisions that still need resolving.

There's a real tension worth surfacing honestly: the dig game was the validated fun, while the human descent stage was less proven, yet the owner has twice affirmed starting with the character controller in Anchor. I should note that as his call while still flagging the risk of front-loading feel investment before the core loop is confirmed. I also need to think through how Fable and Astra would actually divide work in parallel without stepping on each other—same task with independent attempts is one option worth weighing.

Also pits of various depths and rope columns, with tunable constants in a hot-reloadable table. Steps 2 and 3 cover wall-jump/descent and porting the dig game, and I'm thinking a tiny built-in score loop (descend as deep as possible with limited ropes/HP) would turn the feel-lab into something actually judgeable as fun. I should present my four recommended defaults (fall-damage model, wall model, HP-only, 2D rect lab) as a batch for him to confirm or veto, note the design brief and Opus 5 subagent delegation, and reference Anchor's collider exception, update-only input edges, and fixed 120 Hz.

Spelunky Classic's 30Hz constants are already converted in the report, and since he's now on Windows, an Overlunky dump from Spelunky 2 is a cheap optional add later once the lab exists to compare against — character visuals stay deferred per his instruction. I've seen enough of the report's head, tail, and reference-game middle to make a solid proposal, though I want to be honest about what I haven't fully reviewed.

I should also flag the merge/contamination risk between the two folders that'll eventually become one game — my proposal is that the lab stays disposable per model, whichever controller he prefers becomes the base, and ideas from the other folder get ported through conversation rather than file-copying. For format, I'll write thorough prose with labeled recommendation and stop, keeping headers minimal or using bold leads since CLAUDE.md favors depth over rigid structure, and I'll label options A/B/C for the parallel-work question.

My recommendation is to follow the report's order, but shape the first batch so it doubles as a fun-gate rather than a pure feel toy, and settle how two models share one game before either writes code.

The plan I'd follow. Batch 1 is a controller lab in Anchor 3: a 2D layer, rectangle tiles, a fixed tile grid, a custom kinematic controller (no Box2D, per the report and per the Box3D caveats), every constant in one table in tiles and seconds, integrated at the 120 Hz tick. The lab holds the Spelunky Classic verb set, converted from the source numbers already in reference/: walk/run/crawl, variable jump, ledge grab and hang and climb-up, thrown ropes that unroll and can be caught mid-fall, fall damage by descent time, look-down camera. Test geometry is authored, not generated: one tall shaft with ledges at varied spacings, a row of pits at 4/6/8/10 tiles for calibrating the damage threshold, rope columns. Batch 2 adds the things Spelunky lacks and this game needs: wall slide and wall jump, and the descent kit. Batch 3 ports the dig game onto the controller. Anchor buys one thing the HTML sketch never had: save the file and the running lab reloads in place, so tuning constants is a live loop instead of a reload-and-replay loop.

The one change I'd make to the report's plan. Give the lab a score loop from day one: four ropes, four HP, a bottomless authored shaft, score is depth reached. The reason is a tension in the recovery data. The validated fun is the robot dig (v2 got "a lot of fun"); the human descent, the thing the controller serves, only got "actually kinda fun" with a 60-line placeholder. Controller-first is your call and I agree with it, but a controller lab that is only a feel toy can't tell you whether the human half deserves the game. A lab with a score can. It costs almost nothing extra.

Working in parallel with Astra. This is the part that needs your decision, because the folder split only solves contamination, not convergence. Three shapes:

• A. Bake-off (recommended). Both models build the same batch 1 from the same brief. You play both labs, pick the controller that feels right, and that folder becomes the base for batch 2. The other folder is mined for ideas by conversation, never by file copy. Feel is exactly the thing you can't specify and can only choose between, so two independent attempts is the right use of two models here. Cost: batch 1 is built twice.
• B. Split by layer. One model builds the controller lab, the other ports the robot dig stage to Anchor. No duplicated work, but a merge later, and the merge crosses the folder boundary you just drew. It also means the dig port happens before the controller exists to receive it.
• C. Split by verb set. One model does ground movement and ledges, the other ropes and fall damage, inside the same lab. Fastest on paper, but a controller is one state machine, and two authors on one state machine is the worst outcome for feel.

A is my recommendation. If A, the two briefs should be identical and the test geometry identical, or the comparison measures the level, not the controller.

The four decisions the report left open. My picks, vetoable in one line each:

1. Fall damage: Spelunky's model (descent time, one HP at about 7 tiles, stun later when hazards exist), with sliding and gliding counted at a reduced rate rather than resetting.
2. Wall model: build without walls first (Spelunky-pure, ropes and ledges only) as the calibration baseline, then hold-toward slide with a wall jump in batch 2. Celeste-style grab with stamina stays on the table if hanging should cost something.
3. Bad landing costs HP only for now.
4. Lab on a 2D layer with rectangles. Cubes in layer3 at game-port time.

Two things to say plainly. First, the report recommended constants calibrated to Spelunky Classic because those numbers are public and exact; Spelunky 2's are not published. You are on Windows now, so if you own Spelunky 2 the Overlunky per-frame dump is a cheap measurement I can script and you run, but it only pays once a lab exists to compare against, so it belongs after batch 1, not before. Second, the character's look stays deferred as you said, but the lab should be built so the visible body is a readout of the state machine, not a driver of it, so that the choice between live 3D and pre-rendered sprites later costs nothing in the controller.

If you pick a shape for the parallel work and confirm or veto the four defaults, I'll write the batch 1 design brief next. Per the delegation doctrine, once the brief is agreed the implementation goes to an Opus 5 subagent and I review it against the brief.

Astra is working on his own version, not in parallel with you. I'm comparing what you both do in the same project (but in different folders, so don't worry about it) Let's go ahead with your plan, it seems good, let's also do no briefs this time either. As for the numbers, the second transcript should have numbers from multiple games, so you can actually read those and try to see if they give you any insight on how you should pick the numbers.

The owner wants me to proceed with the plan directly, no briefs, pulling constants from multiple games' numbers in the second transcript, starting with the controller lab batch in Anchor 3. I should read through the numbers sections myself—Celeste, survey data, Spelunky 2 and Classic, and the eight-game constants—since picking the right values requires judgment I shouldn't delegate.

For orientation on Anchor 3, I'm weighing whether to hand off reading the docs and API references to a subagent, but since I still need precise implementation details myself, I'm leaning toward doing some of this directly rather than fully delegating.

Reconsidering doctrine: since the controller state machine defines the whole feel of the game, I'll write the spec myself—choosing constants and designing the state machine—then delegate implementation to an Opus 5 subagent with a detailed packet, and verify the result through the anchor drive afterward.

I need to register this run in delegate/runs per the memory protocol, and I should check DELEGATION.md for the exact packet format and registration requirements. I'll invoke the delegate skill to get the proper protocol before proceeding. My plan is to first review the numbers sections of the transcript myself, then in parallel spawn a Sonnet Explore subagent to orient on Anchor 3 for a 2D lab setup—covering the game directory structure, layer creation, drawing primitives, and the input API.

Going ahead. First, three things at once: I'll read the number sections of the second transcript myself, send a Sonnet agent to map the exact Anchor 3 APIs a 2D lab needs, and load the delegation protocol since the implementation goes to an Opus subagent under my spec.

