OMEGA_APP_PLAN.md

1    # Anchor — The Omega App
2   
3   ## Vision
4   
5   The omega app is the next evolution of Anchor: a single application for all creative work, built entirely with the Anchor engine. It replaces the scattered collection of tools (Notepad, NeoVim, Claude Code, Explorer, DAW, browser) with one unified environment owned completely by the user.
6   
7   The core insight comes from 4 months of using Claude Code daily: AI is good enough that you stop reading code. Once you stop reading code, you lose ownership of the codebase. Once you lose ownership, you realize what you actually needed to own wasn't the code — it was the *environment*. The code is replaceable. The environment shapes everything.
8   
9   ### The Ownership Thesis
10  
11  Claude Code's terminal UX nudges you away from ownership. You see only the snippets the AI chose to focus on. There's no physicality, no sense of place in the codebase. The file is never yours. Tools like Cursor have an inherent advantage because the feeling of physicality and place turns out to be important.
12  
13  The solution: build your own space. Not just an editor — a complete workspace where every feature exists because it's needed, where AI integration works exactly right, where ownership is absolute because you built everything yourself.
14  
15  ### The Felt Sense of Place
16  
17  One framing that emerged was the app as a personal MMO — a 2D world where the "city" is the workspace. Different districts for different work, NPCs as AI agents, files as inventory items, quests as commitments. This isn't the practical implementation, but it surfaced something real: **the felt sense of place matters**. The reason code ownership was lost isn't just that code stopped being read — it's that there was never a *place* in it. The code existed nowhere. It was a stream of diffs.
18  
19  The practical version keeps the ideas with genuine functional benefit — spatial canvases, persistent AI agents, modes, filesystem-as-database — and drops the fantasy elements. Closer to a meticulously customized Emacs or a Bloomberg Terminal than to Stardew Valley. Dense, keyboard-first, information-rich, every pixel earning its place. But retaining warmth through considered visual design and the fact that it's a place built for oneself.
20  
21  ### Triple Use
22  
23  Everything built for this app has potentially triple use:
24  1. The development environment (daily work tool)
25  2. The website (a327ex.com rendered by the engine via WASM)
26  3. Artistic artifacts (games, interactive books, music)
27  
28  The engine already compiles to WebAssembly. The website becomes an Anchor app. Blog posts are rendered by the engine, not HTML. Interactive elements are trivial because they're already game objects. The text layout system built for the app becomes the text layout system for the website. Everything compounds. Nothing is throwaway.
29  
30  This also serves the seven stories project — books merged with games where interactive elements live inline with narrative. Displaying a website and displaying a game are the same thing: putting pixels on the screen in the exact way you want.
... [405 more lines]

a327ex.com-blog
Anchor
anchor.blot.im
Anchor2
Anchor-lua
Anchor-YueScript
cute_action.mp3
cute_action.wav
Danpenzero
emoji-ball-battles
emoji-ball-battles-generated
interview.md
it-follows
lane-battle
meal_prep.md
music-theory
notes
Null
OMEGA_APP_PLAN.md
Orblike
private
ref1.png
ref2.png
reference
RTFX
server.md
SNKRX

arena
docs
engine
framework
reference
scripts

E:/a327ex/Anchor2/docs/:
ENGINE_API.md
ENGINE_API_QUICK.md
FRAMEWORK_API.md
FRAMEWORK_API_QUICK.md

E:/a327ex/Anchor2/engine/:
anchor.obj
build
build.bat
build-web.sh
gl.obj
include
lib
run.bat
run-web.bat
shell.html
src

E:/a327ex/Anchor2/framework/:
anchor
run.bat
run-web.bat

E:/a327ex/Anchor2/arena/:
anchor
anchor.exe
ARENA_PROGRESS.md
assets
main.lua
run.bat

E:/a327ex/Anchor2/framework/anchor/:
animation.lua
array.lua
camera.lua
class.lua
collider.lua
color.lua
font.lua
helpers.lua
image.lua
init.lua
input.lua
layer.lua
math.lua
object.lua
physics.lua
shake.lua
spring.lua
spritesheet.lua
timer.lua

1    # Engine API Quick Reference
2   
3   Function signatures for all C-to-Lua bindings. See `ENGINE_API.md` for detailed documentation with examples.
4   
5   ## Layer & Texture
6   
7   ```
8   layer_create(name) -> layer
9   layer_rectangle(layer, x, y, w, h, color)
10  layer_rectangle_line(layer, x, y, w, h, color, line_width?)
11  layer_rectangle_gradient_h(layer, x, y, w, h, color1, color2)
12  layer_rectangle_gradient_v(layer, x, y, w, h, color1, color2)
13  layer_circle(layer, x, y, radius, color)
14  layer_circle_line(layer, x, y, radius, color, line_width?)
15  layer_line(layer, x1, y1, x2, y2, width, color)
16  layer_capsule(layer, x1, y1, x2, y2, radius, color)
17  layer_capsule_line(layer, x1, y1, x2, y2, radius, color, line_width?)
18  layer_triangle(layer, x1, y1, x2, y2, x3, y3, color)
19  layer_triangle_line(layer, x1, y1, x2, y2, x3, y3, color, line_width?)
20  layer_polygon(layer, vertices, color)
21  layer_polygon_line(layer, vertices, color, line_width?)
22  layer_rounded_rectangle(layer, x, y, w, h, radius, color)
23  layer_rounded_rectangle_line(layer, x, y, w, h, radius, color, line_width?)
24  layer_push(layer, x?, y?, r?, sx?, sy?)
25  layer_pop(layer)
26  layer_draw_texture(layer, texture, x, y, color?, flash?)
27  layer_set_blend_mode(layer, mode)
28  layer_stencil_mask(layer)
29  layer_stencil_test(layer)
30  layer_stencil_test_inverse(layer)
... [321 more lines]

1    --[[
2     Anchor 2 — framework initialization.
3   
4     Loads all framework modules in dependency order, then returns a function
5     that takes config and initializes the engine + global state. The game's
6     main.lua is expected to define `update(dt)` and `draw()` as globals; the
7     C engine calls these directly each frame.
8   
9     Usage (from a game's main.lua):
10      require('anchor')({
11        width = 480,
12        height = 270,
13        title = "My Game",
14        scale = 3,
15        vsync = true,
16        filter = "rough",
17      })
18  
19      function update(dt)
20        sync_engine_globals()          -- refresh time/frame/etc. mirrors
21        -- your game update (physics is stepped by the engine automatically
22        -- before update() is called; you just consume collision events here)
23        process_destroy_queue()        -- drain deferred destruction
24      end
25  
26      function draw()
27        -- ... your game draw
28      end
29  
30    Framework modules are loaded in this order (dependency-driven):
... [134 more lines]

1    --[[
2     arena — Anchor 2 test game.
3   
4     Enemies: Orblike seeker (~9203–9514); `physics_enable_collision('enemy','enemy')`.
5   
6     Projectiles: Orblike default box 10×4 sensor (~7822), speed 190, spawn spring + flash;
7     hit FX: impact point (~12597–12603), `hit_circle` + `hit_particle` null_arrow-style (~8305–8308).
8   
9     Player contact: `hit_circle` + particles at contact (~12577–12584), spring 0.2 + flash (~7310–7319).
10  
11    Camera fixed (no follow).
12  ]]
13  
14  require('anchor')({
15    width = 480,
16    height = 270,
17    title = "Anchor 2 arena",
18    scale = 3,
19    filter = "rough",
20  })
21  
22  print('arena: framework loaded OK')
23  
24  -- Palette (cool-dark, high contrast foreground)
25  bg_color     = color(16, 16, 24)
26  fg_color     = color(235, 235, 235)
27  player_color = color(100, 150, 255)
28  enemy_color  = color(220, 80, 80)
29  bullet_color = color(255, 220, 100)
30  
... [698 more lines]

anchor.c

10482 E:/a327ex/Anchor2/engine/src/anchor.c

102:// filter_mode is defined later in the font section
346:    COMMAND_APPLY_SHADER,       // Post-process layer through a shader
828:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
829:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
855:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR);
856:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR);
915:// Global filter mode (smooth = anti-aliased, rough = hard pixel edges)
921:static int filter_mode = FILTER_ROUGH;  // Default to pixel-perfect
991:// Uses global filter_mode: FILTER_ROUGH = 1-bit mono, FILTER_SMOOTH = 8-bit grayscale AA
1044:    font->filter = filter_mode;  // Store filter mode font was loaded with
1065:    if (filter_mode == FILTER_ROUGH) {
1106:                if (filter_mode == FILTER_ROUGH) {
1155:        GLint tex_filter = (filter_mode == FILTER_ROUGH) ? GL_NEAREST : GL_LINEAR;
1172:           filter_mode == FILTER_ROUGH ? "rough" : "smooth",
1704:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
1705:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
1751:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
1752:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
4837:static int l_set_filter_mode(lua_State* L) {
4839:    if (strcmp(mode, "smooth") == 0) {
4840:        filter_mode = FILTER_SMOOTH;
4841:    } else if (strcmp(mode, "rough") == 0) {
4842:        filter_mode = FILTER_ROUGH;
4844:        return luaL_error(L, "Invalid filter mode: %s (use 'smooth' or 'rough')", mode);
4849:static int l_get_filter_mode(lua_State* L) {
4850:    lua_pushstring(L, filter_mode == FILTER_ROUGH ? "rough" : "smooth");
5510:// Optional shader parameter - if 0/nil, uses passthrough
5528:    // Use shader or passthrough
7944:    // Iterate through the table by index (array order matters)
8274:    glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
... [12 more lines]

