AI core (scenes/ai/, 5 new files from 3 gdscript-refactor agents in parallel):
- job.gd (59 lines, Agent A): Job class, RefCounted, label + toils + cursor +
to_dict/from_dict round-trip
- toil.gd (76 lines, Agent A): Toil class, RefCounted; kinds WALK/WAIT/IDLE;
factories walk_to/wait_ticks/idle; Vector2i stored as to_x/to_y ints
because Godot 4 JSON.stringify doesn't round-trip Vector2i
- work_provider.gd (27 lines, Agent A): abstract base, class_name, @export
category/priority, find_best_for() with push_error subclass guard
- job_runner.gd (186 lines, Agent B): Node-derived runner; setup/start_job/
cancel_job/tick; WALK toil delegates to pawn.walk_along_path on first
encounter (sets data.started=true), listens for walk_completed signal;
WAIT decrements ticks_remaining; IDLE never completes; full to_dict/from_dict
- decision.gd (50 lines, Agent C): static pick_next_job(pawn, providers); 5
layers (incapacitation/forced/status/work/idle); layer 1 probes via
has_method to stay future-proof for Phase 9
- rest_provider.gd (31 lines, Agent C): extends WorkProvider; @export rest_tile;
returns [walk_to(rest_tile), idle()] Job
Integration (Opus):
- pawn.gd: added forced_job slot, job_runner ref, _orchestrate_ai called
before _advance_walk on each sim_tick. Calls Decision when forced_job is
queued OR when idle — was a bug initially (only-on-idle never preempted
the never-completing IDLE toil); fixed and caught via MCP runtime test.
Added to_dict/from_dict for save round-trip; captures tile, _path,
_step_progress, _selected, forced_job, job_runner via their serializers.
- selection.gd: rewrote to build a forced-job [walk_to + idle] and set
pawn.forced_job; Decision preempts current job on next tick.
- world.tscn/gd: instantiates RestProvider as child (rest_tile = (50,50)
just outside the stone ring's south-east, reachable from all 3 spawn
tiles); registers via World.register_work_provider; attaches a JobRunner
child to each spawned pawn and wires setup(pawn, pathfinder).
- world.gd autoload: added work_providers list + register/clear methods.
- save_system.gd: write_save walks World.pawns calling to_dict; apply_save
zips dicts to pawns by index (Phase 16 will add stable IDs).
- main.gd: bootstrap log line bumped Phase 2 → Phase 3.
Acceptance — MCP-verified end-to-end:
- 3 pawns boot, Decision assigns each Rest, JobRunner starts each,
all 3 walk to (50,50) on different paths (40/35/30 steps based on
detour around the stone ring), arrive and idle.
- Force Bram to (10,10) via pawn.forced_job; preempt fires:
[decision] Bram: forced 'Go to (10, 10)'. Bram walks while Cora/Edda
stay parked.
- Mid-walk save round-trip (the critical Phase 3 acceptance):
- Paused Bram at (51,10) walking to (70,70) with 79 path steps remaining
- SaveSystem.write_save() → SaveSystem.apply_save(read_save()) after a
mutate-to-(0,0)-with-no-path round-trip
- Restored Bram exactly: tile=(51,10), _path.size=79, walking=true,
job='Go to (70, 70)' at toil_idx=0 (WALK toil with data.started=true)
- Resumed sim → JobRunner's WALK toil saw started=true and did NOT
re-call walk_along_path; the pawn's restored _path continued the walk
naturally → reached (70,26) with 44 steps remaining, still on the
same job. The architecture.md 'mid-toil suspend safe' contract is
provably honored.
Phase 3 gotchas (logged in implementation.md):
- Class-name registration timing bit again (Phase 2 gotcha). Workflow:
agent writes class_name file → MCP reload_project → headless validate.
- Forced-job preempt requires triggering Decision when forced_job != null,
not just when idle (IDLE toil never completes).
- execute_game_script + await Engine.get_main_loop().process_frame is
flaky — MCP auto-recovers but the script's last lines may be lost.
Workaround: split state-inspection into a fresh execute_game_script.
Delegation report this phase:
- gdscript-refactor (Sonnet) Agent A: Job + Toil + WorkProvider abstract
base. 3 files, 162 lines.
- gdscript-refactor (Sonnet) Agent B: JobRunner with toil-execution match
+ walk_completed signal handling + full save round-trip. 1 file, 186
lines.
- gdscript-refactor (Sonnet) Agent C: Decision pipeline + RestProvider.
2 files, 81 lines.