I need to work through the numbered sections of transcript 2 covering the Celeste/games discussion, the survey and taxonomy, Spelunky 2, Spelunky Classic constants, and the eight-games section — around 1100+ lines total. I'll read through these in a few chunks using offsets in parallel.

I have the numbers, but I still need the middle section of the report covering "what the reference games actually do" and the build plan, since that's where the recommended numbers live — I've only seen the head and tail so far. I should read that middle portion of report-character-controller.md before drafting my spec, while I wait on the Sonnet Anchor-orientation agent.

Numbers read. Now the middle of the final report, which holds the previous session's own number recommendations and build plan, before I write the constants table.

With the research done, I'm waiting on the Anchor orientation from the Sonnet agent while working through my own number decisions in the meantime. I should also check the existing HTML sketch's controller code for movement, rope logic, and world constants like tile size and hitbox dimensions, so the lab stays consistent with the game's conventions.

I'm now cross-referencing terminal velocity and jump apex data across Spelunky, Celeste, and Terraria, normalizing by body height to see if there's a consistent ratio I can apply to our own hitbox size — this gives me a principled way to justify the number choices in my handover rather than picking them arbitrarily.

Settling on 18 tiles/s given the human-to-tile ratio is close to Spelunky's. For gravity, I'm working through the numbers across games — Classic comes out around 56 tiles/s² (56 body-heights/s²), Celeste around 82 bodies/s², Terraria roughly 34.6 bodies/s², and Jump King about 35.6 bodies/s², converting each game's raw physics constants into a comparable body-height unit.

By body heights, jump apex varies a lot too: Classic 1.56, Celeste 2.5, Terraria ~2.4, Jump King 5.7 (charged). I think the real feel comes from time-to-apex and airtime rather than raw height, so I'm checking Classic's numbers against each other — airtime of 17 steps (0.57s) and apex of 1.56 tiles imply a launch velocity that doesn't quite match the actual jump speed I calculated earlier, so I need to reconcile that discrepancy.

Working it out, the gap comes from gravity ramping up while the jump button is held rather than staying constant. Given the design intent of a short jump that can't clear 2-tile holes, forcing rope/ledge use, I land on constants close to g=50, apex ~1.6 tiles held / 0.8 tapped — near the earlier suggested values but I'd favor keeping apex at 1.6 rather than 1.75 to preserve that gap-crossing limitation.

Good, matches Classic's 2-tile-only ledge grab rule. Terminal velocity at 18 tiles/s is reached after 3.24 tiles of falling, close to Classic's 3.4 tiles — since terminal is hit early, damage tiers can be approximated as distance-based beyond that point even though the underlying physics rule is time-of-descent. I'm leaning toward implementing the fall counter as time-of-descent internally but displaying it as tile-equivalent distance for legibility, rather than a pure distance-based counter.

The owner accepted this plan: Spelunky's time-of-descent model for fall damage. Since time and distance become linearly equivalent after the 0.36s/3.24-tile terminal velocity threshold, I'm calibrating the damage thresholds so a walk-off fall lands cleanly at 8, 16, and 24 tile-equivalents — working out the descent times for each (roughly 0.62s, 1.07s, and continuing to the third tier).

I'm settling on 4 HP tiers matching the earlier HTML v3 draft: 7 tiles free, 8-15 tiles costs 1 HP, 16-23 costs 2, 24+ is death. Comparing this against Prince of Persia's much harsher system — where falling just 2 rows already costs a hit and 3 rows kills — confirms my thresholds are more forgiving, which fits the intended feel.

I'll expose the fall damage tiers as a tunable preset rather than hardcoding one scheme, letting me swap between the gentler Spelunky-style thresholds and the harsher PoP-style thresholds. Then I'll move on to defining the walk/run/crawl movement states.

For the actual speeds, I'm settling on 5.5/10/1.5 for walk/run/crawl. Ground acceleration should reach cap in about 0.06 seconds, matching roughly 2-3 steps at 30Hz. In the air, I'm using an acceleration of 0.65 times ground accel with no drag when there's no input, keeping momentum Celeste-style rather than the sharp deceleration Spelunky applies, where speed halves in about 3 steps due to its 0.8-per-step air drag.

I'm noting the turn delay from Classic as a decision point where facing flips immediately but acceleration waits two steps. For coyote and buffer times, I'm weighing Celeste's, Hollow Knight's, and Classic's values against the edge-precision goal, landing on 0.08 seconds for both since it doesn't conflict with the walk-off-and-grab mechanic. I'm also looking at how Classic ramps gravity from 0.1 to 1.0 over ten steps for variable jump height.

For the jump mechanism, I'm choosing Classic's held-gravity-ramp approach for that Spelunky feel, with apex heights specified as constants rather than launch speeds — a nice legibility trick where the implementation numerically solves for the required velocity at load time. Now I'm moving into ledge grab specs, defining the hand window and corner-only grabbing.

Working through the grab mechanics: no directional requirement on grab (matching the report's note that you can grab on the way up too), hang state disables gravity and locks the box to the block top, and exits include a buffered drop, fall-away, or Celeste-style climb-up with input lockout. I'm noting buffered drops should be included since they enable chaining hang-drops smoothly, then moving on to the crouch-and-walk mechanic for lowering off an edge.

There's a conflict to resolve here: Minecraft-style sneaking prevents walking off ledges, but I need crouch-walking to actually enable a controlled lower-off. My resolution is that crouch-walking stops you right at the lip (an edge-stop that visually signals the drop), and then holding toward the edge for about 0.12 seconds while crouched triggers the lower-off into a hang — this way both the safety-stop behavior and the intentional lower-off action are preserved.

Now I'm working out rope mechanics: four ropes available, throw-up arcs to a peak and anchors at the nearest solid tile column then unrolls downward; throw-down places a rope one tile ahead if the spot is clear; while hanging, pressing down with a rope hooks the current tile and unrolls further down. I'm also defining the mid-air catch — holding up while falling near a rope segment grabs it and cancels the fall, with climbing speed set at 3 tiles/s and jumping off giving a full jump with horizontal momentum.

Failed rope placements shouldn't consume the item, and catching a rope requires deliberate input rather than happening automatically, matching how ledge grabs work as intentional actions. I'm noting that walls belong in the second batch of verbs, kept after ropes as planned, and I'm sketching the peek-camera behavior: holding down with no horizontal input for 0.4 seconds scrolls the view downward at 8 tiles/s up to six tiles, with the character positioned near the top of the frame and the camera leading movement by a quarter tile.

For testing, I want the score loop to track depth in a small authored shaft with four ropes and four hit points, restarting on death, plus a landing readout. I'm planning to author test rooms as readable ASCII tile maps — one calibration room with flat ground, stepped ledges, and pits of varying depths, and one long descent shaft, though hand-building two hundred tiles deep seems excessive, so I'm leaning toward a seeded procedural generator for the stair-stepped terrain instead.

I'll keep the generator simple by stacking authored 16x8 ASCII chunks from a chunk library, chosen randomly by seed, so the shaft can be both hand-crafted and effectively endless. For debugging I want readouts covering state, velocity, fall timers, last landing speed and damage, ropes, HP, depth, and coyote/buffer flags, plus a hot-reloadable tuning table in its own file.

For controls I'm settling on A/D move, W/S for up/down, Space jump, Shift run, E for rope, R restart, F1 debug toggle, and 1/2 to switch rooms, pulling the actual input API from the agent's report. For verification, I'm sketching drive scripts to check jump apex accuracy, fall damage thresholds at various heights, ledge grabs, hang-drops, and rope throwing/catching behavior.

