One search for your own team's files and the public ecosystem. See how real projects write their agent instructions, and bring the good ideas home.
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
putervisionSkillputervision/agent-reasoning-mcp/.agents/skills/state-memory-mcp/SKILL.md
Teaches the agent to use the state-memory-mcp MCP server to track workflow state, tasks, decisions, blockers, artifacts, plans, milestones, and their semantic relationships in a persistent graph database.
Often used withwebcrypt-mcp
putervisionCLAUDE.mdputervision/agent-reasoning-mcp/CLAUDE.md
This project utilizes vision-memory-mcp to cache visual states, record layout transitions, provide element grounding, and avoid repetitive LLM vision calls. This project uses `world-mo
putervisionCursor ruleputervision/agent-reasoning-mcp/.cursor/rules/agent-reasoning-mcp.mdc
This project uses agent-reasoning-mcp with project slug "agent-reasoning-mcp" to manage goals, decompose complex tasks, evaluate situational trade-offs, and track decision rationale.
putervisionCursor ruleputervision/agent-reasoning-mcp/.cursor/rules/behavior-mcp.mdc
This project uses behavior-mcp with project slug "agent-reasoning-mcp" to execute deterministic behavior trees at ~60Hz in browser runtimes with reactive triggers and safety guardrails.
putervisionCursor ruleputervision/agent-reasoning-mcp/.cursor/rules/state-memory-mcp.mdc
This project tracks workflow state, tasks, design decisions, and blockers using state-memory-mcp with project slug "agent-reasoning-mcp".
putervisionCursor ruleputervision/agent-reasoning-mcp/.cursor/rules/world-model-mcp.mdc
This project uses world-model-mcp with project slug "agent-reasoning-mcp" to maintain a persistent 3D/2D spatial internal world model, entity tracking, object permanence, and movement simulation.
putervisionllms.txtputervision/agent-reasoning-mcp/docs/llms.txt
Strategic BDI Reasoning & Decision Intelligence for Autonomous AI Agents @putervision/agent-reasoning-mcp implements belief-desire-intention (BDI) cognitive architecture for autonomous AI agents. It provides goal hierarchy decomposition, multi-attribute expected utility calculation ($E[U] = \sum w_i u_i$), exponential belief decay ($\lambda = 0.05/\text{hr}$), quantitative risk evaluation, reactive replanning upon obstacles, and an intention queue wire contract for runtime execution. Non-claims statement: Functional agency and closed-loop automation — not consciousness, sentience, or AGI.
Plain text files in a repository that tell a coding agent how the project works: commands to run, conventions to follow and things to avoid. CLAUDE.md, AGENTS.md, cursor rules and skills are the common kinds.
CLAUDE.md is read by Claude Code. AGENTS.md is an open format that Codex, Cursor and other agents read. Many projects keep one and point the other at it.
A folder with a SKILL.md that describes one capability, such as filling PDFs or reviewing code. The agent loads it only when the task calls for it.
Your agents already can, over MCP, limited to the files you're allowed to read. Searching them from this page is coming.