900      int rows = tex->height / cell_height;
901     sheet->total_frames = sheet->frames_per_row * rows;
902 
903     printf("Loaded spritesheet: %s (%dx%d frames, %d total)\n",
904            path, sheet->frames_per_row, rows, sheet->total_frames);
905     return sheet;
906 }
907 
908 static void spritesheet_destroy(Spritesheet* sheet) {
909     if (!sheet) return;
910     texture_destroy(sheet->texture);
911     free(sheet);
912 }
913 
914 // Font - TTF font with baked glyph atlas
915 // Global filter mode (smooth = anti-aliased, rough = hard pixel edges)
916 // Affects shapes and fonts - must be declared before font code
917 enum {
918     FILTER_SMOOTH = 0,
919     FILTER_ROUGH,
920 };
921 static int filter_mode = FILTER_ROUGH;  // Default to pixel-perfect
922 
923 #define MAX_FONT_NAME 64
924 #define FONT_ATLAS_SIZE 512
925 #define FONT_FIRST_CHAR 32
926 #define FONT_NUM_CHARS 96
927 
928 typedef struct {
929     float x0, y0, x1, y1;  // Bounding box in pixels (relative to baseline)
... [170 more lines]

1100 
1101            // Copy glyph bitmap to atlas
1102            for (int y = 0; y < glyph_h; y++) {
1103                for (int x = 0; x < glyph_w; x++) {
1104                    unsigned char alpha;
1105    
1106                    if (filter_mode == FILTER_ROUGH) {
1107                        // Monochrome: 1-bit packed format
1108                        int byte_idx = y * bmp->pitch + (x >> 3);
1109                        int bit_idx = 7 - (x & 7);
1110                        unsigned char pixel = (bmp->buffer[byte_idx] >> bit_idx) & 1;
1111                        alpha = pixel ? 255 : 0;
1112                    } else {
1113                        // Grayscale: 8-bit per pixel
1114                        alpha = bmp->buffer[y * bmp->pitch + x];
1115                    }
1116    
1117                    int atlas_x = pen_x + x;
1118                    int atlas_y = pen_y + y;
1119                    int atlas_idx = (atlas_y * FONT_ATLAS_SIZE + atlas_x) * 4;
1120    
1121                    rgba_bitmap[atlas_idx + 0] = 255;    // R = white
1122                    rgba_bitmap[atlas_idx + 1] = 255;    // G = white
1123                    rgba_bitmap[atlas_idx + 2] = 255;    // B = white
1124                    rgba_bitmap[atlas_idx + 3] = alpha;  // A = coverage
1125                }
1126            }
1127    
1128            // Store glyph info
1129            GlyphInfo* g = &font->glyphs[i];
... [170 more lines]

9180     "}\n"
9181        "\n"
9182        "// SDF for line segment / capsule (with round caps)\n"
9183        "float sdf_capsule(vec2 p, vec2 a, vec2 b, float radius) {\n"
9184        "    vec2 pa = p - a, ba = b - a;\n"
9185        "    float h = clamp(dot(pa, ba) / dot(ba, ba), 0.0, 1.0);\n"
9186        "    return length(pa - ba * h) - radius;\n"
9187        "}\n"
9188        "\n"
9189        "// SDF for triangle\n"
9190        "float sdf_triangle(vec2 p, vec2 p0, vec2 p1, vec2 p2) {\n"
9191        "    vec2 e0 = p1 - p0, e1 = p2 - p1, e2 = p0 - p2;\n"
9192        "    vec2 v0 = p - p0, v1 = p - p1, v2 = p - p2;\n"
9193        "    vec2 pq0 = v0 - e0 * clamp(dot(v0, e0) / dot(e0, e0), 0.0, 1.0);\n"
9194        "    vec2 pq1 = v1 - e1 * clamp(dot(v1, e1) / dot(e1, e1), 0.0, 1.0);\n"
9195        "    vec2 pq2 = v2 - e2 * clamp(dot(v2, e2) / dot(e2, e2), 0.0, 1.0);\n"
9196        "    float s = sign(e0.x * e2.y - e0.y * e2.x);\n"
9197        "    vec2 d = min(min(vec2(dot(pq0, pq0), s * (v0.x * e0.y - v0.y * e0.x)),\n"
9198        "                     vec2(dot(pq1, pq1), s * (v1.x * e1.y - v1.y * e1.x))),\n"
9199        "                     vec2(dot(pq2, pq2), s * (v2.x * e2.y - v2.y * e2.x)));\n"
9200        "    return -sqrt(d.x) * sign(d.y);\n"
9201        "}\n"
9202        "\n"
9203        "// SDF for convex polygon (up to 8 vertices)\n"
9204        "float sdf_polygon(vec2 p, vec2 v[8], int n) {\n"
9205        "    float d = dot(p - v[0], p - v[0]);\n"
9206        "    float s = 1.0;\n"
9207        "    for (int i = 0, j = n - 1; i < n; j = i, i++) {\n"
9208        "        vec2 e = v[j] - v[i];\n"
9209        "        vec2 w = p - v[i];\n"
... [170 more lines]

9870 
9871            step++;
9872            game_time += PHYSICS_RATE;
9873            physics_lag -= PHYSICS_RATE;
9874    
9875            // Copy current input state to previous for next frame's edge detection
9876            input_post_update();
9877            chords_post_update();
9878        }
9879    
9880        // Render at 60Hz (for chunky pixel movement on high-refresh monitors)
9881        if (render_lag >= RENDER_RATE) {
9882            render_lag -= RENDER_RATE;
9883            frame++;
9884            draw_calls = 0;  // Reset draw call counter for this frame
9885    
9886            // Calculate FPS from dt_history average
9887            if (dt_history_filled) {
9888                double avg_dt = 0;
9889                for (int i = 0; i < DT_HISTORY_COUNT; i++) avg_dt += dt_history[i];
9890                avg_dt /= DT_HISTORY_COUNT;
9891                fps = (avg_dt > 0) ? 1.0 / avg_dt : 0;
9892            }
9893    
9894            // Set up orthographic projection (game coordinates)
9895            // Maps (0,0) at top-left to (width, height) at bottom-right
9896            float projection[16] = {
9897                2.0f / game_width, 0.0f, 0.0f, 0.0f,
9898                0.0f, -2.0f / game_height, 0.0f, 0.0f,
9899                0.0f, 0.0f, -1.0f, 0.0f,
... [90 more lines]

10280                        physics_process_events();
10281                   }
10282   
10283                   // Call Lua update(dt)
10284                   lua_getglobal(L, "update");
10285                   if (lua_isfunction(L, -1)) {
10286                       lua_pushnumber(L, PHYSICS_RATE);
10287                       if (lua_pcall(L, 1, 0, err_handler) != LUA_OK) {
10288                           snprintf(error_message, sizeof(error_message), "%s", lua_tostring(L, -1));
10289                           fprintf(stderr, "ERROR: %s\n", error_message);
10290                           lua_pop(L, 1);
10291                           error_state = true;
10292                       }
10293                   } else {
10294                       lua_pop(L, 1);
10295                   }
10296   
10297                   step++;
10298                   game_time += PHYSICS_RATE;
10299                   input_post_update();
10300               }
10301   
10302               if (!running || error_state) break;
10303   
10304               // Increment frame before draw so an.frame is correct
10305               frame++;
10306               draw_calls = 0;
10307   
10308               // Set up orthographic projection
10309               float projection[16] = {
... [50 more lines]

1690         return NULL;
1691        }
1692        layer->command_count = 0;
1693        layer->command_capacity = MAX_COMMAND_CAPACITY;
1694        layer->current_blend = BLEND_ALPHA;
1695    
1696        // Create FBO
1697        glGenFramebuffers(1, &layer->fbo);
1698        glBindFramebuffer(GL_FRAMEBUFFER, layer->fbo);
1699    
1700        // Create color texture
1701        glGenTextures(1, &layer->color_texture);
1702        glBindTexture(GL_TEXTURE_2D, layer->color_texture);
1703        glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, width, height, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
1704        glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
1705        glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
1706        glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_CLAMP_TO_EDGE);
1707        glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_CLAMP_TO_EDGE);
1708    
1709        // Attach color texture to FBO
1710        glFramebufferTexture2D(GL_FRAMEBUFFER, GL_COLOR_ATTACHMENT0, GL_TEXTURE_2D, layer->color_texture, 0);
1711    
1712        // Create stencil renderbuffer (using depth-stencil for wider compatibility)
1713        glGenRenderbuffers(1, &layer->stencil_rbo);
1714        glBindRenderbuffer(GL_RENDERBUFFER, layer->stencil_rbo);
1715        glRenderbufferStorage(GL_RENDERBUFFER, GL_DEPTH24_STENCIL8, width, height);
1716        glFramebufferRenderbuffer(GL_FRAMEBUFFER, GL_DEPTH_STENCIL_ATTACHMENT, GL_RENDERBUFFER, layer->stencil_rbo);
1717    
1718        if (glCheckFramebufferStatus(GL_FRAMEBUFFER) != GL_FRAMEBUFFER_COMPLETE) {
1719            fprintf(stderr, "Layer FBO not complete\n");
... [50 more lines]