Now I'm setting up the delegation packet: Opus 5 runs as a background subagent via the Agent tool, registered under a dated run folder with brief.md, report.md, and run.json referencing my current session as parent. I'm placing the lab in reverse-minesweeper-fable/lab/ as a proper Anchor game directory with main.lua, boot.lua, and a copy of the anchor engine files.

While waiting on the agent, I want to independently check the sketch's index.html for existing human constants and control conventions, verify the human section's sizing, and look at an existing run.json in delegate/runs for the exact format to follow.

I'll look up the sketch's human-controller constants and controls to match the game's conventions, and check an existing delegate run record so I can copy the registration format exactly.

I'm still waiting on the Anchor orientation agent's result before I can write the brief and launch the Opus subagent. In the meantime, I could start drafting the constants table and spec sections of the brief file, leaving a placeholder for the Anchor facts to fill in once that result comes back.

The rest depends on the Anchor orientation result, so in the meantime I'll start drafting the packet with the constants, state machine, rooms, verification, and report format, adding the engine-facts section once the agent reports back.

I need the Anchor orientation agent's result to finish the "Anchor facts" section covering layout, run.bat, anchor.exe, input API, and hot reload. I'll hold off and let that agent confirm details like the tracked anchor.exe on Windows rather than duplicating the check myself.

The packet is drafted except for its engine-facts section, which depends on the orientation agent still running. I'll wait for its report, then finalize the brief and launch the implementer.

I'm figuring out that a game outside the engine repo doesn't need its own anchor.exe—its run.bat just needs to point to the engine's build binary using the correct relative or absolute path.

I'm also thinking through whether required modules like tuning.lua actually re-run on save given Lua's require caching, since the hot reload model apparently re-executes saved files by reassigning globals rather than relying on cached require results.

To handle this safely, tuning.lua should assign its table directly to a global rather than returning it, so reloads properly rebind that global, while derived/computed values get recalculated through a separate `tuning_derive()` function called both at boot and from an `on_reload` hook. I'm also noting that reload only fires on an explicit `engine_reload()` call, so the verification step needs the subagent to trigger that manually after edits.

For camera, since the framework's follow helper is a bit rigid, the implementer may just set camera position directly each tick to match the anchor/lead/peek spec, using attach/detach as the underlying mechanism -- and since we're rect-only, sprite anchoring isn't a concern.

Now I'm ready to finalize the brief by appending an "Anchor facts" section with verified details, then launching the Opus subagent in the background with the brief as its prompt, followed by writing run.json to track the start time.

The orientation is in and it changes two things in the packet: the lab does not need its own engine binary (the shared build at Anchor/engine/engine/build/anchor.exe runs it), and hot reload needs the tuning file to be a definition file that sets a global, with agent instances reloading only on an explicit engine_reload() call. Adding the engine-facts section, then launching the implementer.

Now I'll launch the Opus subagent, passing it the brief path and instructing it to read the file first and follow it exactly, keeping my own context minimal. Alongside that I'll write run.json with the start time—both tasks can happen independently right now.

While the implementer runs, I should share the number-reasoning with the owner in chat now, since he wants that judgment explained fully rather than held back until the end.

The implementer is running under the packet. While it builds, here is what the numbers said and what I picked, since that was the part you asked me to think about.

The one insight that reorganized the table. Raw tiles-per-second across games look chaotic (Terraria's gravity is 90, Celeste's 112, Spelunky Classic's 56, Spelunky 2's roughly 29) until you divide by the character's body height. Then terminal velocity lands between 14 and 19 body heights per second in Spelunky, Celeste and Terraria alike, and standing jump apex lands between 1.5 and 2.5 body heights everywhere except Jump King. The old sketch's terminal velocity was 50 body heights per second, which is why the human fell like a dropped stone. Our human is 0.8 tiles tall and Spelunky's is 1.0, so Spelunky's tile numbers transfer almost directly. I took terminal 18 tiles/s (Classic 18.75) and gravity 50 (between Classic and Spelunky 2), which means terminal is reached after 3.2 tiles of fall, same as Spelunky. That fact matters more than either number alone: because terminal comes early, "how long you fell" and "how far you fell" are the same measurement past the third tile, which is why Spelunky can count frames and still feel height-based. The previous report's own table said 20 tiles/s and called it 25 body heights per second, which contradicted its own normalization, so I lowered it.

Jump. Classic's held jump is 1.56 tiles and its ledge-grab hand window sits 0.8 tiles below the corner, so a 2-tile ledge is reachable from a standing jump and a 3-tile one never is. I kept exactly that geometry: apex 1.6 held, 0.8 tap, hitbox 0.8 tall. The report had 1.75, which would have crept toward the 3-tile grab. One structural choice: the tuning table stores apex heights, not launch speeds, and the lab solves the launch speed numerically at load. You tune what you see. The variable jump uses Classic's mechanism (gravity ramps from zero to full over 0.3 s while held, snaps to full on release) rather than Celeste's sustained-speed window, because that ramp is a large part of why Spelunky's jump feels the way it does.

Ground speeds are Classic's ratios (5.5 walk, 10 run, 1.5 crawl), cap reached in 0.06 s. The crawl tier is the precision instrument at edges and the sketch never had it. Air control is Celeste's 0.65 of ground acceleration, but air drag is Spelunky's: with no input, horizontal speed halves every 0.1 s, so a released jump drops nearly straight down. That is a controlled-descent property, not a limitation, and it is a single tunable if you hate it.

Fall tiers. Two presets in the tuning file, switched by one string. spelunky is 8 tiles = 1 HP, 16 = 2, 24 = death, free under 8. prince is Prince of Persia's grammar scaled to tiles: 4 = 1 HP, 8 = 2, 12 = death. The two are the real design fork. Spelunky's thresholds make most drops safe and reserve punishment for carelessness; Prince of Persia's make every drop a decision and put the hang-and-drop verb at the centre. Your thesis for the human ("if you go down too fast you die") reads closer to Prince of Persia to me, but the sketch was tuned on Spelunky-like values and was fun, so the lab ships with spelunky and the other is one word away. The character also changes colour mid-fall as it crosses each tier, so you can read the fall while it happens.

Ropes are Classic's rope with real flight (peaks about 8 tiles up after 0.6 s, unrolls at half a tile per step), plus Spelunky 2's addition of rope-from-hang: grab a ledge, look down, rope down from the tile you hang on. Rope catch is explicit (hold up), never automatic, matching the rule that ledge grab is a decision. Climb speed 3 tiles/s, between Classic's slow 1.9 and the sketch's 5.5.

Where I departed from the previous report's plan. Lowering off an edge merges two primitives: crouch-walking stops you at the lip (Minecraft's sneak, the brake that lets you look), and holding toward the drop for 0.12 s more lowers you into a hang on that same ledge. Climb-up is Celeste's mantle (rise straight up until the feet clear, then push over) rather than Spelunky's hop, which only works in Classic because of a double-impulse coincidence in the code. The ledge grab test is a sweep over the tick's path, not a point test, because at 18 tiles/s a 0.25-tile window would be skipped one tick in four. Coyote and buffer are both 0.08 s, Celeste's values with the coyote trimmed, so edge precision stays a skill.