- Opus: Pawn integration (forced_job slot, orchestration, to_dict/from_dict),
Selection rewrite, world.tscn/gd wiring, World autoload work_providers
list, SaveSystem extension, MCP-driven runtime verification including
the mid-walk save round-trip demo, gotcha logging.
~70% of Phase 3's GDScript was written by subagents.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
183 lines
6.8 KiB
GDScript
183 lines
6.8 KiB
GDScript
extends Node2D
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## Phase 2 world view. 80×80 TileMap with 6 layers, 3 sample pawns, pathfinder,
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## click-to-select / click-to-move selection.
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##
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## Real ElvGames art lands in Phase 5+ (wood walls custom-authored on
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## FG_Houses, stone walls autotiled from FG_Fortress per the 2026-05-10
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## audit lock). The procedural placeholder tileset is enough to prove the
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## TileMap pipeline + pawn movement + camera + pathfinding end-to-end.
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##
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## TileMap layer indices follow docs/architecture.md:
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## 0 Terrain · 1 Floor · 2 Wall · 3 Designation · 4 Roof · 5 Fog
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const MAP_SIZE_TILES: Vector2i = Vector2i(80, 80)
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const TILE_SIZE_PX: int = 16
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# Atlas coords inside the placeholder tileset (one source, source_id = 0).
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# Real assets in Phase 5 will use multiple atlas sources.
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const TILE_GRASS: Vector2i = Vector2i(0, 0)
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const TILE_DIRT: Vector2i = Vector2i(1, 0)
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const TILE_STONE: Vector2i = Vector2i(2, 0)
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const TILE_STONE_DARK: Vector2i = Vector2i(3, 0)
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const PLACEHOLDER_SOURCE_ID: int = 0
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const PAWN_SCENE: PackedScene = preload("res://scenes/pawn/pawn.tscn")
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# 3 starting pawns — Phase 2 demo. Phase 7+ replaces this with map-gen + name table.
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const SAMPLE_PAWNS: Array[Dictionary] = [
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{"name": "Bram", "tile": Vector2i(20, 40)},
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{"name": "Cora", "tile": Vector2i(25, 40)},
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{"name": "Edda", "tile": Vector2i(30, 40)},
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]
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@onready var terrain_layer: TileMapLayer = $Terrain
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@onready var floor_layer: TileMapLayer = $Floor
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@onready var wall_layer: TileMapLayer = $Wall
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@onready var designation_layer: TileMapLayer = $Designation
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@onready var roof_layer: TileMapLayer = $Roof
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@onready var fog_layer: TileMapLayer = $Fog
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@onready var pathfinder: Pathfinder = $Pathfinder
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@onready var selection: Selection = $Selection
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@onready var rest_provider: RestProvider = $RestProvider
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func _ready() -> void:
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Audit.log("world", "Phase 3 — building %d×%d world + pawns + AI." % [MAP_SIZE_TILES.x, MAP_SIZE_TILES.y])
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var tileset := _build_placeholder_tileset()
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for layer in [terrain_layer, floor_layer, wall_layer, designation_layer, roof_layer, fog_layer]:
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layer.tile_set = tileset
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_paint_terrain()
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_paint_sample_walls()
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_apply_camera_bounds()
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pathfinder.setup(MAP_SIZE_TILES)
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_wire_walls_to_pathfinder()
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selection.bind(pathfinder)
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World.register_work_provider(rest_provider)
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_spawn_sample_pawns()
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_run_pathfinder_spike()
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func world_bounds_px() -> Rect2:
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return Rect2(Vector2.ZERO, Vector2(MAP_SIZE_TILES * TILE_SIZE_PX))
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# ── tileset & map painting ──────────────────────────────────────────────────
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func _build_placeholder_tileset() -> TileSet:
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# Four 16×16 placeholder tiles laid out as a 4×1 atlas. No PNG dependency
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# — atlas built at runtime from a programmatic Image. Real ElvGames art
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# replaces this when wood/stone wall variants are imported in Phase 5.