810      if (!tex) {
811         stbi_image_free(data);
812         return NULL;
813     }
814 
815     tex->width = width;
816     tex->height = height;
817 
818     if (headless_mode) {
819         // Headless: keep dimensions but skip GL texture upload
820         tex->id = 0;
821         stbi_image_free(data);
822         return tex;
823     }
824 
825     glGenTextures(1, &tex->id);
826     glBindTexture(GL_TEXTURE_2D, tex->id);
827     glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, width, height, 0, GL_RGBA, GL_UNSIGNED_BYTE, data);
828     glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
829     glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
830     glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_CLAMP_TO_EDGE);
831     glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_CLAMP_TO_EDGE);
832     glBindTexture(GL_TEXTURE_2D, 0);
833 
834     stbi_image_free(data);
835     printf("Loaded texture: %s (%dx%d)\n", path, width, height);
836     return tex;
837 }
838 
839 // Create a texture from raw RGBA pixel data (4 bytes per pixel)
... [50 more lines]

79:static int game_width = 480;
80:static int game_height = 270;
2737:    float scale_x = (float)window_w / game_width;
2738:    float scale_y = (float)window_h / game_height;
2743:    int scaled_w = (int)(game_width * scale);
2744:    int scaled_h = (int)(game_height * scale);
2756:    return (gx >= 0 && gx < game_width && gy >= 0 && gy < game_height);
4565:    Layer* layer = layer_create(game_width, game_height);
7814:    float scale_x = (float)window_w / game_width;
7815:    float scale_y = (float)window_h / game_height;
8130:    lua_pushinteger(L, game_width);
8135:    lua_pushinteger(L, game_height);
8150:    float scale_x = (float)window_w / game_width;
8151:    float scale_y = (float)window_h / game_height;
8198:    game_width = luaL_checkinteger(L, 1);
8199:    game_height = luaL_checkinteger(L, 2);
8214:static int l_engine_set_scale(lua_State* L) {
8216:        return luaL_error(L, "engine_set_scale must be called before engine_init");
8273:    glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, game_width, game_height, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
8288:    capture_buffer = (unsigned char*)malloc(game_width * game_height * 4);
8293:    printf("Render capture setup: %dx%d -> %s\n", game_width, game_height, capture_output_dir);
8304:    glViewport(0, 0, game_width, game_height);
8318:            float ndc_x = (cmd->x / game_width) * 2.0f;
8319:            float ndc_y = -(cmd->y / game_height) * 2.0f;
8346:    glReadPixels(0, 0, game_width, game_height, GL_RGBA, GL_UNSIGNED_BYTE, capture_buffer);
8350:    int row_bytes = game_width * 4;
8352:    for (int y = 0; y < game_height / 2; y++) {
8354:        unsigned char* bot = capture_buffer + (game_height - 1 - y) * row_bytes;
8364:    stbi_write_png(filename, game_width, game_height, 4, capture_buffer, game_width * 4);
8380:        glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, game_width, game_height, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
... [38 more lines]

8190 // ============================================================================
8191    
8192    static bool engine_initialized = false;
8193    
8194    static int l_engine_set_game_size(lua_State* L) {
8195        if (engine_initialized) {
8196            return luaL_error(L, "engine_set_game_size must be called before engine_init");
8197        }
8198        game_width = luaL_checkinteger(L, 1);
8199        game_height = luaL_checkinteger(L, 2);
8200        return 0;
8201    }
8202    
8203    static int l_engine_set_title(lua_State* L) {
8204        const char* title = luaL_checkstring(L, 1);
8205        strncpy(window_title, title, sizeof(window_title) - 1);
8206        window_title[sizeof(window_title) - 1] = '\0';
8207        // If window already exists, update title immediately
8208        if (window) {
8209            SDL_SetWindowTitle(window, window_title);
8210        }
8211        return 0;
8212    }
8213    
8214    static int l_engine_set_scale(lua_State* L) {
8215        if (engine_initialized) {
8216            return luaL_error(L, "engine_set_scale must be called before engine_init");
8217        }
8218        initial_scale = (float)luaL_checknumber(L, 1);
8219        return 0;
... [20 more lines]

10099:        SDL_GL_SetAttribute(SDL_GL_CONTEXT_MAJOR_VERSION, 3);
10100:        SDL_GL_SetAttribute(SDL_GL_CONTEXT_MINOR_VERSION, 0);
10101:        SDL_GL_SetAttribute(SDL_GL_CONTEXT_PROFILE_MASK, SDL_GL_CONTEXT_PROFILE_ES);
10104:        SDL_GL_SetAttribute(SDL_GL_CONTEXT_MAJOR_VERSION, 3);
10105:        SDL_GL_SetAttribute(SDL_GL_CONTEXT_MINOR_VERSION, 3);
10106:        SDL_GL_SetAttribute(SDL_GL_CONTEXT_PROFILE_MASK, SDL_GL_CONTEXT_PROFILE_CORE);
10108:        SDL_GL_SetAttribute(SDL_GL_DOUBLEBUFFER, 1);
10109:        SDL_GL_SetAttribute(SDL_GL_DEPTH_SIZE, 0);

338:    COMMAND_GLYPH,              // Font glyph with custom UVs (uses flash_color for packed UVs)
914:// Font - TTF font with baked glyph atlas
932:} GlyphInfo;
943:    GlyphInfo glyphs[FONT_NUM_CHARS];  // ASCII 32-127
1070:    // Pack glyphs into atlas
1076:        FT_UInt glyph_index = FT_Get_Char_Index(face, FONT_FIRST_CHAR + i);
1078:        if (FT_Load_Glyph(face, glyph_index, load_flags)) {
1079:            continue;  // Skip failed glyphs
1082:        FT_GlyphSlot slot = face->glyph;
1085:        int glyph_w = bmp->width;
1086:        int glyph_h = bmp->rows;
1089:        if (pen_x + glyph_w + 1 >= FONT_ATLAS_SIZE) {
1096:        if (pen_y + glyph_h + 1 >= FONT_ATLAS_SIZE) {
1097:            fprintf(stderr, "Warning: Font atlas full, some glyphs skipped\n");
1101:        // Copy glyph bitmap to atlas
1102:        for (int y = 0; y < glyph_h; y++) {
1103:            for (int x = 0; x < glyph_w; x++) {
1128:        // Store glyph info
1129:        GlyphInfo* g = &font->glyphs[i];
1132:        g->x1 = g->x0 + glyph_w;
1133:        g->y1 = g->y0 + glyph_h;
1136:        g->u1 = (float)(pen_x + glyph_w) / FONT_ATLAS_SIZE;
1137:        g->v1 = (float)(pen_y + glyph_h) / FONT_ATLAS_SIZE;
1141:        pen_x += glyph_w + 1;
1142:        if (glyph_h > row_height) row_height = glyph_h;
1149:        // Headless: glyph metrics are loaded, skip GL atlas upload
1219:            width += font->glyphs[codepoint - FONT_FIRST_CHAR].advance;
1229:        return font->glyphs[codepoint - FONT_FIRST_CHAR].advance;
1971:// Record a glyph command (top-left positioned, with custom UVs from font atlas)
1972:// x, y is top-left corner of glyph; w, h is glyph size; UVs are atlas coordinates
... [36 more lines]

4234 // Process a glyph command (font atlas with custom UVs)
4235    // Glyph is positioned at top-left (x, y)
4236    static void process_glyph(const DrawCommand* cmd) {
4237        float x = cmd->params[0];
4238        float y = cmd->params[1];
4239        float w = cmd->params[2];
4240        float h = cmd->params[3];
4241    
4242        // Flush batch if texture changes
4243        if (current_batch_texture != cmd->texture_id && batch_vertex_count > 0) {
4244            batch_flush();
4245        }
4246        current_batch_texture = cmd->texture_id;
4247    
4248        // Glyph is positioned at top-left (x, y)
4249        float lx0 = x,     ly0 = y;
4250        float lx1 = x + w, ly1 = y;
4251        float lx2 = x + w, ly2 = y + h;
4252        float lx3 = x,     ly3 = y + h;
4253    
4254        // Transform to world coordinates
4255        float wx0, wy0, wx1, wy1, wx2, wy2, wx3, wy3;
4256        transform_point(cmd->transform, lx0, ly0, &wx0, &wy0);
4257        transform_point(cmd->transform, lx1, ly1, &wx1, &wy1);
4258        transform_point(cmd->transform, lx2, ly2, &wx2, &wy2);
4259        transform_point(cmd->transform, lx3, ly3, &wx3, &wy3);
4260    
4261        // Unpack color (used for tinting)
4262        float r, g, b, a;
4263        unpack_color(cmd->color, &r, &g, &b, &a);
... [25 more lines]