What the lab contains. Three rooms: a calibration room with pits of exact depths and 1/2/3-tile steps, an endless 16-wide shaft built from authored chunks with a seed and a depth score (4 HP, 4 ropes, no refills), and a plain 3-wide shaft reserved for batch 2's wall work. F1 shows state, velocities, timers and the last landing. Every constant lives in tuning.lua with a comment naming the game it came from, and saving it while the lab runs changes the feel in place.

Rules of the parallel work. The packet forbids the implementer from reading or touching reverse-minesweeper-codex/, and everything lands under reverse-minesweeper-fable/lab/. The run is registered under the Anchor workflow's delegate records so it will be woven into this session's log.

When the report comes back I'll re-run its verification script myself, check the code against the packet, and hand over with test instructions.

With the implementer done, I need to follow the review protocol myself: save the report file since the subagent couldn't, update run.json with the finish time and subagent path, list and read the key files like controller.lua, main.lua, and tuning.lua, then re-run verification with anchor check and drive commands and inspect a snapshot or two before handing things over.

On the jump deviation, the implementer's reopen looks justified — my original brief was contradictory since a single launch speed can't produce both apexes when gravity ramps from zero. Their fix, starting the ramp at 0.189 of full gravity instead of zero, seems reasonable: with ramp-from-zero the tap-to-held apex ratio comes out to about 2.44 versus the target of 2.0, so starting the ramp partway in brings the ratio in line. That seems like an acceptable resolution.

Now I need to write the subagent's report into report.md — it's a substantial file, roughly 10KB — then update run.json and re-verify. I'll run those in parallel along with confirming the subagent's jsonl transcript path actually exists on disk.

The implementer's report is back with 47 of 47 checks passing and one legitimate reopen of a rule in my packet. Now the review: record the report and run registration, then re-run the verification myself and read the controller.

The report extraction didn't work as expected, so I'll write report.md directly from the notification text I already have in context. After that, I need to re-run verification by checking the lab, then driving through start, eval verify.lua, and stop in sequence.

I also want to review controller.lua and tuning.lua fully, plus view the calibration and shaft-descent snapshots — all independent tasks I can fire off together now.

Read (C:\Users\a327e\Desktop\a327ex\reverse-minesweeper-fable\lab\tools\snapshots\calibration.png)

Read (C:\Users\a327e\Desktop\a327ex\reverse-minesweeper-fable\lab\tools\snapshots\shaft-descent.png)

The verification re-run seems to have passed based on the tail output, but I should grep verify-report.txt for the actual pass count to be sure. Looking at the calibration screenshot, I notice the debug readout text overlaps with the "STEP 3 (no grab)" world label, causing a visual collision with "state stand facing 1".

On the code side, I'm checking through the player physics logic: crouch handling before jumps looks fine since jumping from crouch requires can_stand, coyote-time jumping correctly sets state to 'jump', and the ledge grab direction check using IN.x requires the player to be actively pressing toward the wall. The touching-tolerance check in ledge_grab_at matches the expected Spelunky-style behavior since horizontal movement resolves before the grab check, ensuring the player is flush against the wall when grabbing.

One edge case worth flagging in the hang state: if jump is buffered within 0.08s before a grab happens (while falling, not holding down), the buffer could trigger an immediate climb-up mantle on grab, which is a slightly surprising "pre-press" auto-mantle behavior. It's a minor timing quirk but plausible as intentional input buffering, so I'll leave it as is rather than patching it.

Checking the rope logic next: jumping off a rope correctly clears the rope reference and applies horizontal kick based on input direction, defaulting to zero kick when no direction is held. The rope-catch condition properly requires holding up, or down while airborne, matching the intended design. Rope-throw while hanging uses the player's own tile column for placement, and the rope's flight trajectory checks for solid tiles to anchor properly at the ceiling.

Fall tracking captures the starting height only once when falling begins, landing logic nudges the player down by a small probe amount each frame to stay glued to the floor, and hanging state zeroes velocity with gravity disabled — all consistent. I also confirm the dead-state guard and camera pixel conversion are correct, and crouch gets reset every frame while airborne as expected.

The ledge-grab logic properly respects the hang lockout timer, and the jump-ramp apex resolution using a fixed initial velocity for taps versus a ramp for held jumps seems sound. Hot reload at 2Hz for tuning values looks good too. Now I need to verify the test totals in the verify report and confirm the freeze/delivery checklist.

For delivery, I'll send the two static snapshot images (calibration-pits.png, shaft-descent.png) directly, note the report will be woven separately from the delegate runs, update the README to document the lab folder and how to run it, update the memory project file with build status and next steps for batch 2 walls, note the review outcome in run.json, and prepare a handover message with test instructions. I also notice a minor HUD debug text overlap issue in the calibration room worth flagging.

Verification passed clean: static check and assertion script both succeed, and the controller code matches the packet including the reopened jump-solve rule. Now I'll confirm the pass count, mark the run reviewed, update the README and memory, and send the snapshots.

Batch 1 is built, reviewed and ready for you to play. It lives at reverse-minesweeper-fable/lab/.

How to test. Run lab/run.bat. Keys: A/D move, S crouch (and down), W up, Space jump, Shift run, E throws a rope up, S+E throws one down (from a lip, or from a hang), R restarts, 1/2/3 switch rooms, F1 toggles the debug panel. Room 1 is calibration: three steps of 1, 2 and 3 tiles (the 2-tile step should catch a ledge grab from a standing jump, the 3-tile never), two chained grab walls, then a row of pits labelled by depth. Room 2 is the score loop: an endless 16-wide shaft of authored chunks, 4 HP, 4 ropes, no refills, depth is the score, seed shown in the corner. Room 3 is a flat-walled shaft with nothing to do in it yet, so you can feel what walls are before batch 2 adds sliding.

The things I most want your read on:

• The hang-drop chain. Crouch-walk to a lip: you stop at the edge. Keep holding toward the drop for a moment and you lower into a hang. Then S+Space drops, Space climbs back up, S+E ropes down from where you hang. That sequence is the Prince of Persia grammar and the whole bet of the human stage.
• Ledge grabs are decisions. You only catch a corner while holding toward it, and you can catch on the way up as well as down. Passing a rope only catches if you hold W.
• The fall tell. The character goes green, yellow, orange, red as the fall crosses the damage tiers, so you can read a fall while it happens.
• Everything in tuning.lua hot-reloads. Save the file while the lab runs and the value is live. Two things worth trying by hand: set fall_preset = 'prince' (4 tiles = 1 HP, 8 = 2, 12 = death) and see whether the harsher grammar suits "go down too fast and you die" better than Spelunky's 8/16/24; and change jump_apex_held or walk_speed to feel the tuning loop.

One deviation from my spec, which I accept. I asked for one launch speed that hits both a 0.8-tile tap and a 1.6-tile held jump with gravity ramping from zero while held. That is arithmetically impossible: the tap would have to launch faster than the held jump. The implementer solved the launch speed from the tap apex and the ramp's starting gravity from the held apex instead, so both heights come out exactly and the ramp starts at about a fifth of gravity rather than zero. Setting jump_ramp_from = 0 in the tuning file restores the literal ramp if you want to feel the difference.

Verified mechanically. The static check is clean, and I re-ran the implementer's 47-assertion script on a fresh agent instance: jump apexes, the three ground speeds, terminal velocity, every fall tier at its pit, the 2-tile versus 3-tile grab, drop and lockout, mantle, lip stop and lower-off, both rope throws and the rope-from-hang, the mid-fall rope catch, the jump-off kick, coyote time, the peek. Hot reload was proven through the eval channel. Feel is yours.