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var ts := TileSet.new()
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ts.tile_size = Vector2i(TILE_SIZE_PX, TILE_SIZE_PX)
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var atlas_w := TILE_SIZE_PX * 4
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var img := Image.create(atlas_w, TILE_SIZE_PX, false, Image.FORMAT_RGBA8)
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var palette: Array[Color] = [
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Color(0.45, 0.65, 0.30), # grass
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Color(0.55, 0.45, 0.30), # dirt
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Color(0.60, 0.60, 0.55), # stone
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Color(0.30, 0.30, 0.32), # stone dark
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]
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for i in palette.size():
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var base: Color = palette[i]
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var border: Color = base.darkened(0.15)
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for px in TILE_SIZE_PX:
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for py in TILE_SIZE_PX:
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var on_border := (
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px == 0 or px == TILE_SIZE_PX - 1
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or py == 0 or py == TILE_SIZE_PX - 1
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)
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img.set_pixel(i * TILE_SIZE_PX + px, py, border if on_border else base)
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var tex := ImageTexture.create_from_image(img)
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var src := TileSetAtlasSource.new()
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src.texture = tex
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src.texture_region_size = Vector2i(TILE_SIZE_PX, TILE_SIZE_PX)
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for i in palette.size():
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src.create_tile(Vector2i(i, 0))
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ts.add_source(src, PLACEHOLDER_SOURCE_ID)
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return ts
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func _paint_terrain() -> void:
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for x in MAP_SIZE_TILES.x:
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for y in MAP_SIZE_TILES.y:
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terrain_layer.set_cell(Vector2i(x, y), PLACEHOLDER_SOURCE_ID, TILE_GRASS)
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func _paint_sample_walls() -> void:
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# An 8×8 stone ring near the map centre as a visual landmark + pathfinding
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# obstacle so the demo proves pawns route around walls.
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var origin := Vector2i(36, 36)
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var size: int = 8
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for i in size:
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wall_layer.set_cell(origin + Vector2i(i, 0), PLACEHOLDER_SOURCE_ID, TILE_STONE)
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wall_layer.set_cell(origin + Vector2i(i, size - 1), PLACEHOLDER_SOURCE_ID, TILE_STONE)
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wall_layer.set_cell(origin + Vector2i(0, i), PLACEHOLDER_SOURCE_ID, TILE_STONE_DARK)
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wall_layer.set_cell(origin + Vector2i(size - 1, i), PLACEHOLDER_SOURCE_ID, TILE_STONE_DARK)
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# ── pathfinder + pawns ──────────────────────────────────────────────────────
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func _wire_walls_to_pathfinder() -> void:
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# Wall cells block pathing. Re-runs on Phase 5 build/destroy events later.
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var wall_cells := wall_layer.get_used_cells()
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for cell in wall_cells:
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pathfinder.set_cell_walkable(cell, false)
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Audit.log("world", "%d wall cells marked impassable" % wall_cells.size())
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func _spawn_sample_pawns() -> void:
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for spawn_data in SAMPLE_PAWNS:
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var p: Pawn = PAWN_SCENE.instantiate()
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add_child(p)
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p.setup(spawn_data["name"], spawn_data["tile"])
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# Phase 3: attach a JobRunner so Decision can hand it jobs.
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var jr := JobRunner.new()
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jr.name = "JobRunner"
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p.add_child(jr)
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jr.setup(p, pathfinder)
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p.job_runner = jr
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World.register_pawn(p)
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# ── spike: AStarGrid2D query timing at 80² ──────────────────────────────────
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func _run_pathfinder_spike() -> void:
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# Phase 2 acceptance spike (~30 min): "AStarGrid2D path-query timing at 80²
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# with 6 pawns simultaneously requesting paths. Confirm sub-millisecond."
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# We benchmark all 4-corner pairs × 3 iterations = 36 path queries.
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var corners := [
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Vector2i(2, 2),
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Vector2i(MAP_SIZE_TILES.x - 3, 2),
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Vector2i(2, MAP_SIZE_TILES.y - 3),
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Vector2i(MAP_SIZE_TILES.x - 3, MAP_SIZE_TILES.y - 3),
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]
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var pairs: Array = []
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for a in corners:
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for b in corners:
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if a != b:
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pairs.append([a, b])
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var result: Dictionary = pathfinder.benchmark(pairs, 3)
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Audit.log("world", "spike: %d paths min=%d us avg=%.1f us max=%d us" % [
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result["total_paths"], result["min_us"], result["avg_us"], result["max_us"]
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])
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# ── camera bounds ───────────────────────────────────────────────────────────
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func _apply_camera_bounds() -> void:
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var cam := get_node_or_null("CameraRig")
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if cam == null:
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Audit.log("world", "no CameraRig child yet — bounds set later when camera lands.")
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return
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if not cam.has_method("set_world_bounds"):
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Audit.log("world", "CameraRig present but missing set_world_bounds() — skipping.")
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return
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cam.set_world_bounds(world_bounds_px())
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