# Arc Skill > Solve an interactive hidden-rule ARC-AGI-3 game from its game ID. Contains the complete playing doctrine (predict before every action, graded claims, one-page notes, optional executable-rules search) plus the `arc` harness the agent drives. Use whenever asked to solve, play, or continue an ARC-AGI-3 game. - Skill: `pbshgthm/arc-skill` (Agent Skill, multi-file: 15 files) - Install (CLI): `npx skillmds@latest add pbshgthm/arc-skill` - Raw SKILL.md: https://api.skillmd.com/api/skills/pbshgthm/arc-skill/raw - Safety review: pending (external: skill-scanner PASS, skillspector CAUTION) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: pbshgthm (https://skillmd.com/u/pbshgthm) - Updated: 2026-09-22 - Page: https://skillmd.com/skills/pbshgthm/arc-skill --- # Arc skill Set the launcher once, work inside one directory per game, then start or resume: ```bash ARC="/scripts/arc" # absolute path mkdir -p && cd # one directory = one run "$ARC" start ``` `start` defaults to a local simulator with competition semantics: one logical run, append-only history, paid resets, completed levels never lost. It is crash-safe — after any interruption, rerun `"$ARC" start ` and the run is resumed or replayed exactly. Use `--mode competition` (live remote server, ~15-minute idle lease, no replay recovery) only when the user explicitly asks. Never create a second run for the same game, never inspect the game's source or private state, and never edit `.arc/` by hand except `NOTES.md`. ## The game A 64×64 board of 16 colors, hidden rules, several levels. Interface priors (not guarantees): ACTION1/2/3/4 = up/down/left/right, ACTION5 = interact, ACTION6:x,y = click at x=column y=row, ACTION7 = undo. Availability can change after every action. **Finish first.** Historically every lost point came from unfinished games, not from extra actions. Early levels are usually cheap tutorials: a wrong action that teaches a mechanic beats a minute of deliberation. Act early, act often, learn from every grade. Efficiency only matters once finishing is likely. ## The loop — look, predict, act, compare, note 1. **Look**: open the printed `IMAGE`; read the worded `TRANSITION` story. 2. **Predict + act**: every action requires `--predict`; the harness grades it: ```bash "$ARC" act ACTION1 --predict "move 12,5 0,-1" "$ARC" act ACTION6 3 14 --predict "cell 3,14=9; region 0:8,10:20" --because "test button" ``` 3. **Compare**: read the ✓/✗ grade, the worded `TRANSITION` story, and the cell-exact `DIFF` before/after masks in the result (`arc view` re-renders them for any event). A ✗ is the most valuable thing that can happen — reality just corrected you for one action. 4. **Note**: keep `.arc/NOTES.md` to one page with three sections — `Verified (cite event ids)`, `Assumed / open questions`, `Plan`. After a ✗, fix the notes before the next action. `arc status` prints the file in full, so it is also your recovery story after any context loss. Claim vocabulary (full reference: `"$ARC" act --help`): `noop`, `change`, `cell X,Y=V`, `move X,Y DX,DY`, `vanish X,Y`, `region X0:X1,Y0:Y1`, `level+1`, `win`; several separated by `;`. Coordinates are x=column, y=row, like ACTION6. Free text is allowed and merely claims "something changes" — prefer one specific claim; it grades sharper and teaches more. ## Batching proven mechanics Once a mechanic is verified, stop paying one command per step — batch with a claim on every step; execution halts at the first miss so a wrong theory cannot burn the rest of the queue: ```bash "$ARC" commit \ --step "ACTION4 :: move 12,5 1,0" \ --step "ACTION4 :: move 13,5 1,0" \ --step "ACTION1 :: level+1" ``` Batch only movement you can predict cell-exactly or level-exactly; never batch exploration. ## Levels, consumables, reset - Completing a level archives your notes to `.arc/levels/`. The new level may reuse mechanics — treat every earlier `Verified` claim as `Assumed` until it survives one test on the new board (status reminds you until the notes change). - An object that vanished and never came back is a consumable. Spend consumables last, after reversible probes; before an irreversible-looking action, prefer ACTION7 (undo) tests when available. - `"$ARC" reset --because ""` rewinds only the current level, for the price of one action. After `GAME_OVER` the reason may be omitted. Completed levels and history are never lost. ## When a level resists — the rules tier (optional) Status nudges you after many actions or repeated misses on one level. Then, and only then, escalate from prose to executable rules: write a plain `rules.py` (grounding, step, actions, goal), verify it against the entire recorded history, and let A* search find the plan. Each plan step carries its own prediction, so live execution still halts on the first surprise. ```bash "$ARC" rules help # the compact contract "$ARC" rules init # template; then edit rules.py "$ARC" rules replay # must fit or gap on every recorded transition "$ARC" rules solve # writes .arc/plan.json "$ARC" commit @.arc/plan.json ``` Model only verified mechanics; mark everything else `Unknown("why")` — replay reports gaps honestly instead of pretending a fit. This tier is never required and never worth it before the game has taught you its mechanics. ## Evidence tools ```bash "$ARC" status # full picture + notes; run after context loss "$ARC" view --grid # exact 0-f pixels "$ARC" view --crop 8:24,10:30 # exact half-open crop "$ARC" view --event 12 --frames # animation frames of a past action "$ARC" python 'connected_components(grid)' "$ARC" python 'shortest_path((r0,c0),(r1,c1), passable_mask)' ``` `arc python` preloads every settled board (`grid`, `previous`, `frames`, `transitions`, `actions`), NumPy, perception helpers, BFS, and A* — free offline computation; use it for parsing and pathfinding instead of paid probing. ## Install location This folder is agent-agnostic. Copy it into the platform's auto-discovered skill directory (Claude Code: `.claude/skills/arc-skill/`, Codex: `.agents/skills/arc-skill/`). From an unrecognized location, instruct the agent to read this `SKILL.md` completely before starting.