Noticed, left alone. The 0.8-tile body means no gap on a whole-tile grid needs a crouch, so crouching only has the lip-stop and lower-off jobs for now. Rope-from-hang anchors in your own column beside the wall, since the ledge tile itself is solid. In the calibration room the F1 panel overlaps a couple of the world labels. The run is registered under the Anchor workflow's delegate records and will weave into this session's log.

Batch 2 is walls: hold-toward slide with Celeste's ramping speed cap as the budget, and a wall jump. I'll wait for your play before starting it.

Lots of details to fix but I'd like you to proceed first with the next batch.

Since the owner wants batch 2 now, I'm focusing on wall interactions: the hold-toward wall slide with Celeste's ramping cap, wall jump with a forced-move window, and interaction rules covering ledge grabs and ropes, plus building out the walls room. That maps to phase 4 of my plan, with phase 5 covering the richer descent kit extras like parachute, glide, and landing.

I'm keeping this batch scoped to walls only rather than pulling in descent extras, and turning the walls room into a real test space with wall-jump shaft geometry before writing the packet quickly and delegating to the Opus subagent in the background. Now I'm working out the wall slide mechanics: triggering when airborne, holding toward a touched wall, moving downward, and not at a ledge-grab corner, with the slide speed ramping from a starting cap toward terminal velocity over a cumulative slide-time budget that resets on landing, ledge grab, rope grab, or wall jump.

I've decided the budget does not reset on wall jump, so chaining wall jumps down a shaft keeps eating the budget and keeps a long wall dangerous, while jumping up doesn't need sliding at all — this is vetoable. I'm also settling that pressing down while airborne against a wall cancels the slide and lets you fall at full speed, and that fall-time counts at a reduced rate during a slide rather than resetting outright.

But I realize the flat reduced-rate approach creates a mismatch — a slow 3 tiles/s slide would still count as a big chunk of equivalent descent even though little height was actually lost. A more principled fix is to scale the fall-time accumulation by the ratio of current velocity to terminal velocity, so a slow slide barely counts while a fast, budget-exhausted slide counts fully.

For the wall jump itself, I'm working out the trigger conditions: jump pressed while airborne with a wall within a tiny reach distance on either side, no directional input needed. The launch gives the same vertical jump velocity (with variable hold) plus a fixed horizontal speed pushing away from the wall, along with a brief forced-control window afterward.

I'm also thinking through the priority between ledge grabs and wall slides—since grab corners sit at the top of a wall, touching a wall below that corner window means you slide instead of grab, and sliding sets your facing direction toward the wall.

I should also test a narrow 1-wide chimney since the body is 0.6 wide, a tall 30-tile wall to check slide budget exhaustion and terminal velocity, a pit only escapable via wall jump, and a ledge on a wall face for slide-to-grab transitions. I'll add a debug readout showing slide budget, wall contact side, and forced-move timer, then verify slide speed starts at 3 and hits terminal after budget runs out, wall jump kick is 8 with a 0.15s forced window, chain jumps climb a 3-wide shaft, pits are escapable, down cancels slide, and sliding the full 30-tile wall causes at least some fall damage once the budget depletes.

I still need to check ledge grabbing while sliding into a corner and wall coyote time. The owner flagged some minor items to fix later, so I'll leave those alone for now. I'll write this up as a delta brief referencing the batch-1 packet for the Anchor facts and code, then register and launch the run.

Proceeding with batch 2, walls. Writing the packet as a delta on batch 1 and launching the implementer.

The implementer is running now with nothing else to act on, so I'll share the batch 2 design decisions with the owner in chat since fast mode defaults to listing them at handover for veto, then wait.

Batch 2 is running under its packet. The wall design it implements, so you can veto any of it while it builds:

• Slide is hold-toward and automatic, no grab button, no stamina bar. Touch a wall in the air while holding toward it and moving downward, and you slide. Facing snaps to the wall.
• The slide is a budget, not a speed. A fresh slide caps at 3 tiles/s and the cap ramps linearly to full terminal velocity over 1.2 s of cumulative sliding per airtime. The budget refills on landing, a ledge grab or a rope catch, and deliberately not on a wall jump, so bouncing down a long shaft stays dangerous.
• The fall clock keeps running while sliding, in proportion to slide speed. A slow slide barely counts, a spent-budget slide counts like a fall. A slide never resets the counter, so sliding the top of a long wall and then letting go lands with the same tier as a plain fall.
• Wall jump needs no direction input: jump within 0.15 tiles of a wall in any air state launches away at 8 tiles/s with the normal variable jump, and input toward the wall is ignored for 0.15 s. A short wall-coyote window of 0.06 s allows a jump just after leaving a wall.
• Priorities: a corner within the hand window grabs before the slide check runs, so sliding down a wall with a protruding block ends in a hang. Holding down cancels a slide. W still catches ropes.
• Room 3 becomes real: a 3-wide shaft you must wall-jump out of, a 2-wide shaft, a 1-wide chimney, a 30-tile flat wall to feel the budget run out, the same wall with one protruding block to catch, and an 8-deep pit to escape.

The verification list extends the 47 batch-1 assertions with a dozen wall ones; I'll re-run the whole file on a fresh instance before handing over.

What's taking so long?

The owner wants to know why this is taking so long. Batch 1 took about 33 minutes and batch 2 is still running with no completion notice yet, so rather than reading the full transcript (which would overflow context), I should just check file modification times in the lab directory to get a cheap, non-invasive read on progress.

Looking at the timestamps, the implementer has been mid-edit for a few minutes across several core files but hasn't touched verify.lua yet, meaning the batch checkpoint hasn't been reached.

So the update to the owner: 17 minutes into the run, code is written, verification hasn't started, and since batch 1 previously took 33 minutes, this is roughly on pace at the halfway mark — nothing further needs to be flagged.

It's 17 minutes in, and it's roughly at the midpoint. The implementer wrote its wall code in the last few minutes (the controller, tuning, rooms, view and boot files all changed two to four minutes ago) and has not yet touched the verification script, so the remaining half is extending the 47-assertion run with the wall checks, driving a fresh instance through all of it, and taking the snapshots. Batch 1 took 33 minutes end to end, and this batch has the same verification tail, so I'd expect the report in another 10 to 15 minutes.

The time goes where it should: most of a batch is the implementer driving an agent instance through the assertions and fixing what fails, which is the part that keeps failures off your test loop. If you'd rather play batch 1 in the meantime, lab/run.bat still runs the batch-1 lab as it was, but note the implementer is editing those same files live, so a save mid-edit could reload into a broken state. Waiting is safer.

The batch 2 report is in, so I'm reviewing it: saving report.md, completing run.json, re-running verification with the anchor check and verify.lua on a fresh instance, then checking the walls diff in controller.lua and the walls-slide snapshot before handing over. The key issue to judge is the budget draining from the first tick with no plateau at 3 — the implementer suggests draining only when the wall is actually holding velocity back at the cap, which matches what I'd intended.

Working through the math, I confirm the crossing point lands at vy=4 given the gravity and ramp rates, so the lack of plateau is just an inherent property of the linear ramp starting from a low cap — not a bug. Comparing to Celeste, its cap also ramps from frame one with no plateau, just at values where the rise happens fast enough to feel instantaneous; here the same mechanic just plays out more visibly as a smooth accelerating slide, which is actually the intended feel.