3722:static void batch_flush(void) {
4196:        batch_flush();
4244:        batch_flush();
4285:        batch_flush();
4348:static void layer_render(Layer* layer) {
4365:            batch_flush();
4392:            glUseProgram(shader_program);
4399:            batch_flush();
4413:            glUseProgram(shader_program);
4421:            batch_flush();
4433:                    batch_flush();
4441:                    batch_flush();
4449:                    batch_flush();
4457:                    batch_flush();
4465:                    batch_flush();
4473:                    batch_flush();
4481:                    batch_flush();
4489:                    batch_flush();
4505:                batch_flush();
4514:                batch_flush();
4522:                batch_flush();
4530:                batch_flush();
4539:            batch_flush();
4544:    batch_flush();
5479:static int l_layer_render(lua_State* L) {
5497:    layer_render(layer);
5549:    glUseProgram(shader_program);
8879:    lua_register(L, "layer_render", l_layer_render);
9903:        glUseProgram(shader_program);
10315:            glUseProgram(shader_program);

4348 static void layer_render(Layer* layer) {
4349        batch_vertex_count = 0;
4350        current_batch_texture = 0;
4351        uint8_t current_blend = BLEND_ALPHA;  // Start with default
4352        apply_blend_mode(current_blend);
4353    
4354        for (int i = 0; i < layer->command_count; i++) {
4355            const DrawCommand* cmd = &layer->commands[i];
4356    
4357            // Handle uniform setting commands
4358            // These need to temporarily switch programs, so flush batch first and restore after
4359            if (cmd->type == COMMAND_SET_UNIFORM_FLOAT ||
4360                cmd->type == COMMAND_SET_UNIFORM_VEC2 ||
4361                cmd->type == COMMAND_SET_UNIFORM_VEC4 ||
4362                cmd->type == COMMAND_SET_UNIFORM_INT ||
4363                cmd->type == COMMAND_SET_UNIFORM_TEXTURE) {
4364                // Flush any pending draws before switching programs
4365                batch_flush();
4366                current_batch_texture = 0;
4367    
4368                glUseProgram(cmd->shader_id);
4369                switch (cmd->type) {
4370                    case COMMAND_SET_UNIFORM_FLOAT:
4371                        glUniform1f((GLint)cmd->uniform_location, cmd->params[0]);
4372                        break;
4373                    case COMMAND_SET_UNIFORM_VEC2:
4374                        glUniform2f((GLint)cmd->uniform_location, cmd->params[0], cmd->params[1]);
4375                        break;
4376                    case COMMAND_SET_UNIFORM_VEC4:
4377                        glUniform4f((GLint)cmd->uniform_location, cmd->params[0], cmd->params[1], cmd->params[2], cmd->params[3]);
... [190 more lines]

5479 static int l_layer_render(lua_State* L) {
5480        if (headless_mode) return 0;
5481        Layer* layer = (Layer*)lua_touserdata(L, 1);
5482    
5483        // Bind layer's FBO
5484        glBindFramebuffer(GL_FRAMEBUFFER, layer->fbo);
5485        glViewport(0, 0, layer->width, layer->height);
5486    
5487        // Clear color and stencil buffers
5488        glClearColor(0.0f, 0.0f, 0.0f, 0.0f);
5489        glClearStencil(0);
5490        glClear(GL_COLOR_BUFFER_BIT | GL_STENCIL_BUFFER_BIT);
5491    
5492        // Ensure stencil starts disabled
5493        glDisable(GL_STENCIL_TEST);
5494        glColorMask(GL_TRUE, GL_TRUE, GL_TRUE, GL_TRUE);
5495    
5496        // Process all queued commands
5497        layer_render(layer);
5498    
5499        // Ensure stencil is disabled after rendering (in case commands left it enabled)
5500        glDisable(GL_STENCIL_TEST);
5501        glColorMask(GL_TRUE, GL_TRUE, GL_TRUE, GL_TRUE);
5502    
5503        // Clear command queue for next frame
5504        layer->command_count = 0;
5505    
5506        return 0;
5507    }
5508    
... [50 more lines]

443:} Layer;
1663:static Layer* layer_create(int width, int height) {
4565:    Layer* layer = layer_create(game_width, game_height);
4594:static int l_layer_create(lua_State* L) {
8792:    lua_register(L, "layer_create", l_layer_create);

410  #endif
411 
412 // Layer
413 typedef struct {
414     GLuint fbo;
415     GLuint color_texture;
416     GLuint stencil_rbo;     // Stencil renderbuffer for masking
417     int width;
418     int height;
419 
420     // Effect ping-pong buffers (created on first use)
421     GLuint effect_fbo;
422     GLuint effect_texture;
423     bool textures_swapped;  // Which buffer is current result
424 
425     // Extra texture bindings for shaders (bound right before apply_shader draws)
426     GLuint extra_texture;     // texture to bind to unit 1
427     GLint extra_texture_loc;  // uniform location for the sampler
428     bool has_extra_texture;
429 
430     // Transform stack (mat3 stored as 9 floats: row-major)
431     // Each mat3: [m00 m01 m02 m10 m11 m12 m20 m21 m22]
432     // Represents 2D affine transform (2x3 used, bottom row is 0,0,1)
433     float transform_stack[MAX_TRANSFORM_DEPTH * 9];
434     int transform_depth;
435 
436     // Command queue (deferred rendering)
437     DrawCommand* commands;
438     int command_count;
439     int command_capacity;
... [20 more lines]

1663 static Layer* layer_create(int width, int height) {
1664        Layer* layer = (Layer*)calloc(1, sizeof(Layer));
1665        if (!layer) return NULL;
1666    
1667        layer->width = width;
1668        layer->height = height;
1669    
1670        // Initialize transform stack with identity matrix at depth 0
1671        layer->transform_depth = 0;
1672        float* m = layer->transform_stack;
1673        m[0] = 1.0f; m[1] = 0.0f; m[2] = 0.0f;  // row 0
1674        m[3] = 0.0f; m[4] = 1.0f; m[5] = 0.0f;  // row 1
1675        m[6] = 0.0f; m[7] = 0.0f; m[8] = 1.0f;  // row 2
1676    
1677        if (headless_mode) {
1678            // Headless: no command buffer, no FBO — all draw calls become no-ops
1679            layer->commands = NULL;
1680            layer->command_count = 0;
1681            layer->command_capacity = 0;
1682            layer->current_blend = BLEND_ALPHA;
1683            return layer;
1684        }
1685    
1686        // Initialize command queue (fixed size, never grows)
1687        layer->commands = (DrawCommand*)malloc(MAX_COMMAND_CAPACITY * sizeof(DrawCommand));
1688        if (!layer->commands) {
1689            free(layer);
1690            return NULL;
1691        }
1692        layer->command_count = 0;
... [50 more lines]

4550 // Find or create a named layer
4551    static Layer* layer_get_or_create(const char* name) {
4552        // Check if layer already exists
4553        for (int i = 0; i < layer_count; i++) {
4554            if (strcmp(layer_names[i], name) == 0) {
4555                return layer_registry[i];
4556            }
4557        }
4558    
4559        // Create new layer
4560        if (layer_count >= MAX_LAYERS) {
4561            fprintf(stderr, "Error: Maximum number of layers (%d) reached\n", MAX_LAYERS);
4562            return NULL;
4563        }
4564    
4565        Layer* layer = layer_create(game_width, game_height);
4566        if (!layer) {
4567            fprintf(stderr, "Error: Failed to create layer '%s'\n", name);
4568            return NULL;
4569        }
4570    
4571        // Store in registry
4572        layer_registry[layer_count] = layer;
4573        layer_names[layer_count] = strdup(name);
4574        layer_count++;
4575    
4576        printf("Created layer: %s\n", name);
4577        return layer;
4578    }
4579    
... [30 more lines]

421:    GLuint effect_fbo;
422:    GLuint effect_texture;
1738:    if (layer->effect_texture) glDeleteTextures(1, &layer->effect_texture);
1739:    if (layer->effect_fbo) glDeleteFramebuffers(1, &layer->effect_fbo);
1745:    if (layer->effect_fbo != 0) return;  // Already created
1748:    glGenTextures(1, &layer->effect_texture);
1749:    glBindTexture(GL_TEXTURE_2D, layer->effect_texture);
1757:    glGenFramebuffers(1, &layer->effect_fbo);
1758:    glBindFramebuffer(GL_FRAMEBUFFER, layer->effect_fbo);
1759:    glFramebufferTexture2D(GL_FRAMEBUFFER, GL_COLOR_ATTACHMENT0, GL_TEXTURE_2D, layer->effect_texture, 0);
1772:    return layer->textures_swapped ? layer->effect_texture : layer->color_texture;
3657:static void execute_apply_shader(Layer* layer, GLuint shader) {
3664:        src_tex = layer->effect_texture;
3668:        dst_fbo = layer->effect_fbo;
4383:                    // Store for binding during execute_apply_shader
4403:            execute_apply_shader(layer, cmd->shader_id);
4406:            // (execute_apply_shader toggled textures_swapped, so current is now the destination)
4407:            GLuint current_fbo = layer->textures_swapped ? layer->effect_fbo : layer->fbo;
5467:    GLuint target_fbo = layer->textures_swapped ? layer->effect_fbo : layer->fbo;
5518:    GLuint target_fbo = dst->textures_swapped ? dst->effect_fbo : dst->fbo;

