ab-methodology
FreeUse for ab methodology recipes when optimizing a Coworld player.
The English summary is being prepared. Showing the original description.
Use for reusable navigation pathfinding recipes in software and coding-agent work.
The English summary is being prepared. Showing the original description.
See how to installReview the instructions the agent will receive before you install.
On-demand recipes (2). Trigger→action heuristics; pull the relevant one when its situation arises.
generic
Always use A* for grid navigation, never greedy/best-first, which detours and dead-ends around walls and oscillates forever between two cells each closer on a different axis; A* has no per-tick directional choice so it eliminates oscillation structurally (in alpha_cog cogs-v-clips this cut max stuck-ticks 5875 -> 11 and closed the largest tournament gap, so a sky-high max-stuck stat signals navigation, not strategy, is the bottleneck). Treat out-of-bounds queries as impassable WALL (keeps the search total, avoids scattering bounds checks). Match A*'s unexplored-tile assumption to the policy's: if the policy treats unexplored as passable, A* must too. Use a Manhattan heuristic with a tie-breaking counter for determinism, and cap node expansions to bound per-tick cost (alpha_cog uses 10,000) -- but a cap set below what a real path needs makes A* silently give up even when a path exists (a 30,000 cap failed on a path needing ~92,000 expansions), so confirm reachability with an UNCAPPED BFS and compare expansion count to the cap before blaming the map. <sub>sources: claude-code:27984094-3b9e-4e67-92c5-da2a61ceb32a, codex:019e031e-f7d3-7342-a7d9-96993bc91097, claude-code:19ac76fb-7c48-44a1-81dd-eebcbdc9c19c, opencode:ses_1ff24a65cffeJSXwU2v6gcXbHQ (+6)</sub>
generic · ⚠ session-derived, unverified
Give every action/task a success condition, a bounded retry budget, and a clean failure that hands control back with fresh state. An action with no success signal, no timeout, and no fallback becomes an infinite no-op loop (example: a task pressed a button every other tick for 300+ ticks because its success detection was broken and it never saw completion). A 'complete' flag that does not change the next decision creates a re-entry loop — if a meta-decider re-selects the same state because its inputs are unchanged, ensure completing a state changes observable state or the decider's inputs. A no-op fallback on a transient degraded state traps the agent in dead time if the no-op does nothing to recover — prefer an active escape/recovery action. Make a reflex's cooldown at least as long as the behavior it triggers, or the cooldown expires mid-behavior and the reflex re-fires before finishing. <sub>sources: claude-code:3b14ac5a-1d66-4524-94c0-59a48466d223, claude-code:067e7439-cbd1-4b26-9b3f-d054bde3aa40, claude-code:0919285d-1374-4827-b596-6e7107d95526</sub>
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Use for ab methodology recipes when optimizing a Coworld player.
The English summary is being prepared. Showing the original description.
Use for ab methodology recipes in scripted Coworld policy optimization.
The English summary is being prepared. Showing the original description.
Use for reusable ab methodology recipes in software and coding-agent work.
The English summary is being prepared. Showing the original description.
Use for Crewrift-specific ab methodology recipes when optimizing a player.
The English summary is being prepared. Showing the original description.
Use for Crewrift-specific agent workflow collab recipes when optimizing a player.
The English summary is being prepared. Showing the original description.
Use for agent workflow collab recipes when optimizing a Coworld player.
The English summary is being prepared. Showing the original description.