The other findings — ledge-grab across a shaft being a tight 2-3 frame input, a 30-tile slide being lethal given the fall factor, and wall jumps requiring held input — are all real but fall into tuning territory rather than bugs, so I'll flag them for the owner without changing anything myself.

Now I'm moving into the parallel review actions: writing up report.md, updating run.json, re-running the check and verify steps, and pulling up the walls section of controller.lua to confirm the new functions and the air-update region match what's described, plus reviewing the walls-slide.png output.

Batch 2 is back: 84 of 84 assertions, one station in my packet found to be geometrically impossible and replaced with the nearest constructible one, and one of my assertions shown to contradict the model I specified. Reviewing now: saving the report, re-running the verification on a fresh instance, and reading the new wall code.

Read (C:\Users\a327e\Desktop\a327ex\reverse-minesweeper-fable\lab\tools\snapshots\walls-slide.png)

All 84 tests pass on re-run and the code looks coherent. I'm checking the wall-jump-from-slide interaction: since wall_lock is set after a wall jump, sliding correctly evaluates to false afterward, and wall_jumped_tick preserves horizontal velocity as intended. I'm now looking more closely at the air-update wall jump check, which triggers whenever buffer is positive during any airborne state.

Now I need to wrap up: save the report, update run.json with the finished status and review notes, edit the README and memory to reflect batch 2 completion, send the wall-slide and wall-jump snapshots, and then write the handover message.

Verification re-run on a fresh instance by me: 84 of 84 pass, static check clean, and the wall code reads correctly against the packet. Closing out the run record and handing over.

Batch 2 is in the lab and reviewed. Same lab/run.bat; press 3 for the wall course.

How to test. Room 3 is a walkway with nine stations, each a lane you drop into: a 3-wide shaft you must wall-jump out of, a 2-wide shaft, a 1-wide chimney, a 30-tile flat wall to slide down, that wall with a block 12 tiles down, a pillar across a lane to catch while sliding, an 8-deep pit with one rough wall, and a wall that ends in mid-air for the coyote window. Walls slide when you hold toward them in the air. Space near any wall wall-jumps away, no direction needed. A thin bar on the wall side of the character drains as the slide budget goes. Rooms 1 and 2 are unchanged in layout but every wall in them now slides, which changes the shaft.

Three things the build found that are design questions, not bugs.

• A slide can never catch a corner on the wall it slides down. Geometrically: sliding keeps you flush against a column that continues below, and a block protruding from that column is under your feet, so you land on it. The only slide-to-grab is across a gap, and at full slide speed that is a two-to-three-frame input. If that verb matters at depth it needs a wider hand window, a slower ramp, or a wall jump into the grab.
• The 30-tile slide is still lethal. The budget buys back under 3 tiles of the 24-tile death tier. The wall delays you, it does not save you. That is what the tuning table produces at a fall factor of 1; wall_slide_fall_factor and wall_slide_budget are the two knobs.
• Wall-jump chains need the jump button held. A tapped wall jump buys the 0.8-tile apex and you sink. Real skill floor; feel it before tuning.

One of my own assertions was wrong. I asked for the slide to "settle at 3 tiles/s while the budget is fresh". Under Celeste's model the cap starts rising the moment the slide starts, so the speed tracks a rising cap and never plateaus; it meets the cap at about 4 and climbs to 18 over 1.2 s. That is the model I specified and it is Celeste's, so I kept it. If you want a real slow plateau, draining the budget only while the wall is actually holding you back is a one-line change I'd make on your word.

Verified. Static check clean; I re-ran the full 84-assertion script on a fresh instance. The run is registered and reviewed under the delegate records.

You said batch 1 has lots of details to fix. Whenever you send the list, I'll take those directly rather than through a packet, since fixing against your feel notes is the part that stays with me.

A lot of things to tune, but let's keep moving, what would you do next?

He's asking a judgment question about what to do next, so per CLAUDE.md I should lay out options with a recommendation and stop there rather than just proceeding. I'm weighing candidates like adding descent extras as toggles—parachute auto-deploy and similar features from phase 5 of the report—against other possible directions.

My real recommendation is porting the dig-game itself: world gen, robot stage, and camp loop onto the controller, since the lab's tuning is meaningless without real terrain and the sooner the human controller meets the robot's craters, the sooner we know if the two-stage core survives in Anchor. I'd split this into batches, starting with porting the dig game—tile world, mines, digging mechanics, blasts, nuggets, depth lines, and the countdown clock—as the robot stage moved from index.html into Anchor on the same tile system.

The second batch would stitch in the two-stage loop with powerdown, camera pan, human descent using the lab controller, and camp cycling with score tracking, and I think robot stage should come first since it's the validated fun piece independent of the controller. The robot stage's mouse-driven digging and key controls represent roughly 600 lines of JS that could be ported faithfully by treating index.html as the spec, and I'm now weighing whether to keep the lab codebase and just add the dig world as a new room, letting the lab's debug rooms stay accessible within the same game directory rather than splitting into a separate project.

I should present this as options A/B/C with a recommendation for B, sketch out concretely what the first stage of B looks like, then stop and let him decide since he asked for my take — keeping the response tight rather than exhaustive.

Port the dig game onto the controller next, and treat the descent extras as things to evaluate inside the real game rather than in the lab. Reasoning and the alternatives:

Why the port now. The lab's shaft chunks are a stand-in for the terrain the human will actually descend: robot-dug shafts and mine craters. Craters are round, so their walls are stair-stepped and every step is a ledge; dug shafts are one to three tiles wide, which is exactly the wall-jump and chimney geometry. Every tuning question the lab has raised (how lethal a long slide should be, whether the slide-to-grab needs a wider window, the wall-jump skill floor) is answered by that terrain, not by the calibration rooms. Tuning further in the lab risks tuning for chunks I authored rather than for craters the mines make. The robot stage is also the validated fun, and it has been sitting in an HTML file for eight days; the sooner both halves run in Anchor the sooner we know whether the two-stage core survives the engine change.

The shape, two batches.

1. The robot stage. Port the dig game from the v3.1 sketch, which is the spec: the infinite tile world with mines and numbers, the 9x7 reach rectangle with hold-to-dig, flags, mine blasts with the 2.5-tile radius and chaining, buried nuggets that fall out and get collected, depth lines every 10 m refunding the clock, the countdown, the stats. Same tile grid, same tuning-table pattern, the dig tunables in the same file as the controller's. The lab's three rooms stay as debug rooms behind the number keys, the game world becomes room 4. The lab folder is the game from here; it just grows.
2. The two-stage loop. Power-down, the camera pan back to camp, the human descending with the lab controller, camp at the robot with heal and rope refill, the next dig starting from camp, death and score. This is the batch where the lab's tuning starts to mean something, and where I'd expect your list of details to get longer, not shorter.

The alternatives I'd set aside for now.

• A. Descent extras first (auto-parachute, hold-to-glide, a timed landing roll). Cheap toggles, but each is a bet on what the human needs, and the need only shows up in the craters. After batch 2 of the port they are an afternoon.
• C. The character's look. You deferred it and I agree; the controller is a green box until the game around it is stable, and a body taller than a tile would change the crouch geometry the lab just settled.
• D. Your tuning list. Whenever it arrives I take it directly, between batches or during one, since the packets touch different files from the constants.