1    --[[
2     Layer module — procedural API over the engine layer handle.
3   
4     Layers are FBOs that accumulate draw commands during the frame. Commands are
5     deferred and processed via layer_render() with GL batching. Composite to the
6     screen with layer_draw().
7   
8     Usage:
9       game_layer = layer_new('game')
10      layer_rectangle(game_layer, 100, 100, 50, 30, color)
11      layer_render(game_layer)
12      layer_draw(game_layer)
13  
14    State table shape (from layer_new): { name, handle, parallax_x, parallax_y }
15    All layer_* functions below take that table as the first argument `lyr`.
16  
17    ---------------------------------------------------------------------------
18    ENGINE NAME CONFLICTS (Lua globals registered by anchor.c)
19  
20    The C engine binds the same symbol names to raw engine implementations whose
21    first argument is a C layer pointer (lightuserdata), e.g. layer_rectangle(ptr, ...).
22  
23    This file captures those implementations in `eng` at load time, then REPLACES
24    the globals with wrappers whose first argument is a layer state table from
25    layer_new() (field .handle holds the pointer). Wrappers also accept a raw
26    handle for occasional interop.
27  
28    After require('anchor.layer'), direct engine-style calls like
29    layer_rectangle(userdata_ptr, x, y, w, h, c) no longer use the C binding
30    unless you passed a lightuserdata: the wrapper treats a non-table first arg
... [241 more lines]

E:/a327ex/Anchor/framework/assets/LanaPixel.ttf
E:/a327ex/Anchor/reference/love-compare/anchor/assets/LanaPixel.ttf
E:/a327ex/Anchor/reference/love-compare/assets/FatPixelFont.ttf
E:/a327ex/Anchor/reference/love-compare/assets/LanaPixel.ttf
E:/a327ex/Anchor/reference/love-compare/assets/m6x11plus.ttf
E:/a327ex/Anchor/reference/love-compare/assets/Mx437_DOS-V_re_JPN12.ttf
E:/a327ex/Anchor/reference/love-compare/assets/sd_auto_pilot.ttf
E:/a327ex/Anchor/reference/super emoji box/assets/diest64.ttf
E:/a327ex/Anchor/reference/super emoji box/assets/FatPixelFont.ttf
E:/a327ex/Anchor/reference/super emoji box/assets/fusion-pixel-10px-monospaced-latin.ttf
E:/a327ex/Anchor/reference/super emoji box/assets/fusion-pixel-12px-monospaced-latin.ttf
E:/a327ex/Anchor/reference/super emoji box/assets/fusion-pixel-8px-monospaced-latin.ttf
E:/a327ex/Anchor/reference/super emoji box/assets/LanaPixel.ttf
E:/a327ex/Anchor/reference/super emoji box/assets/m6x11plus.ttf
E:/a327ex/Anchor/reference/super emoji box/lun/assets/Quicksand-Regular.ttf
E:/a327ex/Anchor-lua/framework/assets/LanaPixel.ttf
E:/a327ex/Anchor-lua/reference/love-compare/anchor/assets/LanaPixel.ttf
E:/a327ex/Anchor-lua/reference/love-compare/assets/FatPixelFont.ttf
E:/a327ex/Anchor-lua/reference/love-compare/assets/LanaPixel.ttf
E:/a327ex/Anchor-lua/reference/love-compare/assets/m6x11plus.ttf
E:/a327ex/Anchor-lua/reference/love-compare/assets/Mx437_DOS-V_re_JPN12.ttf
E:/a327ex/Anchor-lua/reference/love-compare/assets/sd_auto_pilot.ttf
E:/a327ex/Anchor-lua/reference/super emoji box/assets/diest64.ttf
E:/a327ex/Anchor-lua/reference/super emoji box/assets/FatPixelFont.ttf
E:/a327ex/Anchor-lua/reference/super emoji box/assets/fusion-pixel-10px-monospaced-latin.ttf
E:/a327ex/Anchor-lua/reference/super emoji box/assets/fusion-pixel-12px-monospaced-latin.ttf
E:/a327ex/Anchor-lua/reference/super emoji box/assets/fusion-pixel-8px-monospaced-latin.ttf
E:/a327ex/Anchor-lua/reference/super emoji box/assets/LanaPixel.ttf
E:/a327ex/Anchor-lua/reference/super emoji box/assets/m6x11plus.ttf
E:/a327ex/Anchor-lua/reference/super emoji box/lun/assets/Quicksand-Regular.ttf
... [20 more lines]

1    --[[
2     font — thin wrapper over C font functions.
3   
4     Usage:
5       fonts.main = font_register('main', 'assets/LanaPixel.ttf', 11)
6       layer_text(game_layer, "Hello", fonts.main, 100, 50, color)
7   
8     A font is a plain table with .name, .size, .height plus query methods.
9     Stays as a simple class/struct pattern for consistent access.
10  ]]
11  
12  font = class()
13  
14  function font:new(name, path, size)
15    self.name = name
16    self.size = size
17    font_load(name, path, size)
18    self.height = font_get_height(name)
19  end
20  
21  function font:text_width(text)
22    return font_get_text_width(self.name, text)
23  end
24  
25  function font:char_width(codepoint)
26    return font_get_char_width(self.name, codepoint)
27  end
28  
29  function font:glyph_metrics(codepoint)
30    return font_get_glyph_metrics(self.name, codepoint)
... [9 more lines]

3657 static void execute_apply_shader(Layer* layer, GLuint shader) {
3658        // Ensure effect buffer exists
3659        layer_ensure_effect_buffer(layer);
3660    
3661        // Determine source and destination based on current state
3662        GLuint src_tex, dst_fbo;
3663        if (layer->textures_swapped) {
3664            src_tex = layer->effect_texture;
3665            dst_fbo = layer->fbo;
3666        } else {
3667            src_tex = layer->color_texture;
3668            dst_fbo = layer->effect_fbo;
3669        }
3670    
3671        // Bind destination FBO
3672        glBindFramebuffer(GL_FRAMEBUFFER, dst_fbo);
3673        glViewport(0, 0, layer->width, layer->height);
3674    
3675        // Clear destination
3676        glClearColor(0.0f, 0.0f, 0.0f, 0.0f);
3677        glClear(GL_COLOR_BUFFER_BIT);
3678    
3679        // Disable blending (replace, don't blend)
3680        glDisable(GL_BLEND);
3681    
3682        // Use the effect shader
3683        glUseProgram(shader);
3684    
3685        // Set standard uniforms
3686        GLint tex_loc = glGetUniformLocation(shader, "u_texture");
... [40 more lines]

992:static Font* font_load(const char* name, const char* path, float size) {
5010:static int l_font_load(lua_State* L) {
5014:    Font* font = font_load(name, path, size);
8828:    lua_register(L, "font_load", l_font_load);

5005                                 u0, v0, u1, v1, color, flash);
5006        return 0;
5007    }
5008    
5009    // Font Lua bindings
5010    static int l_font_load(lua_State* L) {
5011        const char* name = luaL_checkstring(L, 1);
5012        const char* path = luaL_checkstring(L, 2);
5013        float size = (float)luaL_checknumber(L, 3);
5014        Font* font = font_load(name, path, size);
5015        if (!font) {
5016            return luaL_error(L, "Failed to load font: %s", path);
5017        }
5018        return 0;
5019    }
5020    
5021    static int l_font_unload(lua_State* L) {
5022        const char* name = luaL_checkstring(L, 1);
5023        font_unload(name);
5024        return 0;
5025    }
5026    
5027    static int l_font_get_height(lua_State* L) {
5028        const char* name = luaL_checkstring(L, 1);
5029        float height = font_get_height(name);
5030        lua_pushnumber(L, height);
5031        return 1;
5032    }
5033    
5034    static int l_font_get_text_width(lua_State* L) {

1    @echo off
2   setlocal
3   
4   cd /d "%~dp0"
5   
6   :: Find and run vcvarsall.bat for Visual Studio
7   if exist "C:\Program Files\Microsoft Visual Studio\18\Community\VC\Auxiliary\Build\vcvarsall.bat" (
8       call "C:\Program Files\Microsoft Visual Studio\18\Community\VC\Auxiliary\Build\vcvarsall.bat" x64 >nul 2>&1
9   ) else if exist "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvarsall.bat" (
10      call "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvarsall.bat" x64 >nul 2>&1
11  ) else if exist "C:\Program Files\Microsoft Visual Studio\2022\Professional\VC\Auxiliary\Build\vcvarsall.bat" (
12      call "C:\Program Files\Microsoft Visual Studio\2022\Professional\VC\Auxiliary\Build\vcvarsall.bat" x64 >nul 2>&1
13  ) else if exist "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" (
14      call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64 >nul 2>&1
15  ) else (
16      echo ERROR: Could not find Visual Studio
17      exit /b 1
18  )
19  
20  if not exist build mkdir build
21  
22  :: Build Lua library if it doesn't exist
23  if not exist lib\lua.lib (
24      echo Building Lua library...
25      if not exist build\lua_obj mkdir build\lua_obj
26      cl.exe /nologo /O2 /W3 /c /I"include/lua" ^
27          include/lua/lapi.c include/lua/lauxlib.c include/lua/lbaselib.c ^
28          include/lua/lcode.c include/lua/lcorolib.c include/lua/lctype.c ^
29          include/lua/ldblib.c include/lua/ldebug.c include/lua/ldo.c ^
30          include/lua/ldump.c include/lua/lfunc.c include/lua/lgc.c ^
... [76 more lines]

1    @echo off
2   REM Run arena test game. CWD must be repo root; first arg is the game folder name.
3   
4   cd /d "%~dp0.."
5   "%~dp0anchor.exe" arena
6   

8260 }
8261    
8262    static int l_engine_render_setup(lua_State* L) {
8263        const char* dir = luaL_checkstring(L, 1);
8264        strncpy(capture_output_dir, dir, sizeof(capture_output_dir) - 1);
8265        capture_output_dir[sizeof(capture_output_dir) - 1] = '\0';
8266        capture_frame_number = 0;
8267    
8268        // Create capture FBO at native game resolution
8269        glGenFramebuffers(1, &capture_fbo);
8270        glGenTextures(1, &capture_texture);
8271    
8272        glBindTexture(GL_TEXTURE_2D, capture_texture);
8273        glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, game_width, game_height, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
8274        glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
8275        glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
8276    
8277        glBindFramebuffer(GL_FRAMEBUFFER, capture_fbo);
8278        glFramebufferTexture2D(GL_FRAMEBUFFER, GL_COLOR_ATTACHMENT0, GL_TEXTURE_2D, capture_texture, 0);
8279    
8280        GLenum status = glCheckFramebufferStatus(GL_FRAMEBUFFER);
8281        if (status != GL_FRAMEBUFFER_COMPLETE) {
8282            glBindFramebuffer(GL_FRAMEBUFFER, 0);
8283            return luaL_error(L, "Capture FBO incomplete: 0x%x", status);
8284        }
8285        glBindFramebuffer(GL_FRAMEBUFFER, 0);
8286    
8287        // Allocate pixel read buffer
8288        capture_buffer = (unsigned char*)malloc(game_width * game_height * 4);
8289        if (!capture_buffer) {
... [5 more lines]

3722 static void batch_flush(void) {
3723        if (batch_vertex_count == 0) return;
3724    
3725        // Bind texture if we have one (for sprites)
3726        if (current_batch_texture != 0) {
3727            glActiveTexture(GL_TEXTURE0);
3728            glBindTexture(GL_TEXTURE_2D, current_batch_texture);
3729        }
3730    
3731        glBindVertexArray(vao);
3732        glBindBuffer(GL_ARRAY_BUFFER, vbo);
3733        glBufferSubData(GL_ARRAY_BUFFER, 0,
3734                        batch_vertex_count * VERTEX_FLOATS * sizeof(float),
3735                        batch_vertices);
3736        glDrawArrays(GL_TRIANGLES, 0, batch_vertex_count);
3737        glBindVertexArray(0);
3738    
3739        batch_vertex_count = 0;
3740        draw_calls++;
3741    }
3742    
3743    // Process a rectangle command (SDF-based, UV-space approach)
3744    // The SDF is computed in local quad space using UV coordinates.
3745    // This handles rotation correctly because UV interpolation implicitly
3746    // provides the inverse rotation.
3747    static void process_rectangle(const DrawCommand* cmd) {
3748        float x = cmd->params[0];
3749        float y = cmd->params[1];
3750        float w = cmd->params[2];
3751        float h = cmd->params[3];
... [20 more lines]

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\engine\src\anchor.c has been updated successfully. (file state is current in your context — no need to Read it back)

1665:static Layer* layer_create(int width, int height, int layer_filter) {
4568:static Layer* layer_get_or_create(const char* name, int layer_filter) {
4582:    Layer* layer = layer_create(game_width, game_height, layer_filter);
4612:// layer_create(name [, filter]) — filter is 'smooth' or 'rough'; defaults to global filter_mode.
4613:static int l_layer_create(lua_State* L) {
4628:    Layer* layer = layer_get_or_create(name, layer_filter);

994:static Font* font_load(const char* name, const char* path, float size, int font_filter) {
5042:// font_load(name, path, size [, filter]) — filter is 'smooth' or 'rough'; defaults to global filter_mode.
5043:static int l_font_load(lua_State* L) {
5060:    Font* font = font_load(name, path, size, font_filter);

Microsoft Windows [Version 10.0.26200.8246]
(c) Microsoft Corporation. All rights reserved.

E:\a327ex\Anchor2\engine>

anchor.c
include/stb\stb_image_write.h(776): warning C4996: 'sprintf': This function or variable may be unsafe. Consider using sprintf_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(249): warning C4996: 'strcpy': This function or variable may be unsafe. Consider using strcpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(1044): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(1250): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(2463): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(2457): warning C4267: 'initializing': conversion from 'size_t' to 'int', possible loss of data
src/anchor.c(2854): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(3132): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(3138): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(3248): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(3257): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(3351): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(3353): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(4590): warning C4996: 'strdup': The POSIX name for this item is deprecated. Instead, use the ISO C and C++ conformant name: _strdup. See online help for details.
src/anchor.c(5666): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(6551): warning C4244: 'initializing': conversion from 'lua_Number' to 'float', possible loss of data
src/anchor.c(6552): warning C4244: 'initializing': conversion from 'lua_Number' to 'float', possible loss of data
src/anchor.c(8244): warning C4244: '=': conversion from 'lua_Integer' to 'int', possible loss of data
src/anchor.c(8245): warning C4244: '=': conversion from 'lua_Integer' to 'int', possible loss of data
src/anchor.c(8251): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(8310): warning C4996: 'strncpy': This function or variable may be unsafe. Consider using strncpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(9564): warning C4996: 'strcpy': This function or variable may be unsafe. Consider using strcpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(9568): warning C4996: 'strcat': This function or variable may be unsafe. Consider using strcat_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(9573): warning C4996: 'strcpy': This function or variable may be unsafe. Consider using strcpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(9577): warning C4996: 'strcat': This function or variable may be unsafe. Consider using strcat_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(9583): warning C4996: 'strcpy': This function or variable may be unsafe. Consider using strcpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(9587): warning C4996: 'strcat': This function or variable may be unsafe. Consider using strcat_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(9593): warning C4996: 'strcpy': This function or variable may be unsafe. Consider using strcpy_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
src/anchor.c(9597): warning C4996: 'strcat': This function or variable may be unsafe. Consider using strcat_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
... [8 more lines]

The file E:\a327ex\Anchor2\framework\anchor\layer.lua has been updated successfully. (file state is current in your context — no need to Read it back)

The file E:\a327ex\Anchor2\framework\anchor\font.lua has been updated successfully. (file state is current in your context — no need to Read it back)

E:/a327ex/Anchor2/app/:
anchor
anchor.exe
assets

E:/a327ex/Anchor2/app/anchor/:
animation.lua
array.lua
camera.lua
class.lua
collider.lua
color.lua
font.lua
helpers.lua
image.lua
init.lua
input.lua
layer.lua
math.lua
object.lua
physics.lua
shake.lua
spring.lua
spritesheet.lua
timer.lua

E:/a327ex/Anchor2/app/assets/:
LanaPixel.ttf
Quicksand-Regular.ttf
RobotoMono-Regular.ttf

File created successfully at: E:\a327ex\Anchor2\app\run.bat (file state is current in your context — no need to Read it back)

1    --[[
2     color — mutable RGBA color with HSL conversion helpers.
3   
4     Simpler than v1's color class. A color is a plain table {r, g, b, a} with
5     a __call metamethod that returns the packed rgba integer used by drawing
6     functions. No auto-sync between RGB and HSL — HSL is a *conversion*, not a
7     storage format. If you want to modify hue, convert to HSL, modify, convert
8     back.
9   
10    Usage:
11      red = color_new(255, 0, 0)
12      red.a = 128              -- set alpha
13      layer_circle(game_layer, x, y, r, red())  -- __call returns packed rgba integer
14  
15      -- HSL manipulation:
16      h, s, l = color_to_hsl(red)
17      h = (h + 120) % 360      -- shift hue
18      shifted = color_from_hsl(h, s, l, red.a)
19  
20      -- Common operations:
21      copy = color_clone(red)
22      mixed = color_mix(red, blue, 0.5)
23      dark = color_darken(red, 0.5)      -- multiply RGB by 0.5
24      light = color_lighten(red, 1.5)    -- multiply RGB by 1.5 (clamped)
25      inverted = color_invert(red)
26  
27    Design notes:
28      - Colors are plain tables. Modify fields directly: c.r = 100.
29      - Procedural functions (color_mix, color_clone, etc.) return NEW colors,
30        not mutating the input. If you want to mutate, do `c.r = ...` directly.
... [50 more lines]

File created successfully at: E:\a327ex\Anchor2\app\main.lua (file state is current in your context — no need to Read it back)