One thing I'd decide before the port and would like your word on: the sketch's robot digs with the mouse (hold the left button inside the reach rectangle) while the human is keyboard-only. In Anchor that stays as is for the port, since faithfulness is the point of a port. But if you already know you want the robot on keys too, say so now and the port does it once rather than twice.

If you say go, batch 1 of the port starts under a packet the same way.

Go ahead with your preference.

I'm porting the first batch as room 4 in lab/, keeping the mouse digging mechanic faithful to the original. I need to write the spec in index.html for the implementer, laying out the closed decisions: same tile grid, having tile_solid consult a sparse, lazily-generated row map that extends infinitely downward, and adding tuning constants for density, treasure, blast radius, chain blast, and dig behavior.

The robot needs its own kinematic movement using the sketch's original speed, gravity, and jump values, reusing the same collision sweep but without ledge grabs, ropes, or fall damage since it's a robot that can fall any distance. For mouse input, I need to note the RMB button mapping and flag the fact that the implementer will need to look up the framework's function for converting mouse position to world coordinates through the camera.

The world generates sparse rows lazily and seeded, with each tile tracking solid/mine/dug/flag state and a cached mine-count number shown on exposed tiles adjacent to dug ones. Digging a mine triggers a blast clearing a radius and chaining other mines, nuggets fall out under gravity and get collected by the robot on touch, depth lines every 10m grant bonuses, and dig time scales with depth up to a cap while the countdown clock ticks and score tracks max depth reached.

I should focus on porting only the robot 'play' state faithfully — world generation, digging, blasts, nuggets, lines, clock, stats, HUD, and drawing — while skipping the human/powerdown/camp states and bot simulations, which belong to a later batch. The robot is controlled with A/D to move and W to jump, with a reach rectangle and target tile highlight drawn based on the cursor.

The camera should generalize to follow whichever actor is active, so the robot stage reuses the same camera logic as the player. For tile collision, rooms.lua needs a 'world' mode where tile_solid queries the sparse world data instead of the fixed room maps, without touching the lab controller's behavior.

For verification, I'm planning to check world generation determinism via seed, mine density, digging through injected mouse events, correct neighbor-count numbers, blast radius/chaining, nugget spawn/fall/collection, depth line bonuses, and the clock reaching zero to trigger a powerdown placeholder.

Scope stays within lab/ files, allowing new world.lua, robot.lua, and dig.lua modules while keeping the controller mostly untouched. I'll write up the packet now and launch it without needing to re-check index.html myself, since the implementer will read that directly.

Going with the port. Batch 1 of it is the robot stage, with the v3.1 sketch as the spec. Writing the packet and launching.

The robot-stage port is running under its packet. What it builds, so you can veto while it runs:

• Room 4, key 4, is the sketch's play state ported rule for rule: the seeded sparse world with mines and numbers, the robot with the sketch's own movement numbers, the 9x7 reach rectangle with hold-left-button digging and right-button flags, dig time growing with depth and mines taking the full time, blasts with radius and chaining, nuggets falling out and refunding the clock, depth lines every 10 m refunding it too, the countdown, the stats. Its look is the lab's rectangle style with numbers in the lab's font.
• The world is deterministic by seed, hashed per tile rather than drawn from a stream, so the same seed gives the same rows no matter which rows you touch first. That matters later for replays and for the verify scripts.
• One grid query. The controller's only question of the world is "is this tile solid", so the human controller will run unchanged on the dug world in the next batch. The robot reuses the same collision sweep but none of the human's verbs: no grab, no ropes, no fall damage.
• When the clock hits zero the run just ends with a banner and the depth. The power-down pan, the human descent and the camp loop are the next batch.
• Everything from the sketch's tunables lands in the tuning file under a dig block, hot-reloadable like the rest.

The verification adds determinism, density, number correctness, a digging test through injected mouse input, blast and chain, nuggets, lines, the clock and the stats to the existing 84 assertions. Expect it in roughly half an hour; I'll re-run the whole file before handing over.

I should finish up by saving the report, completing run.json, re-running the check and verification, and spot-checking a couple of snapshots. I also want to quickly grep the controller.lua diff for camera_target changes, then update the README and memory before handing off — the deviations I found look acceptable overall.

The robot stage is ported: 135 of 135 assertions and nothing stopped. Reviewing the same way: saving the report, re-running the verification myself, checking the one controller change and the snapshots.

Read (C:\Users\a327e\Desktop\a327ex\reverse-minesweeper-fable\lab\tools\snapshots\game-dig.png)

Read (C:\Users\a327e\Desktop\a327ex\reverse-minesweeper-fable\lab\tools\snapshots\game-blast.png)

Everything's verified now, so I'll save the report file as-is, update the README and memory, send the snapshots, and prepare the handover message — these are all independent tasks I can do together in one response.

The robot stage runs in Anchor. Same lab/run.bat, press 4.

How to test. It is the sketch's robot round, rule for rule: A/D move, W or Space jump, S digs under your feet, hold the left mouse button on a tile inside the reach rectangle to dig it, right button flags. Numbers appear on every exposed face, mines take the full dig time and blast a 2.5-tile crater that chains, nuggets fall out of dug tiles and refund the clock, depth lines every 10 m refund it too. When the clock hits zero you get an out-of-energy banner with the depth and stats, and R restarts. Every tunable from the sketch is in the tuning file under a dig block and hot-reloads like the rest; T.seed pins a world (the seed shows in the HUD, so a run you liked can be replayed).

What the port changed on purpose. The camera is the lab's, with its velocity lead, not the sketch's plain follow; you will feel the view run ahead of the robot on a long fall. The view is 20 tiles wide against a 16-wide world, so bedrock is drawn at the sides rather than void. The reach rectangle is drawn as a faint outline, which the sketch never did. Everything else is meant to be the sketch, including two things the implementer noticed and correctly left alone: a blast often leaves the robot standing on air, and the energy economy is generous enough that an open-shaft fall banks more clock than it spends, so all the tension comes from digging costing time. Both are play questions for you, not port questions.

Verified. Static check clean; I re-ran the full 135-assertion script on a fresh instance, including world determinism under scrambled access order, mine density, number correctness against an independent count, digging through injected mouse input, blast and chain, nuggets, depth lines, the clock and the restart. The run is registered and reviewed.

Next is port batch 2, the loop: clock out, the camera pans back to camp, the human descends the dug world with the lab controller, camp at the robot with heal and rope refill, the next dig from camp, death and score. That is the batch where the two halves meet and where your tuning list will matter most, so if you want to play the robot stage first and send notes, this is a natural point to do it. Otherwise say go and I'll write the packet.

You can go ahead, you can also remove or decrease the velocity lead, at least vertically, it's going down too much and too easily. This is something we have to work on manually later to fix more carefully.

I want to reduce the vertical camera lead since it's dropping too easily — I'll cut `cam_lead` down to something like 0.08, or even 0 to be conservative, as a simple one-line tuning tweak in tuning.lua.

Now for batch 2, I'm designing the power-down/human-descent loop: after the robot runs out of power it stops and shows a banner, the camera pans to camp, then the human spawns with ropes and HP to descend and reach the robot, triggering a new camp that heals, refills ropes, recharges the robot, and increments the cycle. Death happens at zero HP with a depth-based dead screen and restart, with score tracked as max robot depth — I'm adapting the sketch's fall-damage mechanic to the lab controller now.