80   
81  color_mt.__call = function(c)
82    return rgba(
83      math.floor(c.r + 0.5),
84      math.floor(c.g + 0.5),
85      math.floor(c.b + 0.5),
86      math.floor(c.a + 0.5)
87    )
88  end
89  
90  --[[
91    color_new(r, g, b, a)
92    Create a new color. Defaults to white (255, 255, 255, 255).
93  ]]
94  function color_new(r, g, b, a)
95    return setmetatable({
96      r = r or 255,
97      g = g or 255,
98      b = b or 255,
99      a = a or 255,
100   }, color_mt)
101 end
102 
103 -- Shorter alias — `color(r, g, b, a)` creates a color.
104 -- This makes the v1-style usage `red = color(255, 0, 0)` still work.
105 color = color_new
106 
107 --[[
108   color_from_hsl(h, s, l, a)
109   Create a color from HSL values (h: 0-360, s: 0-1, l: 0-1).
... [10 more lines]

26:#include <direct.h>  // _chdir
29:#include <unistd.h>  // chdir
10129:            _chdir(game_folder);
10131:            chdir(game_folder);

10110                        int key_len = (int)(eq - arg);
10111                       if (key_len >= MAX_CLI_KEY) key_len = MAX_CLI_KEY - 1;
10112                       strncpy(cli_args[cli_arg_count].key, arg, key_len);
10113                       cli_args[cli_arg_count].key[key_len] = '\0';
10114                       strncpy(cli_args[cli_arg_count].value, eq + 1, MAX_CLI_VALUE - 1);
10115                       cli_args[cli_arg_count].value[MAX_CLI_VALUE - 1] = '\0';
10116                   } else {
10117                       strncpy(cli_args[cli_arg_count].key, arg, MAX_CLI_KEY - 1);
10118                       cli_args[cli_arg_count].key[MAX_CLI_KEY - 1] = '\0';
10119                       // Use "true" as default value for flags without =
10120                       strncpy(cli_args[cli_arg_count].value, "true", MAX_CLI_VALUE - 1);
10121                   }
10122                   cli_arg_count++;
10123               } else if (!game_folder && !zip_initialized) {
10124                   game_folder = argv[i];
10125               }
10126           }
10127           if (game_folder) {
10128               #ifdef _WIN32
10129               _chdir(game_folder);
10130               #else
10131               chdir(game_folder);
10132               #endif
10133               printf("Game folder: %s\n", game_folder);
10134           }
10135       }
10136   
10137       printf("Loading: main.lua\n");
10138   
10139       // Initialize SDL (headless only needs timer, not video/audio/gamepad)
... [10 more lines]

main.lua OK
layer.lua OK
font.lua OK

The file E:\a327ex\Anchor2\app\main.lua has been updated successfully. (file state is current in your context — no need to Read it back)

Anchor Engine starting...
Headless mode enabled
Game folder: app
Loading: main.lua
Headless mode: skipping window and graphics initialization
Engine initialized (headless): 1440x900
app: framework loaded OK
Created layer: smooth (smooth)
Created layer: rough (rough)
Created layer: ui (smooth)
Loaded font: heading_smooth (42.0px, smooth) atlas=512x512
Loaded font: body_smooth (16.0px, smooth) atlas=512x512
Loaded font: small_smooth (12.0px, smooth) atlas=512x512
Loaded font: label_smooth (18.0px, smooth) atlas=512x512
Loaded font: heading_rough (22.0px, rough) atlas=512x512
Loaded font: body_rough (13.0px, rough) atlas=512x512
Loaded font: small_rough (11.0px, rough) atlas=512x512
Loaded font: label_rough (13.0px, rough) atlas=512x512
Initialization complete. Press ESC to exit, F11 for fullscreen.
Headless loop starting...
Shutting down...

Anchor Engine starting...
Headless mode enabled
Game folder: arena
Loading: main.lua
Headless mode: skipping window and graphics initialization
Engine initialized (headless): 480x270
arena: framework loaded OK
Physics initialized (Box2D)
Created layer: game (rough)
Created layer: ui (rough)
Loaded font: main (11.0px, rough) atlas=512x512
Loaded spritesheet: assets/hit1.png (5x1 frames, 5 total)
Initialization complete. Press ESC to exit, F11 for fullscreen.
Headless loop starting...
Shutting down...

File created successfully at: C:\Users\adn\.claude\projects\E--a327ex\memory\project_anchor_app.md (file state is current in your context — no need to Read it back)

1    # Memory
2   
3   ## Code Style - Emoji Ball Battles (Lua)
4   
5   ### Operator spacing convention
6   - `*` and `/`: no spaces (e.g., `a*b`, `x/y`)
7   - `+` and `-`: spaces (e.g., `a + b`, `x - y`)
8   
9   Example:
10  ```lua
11  result = a*b + c/d - e
12  velocity = speed*math.cos(angle) + offset
13  ```
14  
15  ## Conversion History
16  
17  - **Emoji Ball Battles**: Converted from YueScript to Lua (2026-02-24). Archived `.yue` files in `emoji-ball-battles/reference/yue/`. Framework files copied from `Anchor/framework/anchor/`.
18  - **Orblike**: Converted from YueScript to Lua (2026-02-25). Archived `.yue` files in `orblike/reference/yue/`. Framework files copied from `Anchor/framework/anchor/`.
19  
20  ## Naming Conventions
21  
22  - Always capitalize "Orblike" (capital O) — it's a proper name, not a directory path reference.
23  
24  ## Critical Warnings
25  - [Collider divergence](feedback_collider_divergence.md) — Orblike's collider.lua has steering functions not in framework; never overwrite
26  
27  ## Workflow
28  - [No permission for ability code](feedback_no_permission_abilities.md) — just implement after showing design, don't ask
29  - [Blog-post interview format](feedback_interview_format.md) — batch ~5 questions per post in interview.md, commit only at end, probe don't debate
30  
... [7 more lines]

The file C:\Users\adn\.claude\projects\E--a327ex\memory\MEMORY.md has been updated successfully. (file state is current in your context — no need to Read it back)

C:/Users/adn/AppData/Local/nvim/init.lua
C:/Users/adn/AppData/Local/nvim/lazy-lock.json
---

1    -- Start in project root
2   vim.api.nvim_set_current_dir("E:/a327ex")
3   
4   -- Neovide settings
5   if vim.g.neovide then
6     vim.g.neovide_cursor_animation_length = 0
7     vim.g.neovide_cursor_trail_size = 0
8     vim.g.neovide_scroll_animation_length = 0
9     vim.o.title = true
10    vim.o.titlestring = "NeoVim"
11    vim.o.guifont = "Cascadia Code:h11"  -- adjust size (h11, h10, h9, etc.)
12  end
13  
14  -- Bootstrap lazy.nvim
15  local lazypath = vim.fn.stdpath("data") .. "/lazy/lazy.nvim"
16  if not (vim.uv or vim.loop).fs_stat(lazypath) then
17    vim.fn.system({
18      "git", "clone", "--filter=blob:none",
19      "https://github.com/folke/lazy.nvim.git",
20      "--branch=stable", lazypath,
21    })
22  end
23  vim.opt.rtp:prepend(lazypath)
24  
25  -- Leader key (must be set before lazy)
26  vim.g.mapleader = ','
27  
28  vim.g.loaded_netrw = 1
29  vim.g.loaded_netrwPlugin = 1
30  
... [449 more lines]

drafts
images
pages
posts
---
context
files
logs
notes
pages

E:/a327ex/a327ex.com-blog/drafts/it_follows.txt.preview.html
E:/a327ex/a327ex.com-blog/drafts/the_haircutter.txt.preview.html
---

home.txt
---
home.md

[
  {
    "type": "tool_reference",
    "tool_name": "WebFetch"
  }
]

# Visual Design Analysis of a327ex.com

Based on the provided HTML content, I can describe the site's visual approach:

**Color Scheme & Typography:**
The page uses a clean, high-contrast design with what appears to be dark text on a light background (standard web defaults). No explicit CSS color declarations are visible in the provided excerpt, suggesting the site relies on browser defaults or external stylesheets not shown.

**Layout & Spacing:**
The design follows a minimalist aesthetic with generous whitespace. Content is organized hierarchically:

- A simple header with the site name and navigation links
- Key projects/links presented as a concise list
- Footer contact information separated by horizontal rules (`* * *`)

**Visual Elements:**

- Horizontal dividers (represented as `* * *`) create subtle segmentation
- Minimal use of visual accents—primarily text-based navigation
- Link styling appears standard (underlined or colored hyperlinks)

**Overall Mood:**
The site embodies a distinctly **minimalist** and **utilitarian** aesthetic. It prioritizes content clarity and accessibility over decorative elements. The sparse layout suggests a developer's portfolio that values function over form—appropriate for a game developer/writer sharing work and contact information.

This approach is characteristic of many indie developer sites that favor readability and direct navigation.

# Visual Design Analysis

Based on the provided content, I cannot perform a detailed visual design analysis because **the source material contains only HTML structure and navigation elements—no CSS declarations are visible**.