I also need to handle the offscreen robot marker during human/powerdown phases, camera and controls switching to the human, camp positioning logic (initial surface spawn versus later robot position), resetting the clock to time0 each new cycle, disabling digging for the human while keeping wall-jump support, and ensuring the robot only powers down once it's grounded rather than mid-air.

On death, the human should see a "FELL TO DEATH" banner with depth and a restart prompt, and R should start a fresh run. The HUD in human mode needs hearts, ropes, the offscreen robot distance marker, and depth tracking, with falls incrementing stats. I'm running through the full verification checklist: powerdown timing, camera pan, human spawn stats, touching the robot to heal and advance the cycle, death and restart behavior, marker visibility, disabled digging, and mines being solid but harmless to the human. I still need to fix the camera lead behavior myself.

I'll go read tuning.lua and make an edit there, then launch the packet — making sure the packet doesn't touch cam_lead.

Two things: the camera lead is a one-line tuning value, so I'll zero it myself now, and the loop batch goes out under a packet.

The camera lead is removed: cam_lead is 0 in the tuning file, with a comment recording your reason, so the view now follows the actor with only the tween. It reloads live if the lab is running. The camera stays on the list for a careful pass by hand later.

The loop batch is running under its packet. What it builds:

• The sketch's state chain. Clock out, then power-down only once the robot is on the ground, the banner, the camera pan back to camp over the sketch's pan time, the human spawning at camp with 4 HP and 4 ropes, the descent, camp on touching the robot with the sketch's heal, rope refill, robot recharge and cycle count, then the next dig from that camp. Death on 0 HP with the sketch's banner, R restarts.
• The human is the lab controller, unchanged, running on the dug world. Mines are inert solid tiles for the human, the mouse does nothing in the human stage, ropes are the lab's and persist across cycles.
• Score stays the robot's max depth, as in the sketch, with a session best on the death banner. The ROBOT off-screen marker returns for the descent.

The verification adds the full cycle twice over, the pan timing, spawning on solid ground, ropes on the dug world, camp arithmetic from 3 HP, death and restart to the existing 135 assertions. I'll re-run everything before handing over.

I should finish up the same way as before: save the report, complete run.json, and re-run verification. Since game.lua is new, I want to skim through maybe 300 lines of it, and check the game-rope and game-powerdown snapshots. Then I'll hand over the key findings — the design issue where you can't fall past the robot, the clock showing 0 during the camp banner — and update the README and memory notes.

The loop batch is back with 216 of 216. Reviewing: saving the report, re-running the verification, reading the new loop file, and viewing the descent snapshots.

Read (C:\Users\a327e\Desktop\a327ex\reverse-minesweeper-fable\lab\tools\snapshots\game-rope.png)

Read (C:\Users\a327e\Desktop\a327ex\reverse-minesweeper-fable\lab\tools\snapshots\game-powerdown.png)

Everything checks out, so now I'll save the report file, update the README and memory, send the two snapshots, and hand things over — all independent steps I can do right away.

The whole game now runs in Anchor. Same lab/run.bat, press 4: the robot digs until its clock runs out, the view pans back to camp, you descend with the lab's human, touching the robot makes a new camp with a heal, a rope refill and a recharged robot, and the next dig starts from there. Death ends the run with the sketch's banner and R restarts.

Verified. Static check clean; I re-ran the full 216-assertion script on a fresh instance, including two complete cycles, the pan timing, spawning on solid ground at a deep camp, ropes on the dug world, the camp arithmetic from 3 HP and 2 ropes, death and restart, and the ROBOT marker. The human controller file is byte-identical to batch 2; the loop lives in its own file. Four delegate runs are registered and reviewed for this session's log.

Three findings you should feel before we tune anything, all faithful to the sketch:

• You cannot fall past the robot. Reaching it is a 1-tile touch test evaluated every tick, so any drop whose line passes through the robot becomes a camp, however lethal the fall was. A straight drop down the robot's own shaft is always safe. Whether reaching the robot should require landing beside it rather than touching it is the biggest open design question the port surfaced.
• Only a fall ends a run. The clock refills fully at every camp, so run length is set by the human, and the human's fastest way down is also the safe one whenever the robot sits under a clean shaft. The tension lives in ragged blast walls.
• The clock shows 0.0 through the camp banner, because the sketch refills it on leaving camp rather than entering. One line to move if it reads wrong.

Smaller things the implementer left as the sketch had them: nuggets are only collected by the robot, ropes persist forever, the descent help overlay shows for 8 seconds of every descent, and the tent hides under the robot at camp.

That completes the plan you approved: controller lab, walls, robot stage, loop. Everything from here is tuning and details against your play, which I take directly rather than through packets. Send the list whenever you have it, in any order; camera first is fine since you already flagged it.

Very very good, what would you do next?

He's asking what I'd tackle next, so I want to weigh a few candidates: his play session and tuning list, the fix for falling past the robot plus an initial balance pass, the descent extras toggles, and the notable gap that the fable folder has no git repo at all — everything's sitting uncommitted on disk, a real backup risk since the sketches repo was private.

Given his wipe-test concerns and worry about single-copy inventory, I think initializing a git repo there and pushing to a private remote is cheap and worth flagging as an ask. I also want to suggest a replay-review loop — he plays a session, the game auto-records it, and I read the .apr replay frames afterward to see what happened at landings, which matches the report's idea and makes his sessions reviewable without me needing to be present live.

My recommendation: commit the folder to a private repo now for safety, have him play one full recorded session for me to review afterward, then tackle the touch-vs-land question and tuning pass together — keeping everything serial rather than parallel, and noting a natural stopping point given this is already a long session.

Three things, in this order.

1. Put the folder under version control before anything else. Everything in reverse-minesweeper-fable/ exists once, on disk, uncommitted: the recovered transcripts, the reference corpus, and four batches of game. The sketch had a private repo before the wipe. I'd git init there, commit, and push to a private GitHub repo. That last step publishes to an external service, so I want your word on the repo name and that it goes to GitHub at all. Five minutes, and it turns today's work from a single copy into a safe one.

2. You play a full session, and I read the replays. Every visible run of the lab auto-records an .apr into lab/replays/. That means your play is reviewable by me after the fact: I can render frames from the recording around each landing, each death, each rope throw, and see what actually happened rather than reconstruct it from a description. So the next unit of work is yours: play rooms 1 to 4 for as long as it stays interesting, keep your list in whatever form is fastest, and hand me the list plus the pointer to the session. I'd then work the list directly, camera first as you flagged, with the replays as evidence. This is the feel loop and it cannot be delegated or skipped.

3. Then the two design decisions the loop surfaced, settled together with the tuning pass, because they interact with every number: whether reaching the robot means touching it or landing beside it, and how the fall tiers and the slide budget should read once the human is descending real craters rather than my authored chunks. I have a view on both (landing, not touching; and the Prince of Persia preset is closer to your stated thesis than Spelunky's), but they are yours to call after playing, not mine to pre-empt.

What I would not do next: the descent extras (parachute, glide, landing roll), the character's look, or the robot on keys. All three are bets about what the human needs, and one play session answers more of that than another batch would.

One housekeeping note: this session is long and carries four delegated runs. Ending it after the repo push, and starting the tuning work in a fresh session that reads the folder README, would keep the log readable and the next session's context clean. Your call on when.

Let's end this session here, name it Reverse Minesweeper Prototype Fable.