The page shows:

- A navigation-heavy layout with extensive link listings
- Minimal styling information (no font-family, color, spacing values, borders, or shadows are disclosed)
- A content section describing the site's purpose as a devlog

## What Can Be Inferred

The site appears to prioritize **content organization and accessibility** over visual flourish. The lengthy navigation suggests a documentation-focused aesthetic rather than a polished marketing presence.

## Limitations

Without access to actual CSS files or visual rendering, I cannot provide:

- Specific color values (background, text)
- Font family declarations
- Spacing metrics
- Shadow or border details
- Comparative analysis to a327ex.com's design

**To complete this analysis**, you would need to share the site's CSS stylesheet or a screenshot showing the rendered appearance.

I cannot provide the HTML content of the `<head>` tag because it is not included in the web page content you've shared. The material provided only contains the visible body content of the page, which lists navigation links, featured projects, and contact information.

To access the `<head>` section (including stylesheet links and style tags), you would need to either:

- View the page source directly in your browser
- Share the complete HTML document including the head section

<html>
<head><title>403 Forbidden</title></head>
<body>
<center><h1>403 Forbidden</h1></center>
<hr><center>openresty</center>
</body>
</html>

<!DOCTYPE html>
<html>
  <head>
      <meta charset="utf-8">
      <meta name="viewport" content="width=device-width, initial-scale=1">

      <title> - a327ex</title>
      <meta name="description" content="It Follows (Dec 2025, STORY) SNKRX (May 2021, Steam, GAME) BYTEPATH (Feb 2018, Steam, GAME)   Read my devlog Read my blog Follow me on steam   And">
      
      <!-- Begin proprietary meta tags for sharing on social media -->
      <meta property="og:title" content=" - a327ex">
      <meta property="og:description" content="It Follows (Dec 2025, STORY) SNKRX (May 2021, Steam, GAME) BYTEPATH (Feb 2018, Steam, GAME)   Read my devlog Read my blog Follow me on steam   And">
      <meta property="og:type" content="website">
      <meta property="og:url" content="https://a327ex.com/">
      <!-- End proprietary meta tags for sharing on social media -->

      <link rel="alternate" type="application/rss+xml" title="a327ex" href="https://a327ex.com/feed.rss">
      <link rel="icon" href="https://cdn.blot.im/blog_13d6ee76e82c4da8b3e12f8748579ad0/_avatars/4582df12-c96a-43bd-acaf-7cfef8e17f1f.jpg" type="image/x-icon">
      <link rel="stylesheet" href="https://cdn.blot.im/template/d5/ee/1ac36782338efe961bc12c315da0/style.css">
  </head>  <body>
    <div class="header alignment-justified position-top">
        <a id="logo" href="/">
          <!-- 
          <img class="avatar " src="https:&#x2F;&#x2F;cdn.blot.im&#x2F;blog_13d6ee76e82c4da8b3e12f8748579ad0&#x2F;_avatars&#x2F;4582df12-c96a-43bd-acaf-7cfef8e17f1f.jpg" alt="a327ex"/>
           -->
          a327ex
        </a>

        <div class="nav">
          <a href="/" title=""></a>
... [20 more lines]

<persisted-output>
Output too large (60.5KB). Full output saved to: C:\Users\adn\.claude\projects\E--a327ex\776d994d-07fd-4a03-a799-680a4b64e07c\tool-results\bcn2d8ptx.txt

Preview (first 2KB):
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... [10 more lines]

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",
      "media_type": "image/png"
    }
  }
]

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File created successfully at: E:\a327ex\Anchor2\app\docs\visual_identity.md (file state is current in your context — no need to Read it back)

Launching skill: frontend-design:frontend-design

1    # Anchor App — Visual Identity Brief
2   
3   Authoritative reference for the app's look and feel. Feed image-generation
4   prompts from the bottom section into ChatGPT's `gpt-image-1` (best for UI
5   screenshots with legible text), Midjourney v7 (best for mood boards), or
6   Flux 1.1 Pro (best for local control). Interactive HTML mockups are generated
7   by Claude directly.
8   
9   ---
10  
11  ## 1. What the app is
12  
13  Anchor is a single, unified workspace for all creative work — writing,
14  reading, coding, note-making, music composition, game development — built
15  entirely on the Anchor game engine. It replaces a scattered collection of
16  tools (Notepad, NeoVim, Claude Code, Explorer, DAW, browser) with one
17  environment owned end-to-end by one user.
18  
19  Documents are **spatial canvases** where elements (text blocks, images, code,
20  game views, diagrams) are positioned freely at (x, y, w, h). There is no
21  Markdown — the document *is* its visual form. A blog post is a canvas whose
22  elements happen to be stacked in a column. A knowledge map is a canvas with
23  elements placed spatially. Same primitive either way.
24  
25  It also serves triple use: the app is the daily dev environment, the website
26  (a327ex.com) is rendered by the same engine compiled to WASM, and artistic
27  artifacts (games, interactive essays) drop into the same view primitives.
28  
29  The prevailing feel target is **meticulously customized Emacs or Bloomberg
30  Terminal**, not Stardew Valley. Dense, keyboard-first, information-rich, every
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1    ---
2   name: Anchor app (omega app)
3   description: Canvas-based workspace app in Anchor2/app/ — the omega-app vision from OMEGA_APP_PLAN.md, starting Phase 1 Foundation 2026-04-17
4   type: project
5   originSessionId: 776d994d-07fd-4a03-a799-680a4b64e07c
6   ---
7   The user is building an "omega app" in `Anchor2/app/` — a canvas-based unified workspace (planned to replace Notepad, Explorer, editors, DAW, browser). The authoritative design is `OMEGA_APP_PLAN.md` in the repo root. Documents are spatial canvases of positioned elements (text, image, code, game view); no Markdown; native structured format. Triple use: dev environment, a327ex.com website via WASM, artistic artifacts — all rendered by Anchor.
8   
9   **Why:** Four months of Claude Code use eroded code ownership; the realization was that what needs owning is the *environment*, not the code. Claude-written code is replaceable; the place you work inside of isn't.
10  
11  **How to apply:**
12  - Follow `OMEGA_APP_PLAN.md` phase order (1 Foundation → 10 Background). Phase 1 has many sub-systems; build one at a time.
13  - Target hardware is a single 1920×1080 Windows monitor. No hi-DPI or multi-monitor work needed.
14  - App runs at `engine_set_game_size(1440, 900)` + `scale=1`, `filter='smooth'`. Not pixel-art; high-res for legibility.
15  - Engine now supports per-layer + per-font `filter_mode` (smooth/rough). Mixed-mode frames work: game-view elements can be rough layers inside an otherwise smooth canvas.
16  - Coding conventions match arena (`Anchor2/arena/main.lua`): procedural framework modules, `class()` for entities, `make_entity(self)`, ID-based cross-refs, explicit destroy.
17  

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190  - Conversation view as a panel
191 
192 **Milestone:** Blog posts are written in this app. It's the daily writing tool. Vim keys work. Modes switch. AI Oracle available for questions.
193 
194 ---
195 
196 ### Phase 3: Filesystem + Tagging
197 
198 **Filesystem view:**
199 - Tree view of directories (panel in Browse mode)
200 - File preview (click to preview without opening)
201 - File operations (create, rename, move, delete — with undo)
202 - Drag files between folders
203 
204 **Metadata database (SQLite):**
205 - Every file gets a stable ID
206 - Tags (arbitrary string labels)
207 - Project assignments (file belongs to projects X, Y)
208 - Custom metadata
209 - Full-text search index
210 
211 **Tag-based workflow:**
212 - Right-click file → assign to project, add tags
213 - Filter views: files matching tag query
214 - Tag management panel
215 
216 **AI integration for this phase:**
217 - AI-assisted tagging: agent scans untagged files, suggests tags
218 - AI memory per file: conversation summaries attach to file metadata
219 - Librarian agent: search-focused, finds things in knowledge base
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320  
321 **Milestone:** Notes, references, highlights organized and searchable. Knowledge base with AI-suggested connections.
322 
323 ---
324 
325 ### Phase 8: Music Views
326 
327 **Composition:**
328 - Piano roll view
329 - Synth/instrument patches using Anchor audio system
330 - Sound library browser (integrated with filesystem tags)
331 
332 **Theory learning:**
333 - Exercise view (chord ID, scale construction, intervals)
334 - Reference wall for songs being studied
335 - Progress tracking
336 
337 **AI integration for this phase:**
338 - Composer agent: music-focused, knows theory curriculum, suggests chord changes
339 - Active during composition and practice
340 
341 **Milestone:** Chiptune game music composable within the app. Theory learning integrated with composition tools.
342 
343 ---
344 
345 ### Phase 9: Game Development Views
346 
347 **Core:**
348 - Game launcher (run projects from the app)
349 - Live game state inspection
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Found 2 files
Anchor2\app\docs\visual_identity.md
anchor.blot.im\logs\anchor-arena-final-and-neovim-diff-tool.md

Found 1 file
C:\Users\adn\.claude\projects\E--a327ex\memory\project_anchor_app.md

172:by phase from OMEGA_APP_PLAN.md. Image-gen prompts below reference these.

12:1. `OMEGA_APP_PLAN.md` in repo root — the 10-phase build plan.

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