behavior-mcp / rules
Cursor rule24 starsChanged 47 days agoMITView on GitHub
This project uses world-model-mcp with project slug "behavior-mcp" to maintain a persistent 3D/2D spatial internal world model, entity tracking, object permanence, and movement simulation.
Where files are headingNew Cursor rule files have more rules about planning and tracking tasks, and fewer about code style.
Of the Cursor rule files we read, the 4,183 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository15 other files it gives its agents.
- .agents/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- .cursor/rules/agent-reasoning-mcp.mdcCursor rule
- .cursor/rules/behavior-mcp.mdcCursor rule
- .cursor/rules/state-memory-mcp.mdcCursor rule
- .cursor/rules/vision-memory-mcp.mdcCursor rule
- docs/llms.txtllms.txt
- agent-reasoning-mcpSkill
- behavior-mcpSkill
- state-memory-mcpSkill
- video-ingestSkill
- vision-memory-mcpSkill
- webcrypt-mcpSkill
- world-model-mcpSkill
The file
We split this world-model-mcp.mdc into the rules it gives an agent
3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 7
Orient & Explore: Call get_spatial_map(format: 'summary') and get_expected_view at the start of spatial or simulated tasks.
- Very specific: line 8
Entity Queries: Use query_entities (FTS5 search, proximity radius, or entity_id lookup) before creating duplicate objects.
- Very specific: line 13
Action Simulation & Validation: Before executing movement, call simulate_movement to verify path validity and avoid AABB obstacle …
≈ “Common” is an estimate: at least 1 in 5 of the 6,668 Cursor rule files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
<!-- world-model-mcp:start --> ## Spatial World Model (world-model-mcp) This project uses `world-model-mcp` with project slug "behavior-mcp" to maintain a persistent 3D/2D spatial internal world model, entity tracking, object permanence, and movement simulation. ### 1. Mandatory Workflow & Priority 1. **Orient & Explore**: Call `get_spatial_map(format: 'summary')` and `get_expected_view` at the start of spatial or simulated tasks. 2. **Entity Queries**: Use `query_entities` (FTS5 search, proximity radius, or entity_id lookup) before creating duplicate objects. 3. **Perception Bridging**: - Ingest detected objects from vision models using `ingest_observation`. - Reconcile expected vs observed visual state using `ingest_observation(reconcile: true)`. 4. **Spatial Relations**: Record topological containment, support, or proximity using `set_relation` (e.g. `on`, `inside`, `next_to`, `contains`). 5. **Action Simulation & Validation**: Before executing movement, call `simulate_movement` to verify path validity and avoid AABB obstacle collisions, or `simulate_movement(mode: 'navigate')` for waypoint planning. 6. **Goal Alignment**: Link target entities and destination regions to active `state-memory-mcp` tasks using `link_to_goal`. 7. **Action Outcomes**: Record movement success and entity mutations using `record_outcome`. ### 2. Tool Reference Summary (15 Core MCP Tools) * `update_entity`: Create or update an entity (position, orientation, bounding box, properties, confidence). * `query_entities`: Search entities by keyword, type, region, spatial proximity, tags, status, or lookup specific entity location/history. * `set_relation`: Record/update spatial relationships (on, inside, next_to, above, below, near, contains). * `get_spatial_map`: Export structured spatial layout, topological graph, 3D asset, or high-level summary. * `simulate_movement`: Predict entity trajectory, test for AABB obstacle collisions, or compute navigation waypoints. * `ingest_observation`: Merge perception detections into world model; re-identify entities and reconcile frustum view. * `get_expected_view`: Calculate what entities should be visible from an observer pose and FOV cone. * `link_to_goal`: Associate entities/regions with state-memory task IDs, or extract goal-relevant context slices. * `record_outcome`: Update world model after action execution completes. * `manage_spatial_spec`: Spatial SDD physical contract baseline registration, verification, and listing. * `create_evidence_pack`: Generate cryptographic SHA-256 evidence packages linking spatial state to tasks. * `use_spatial_blackboard`: Multi-agent shared spatial blackboard for publishing intentions and claiming mutex locks. * `manage_snapshot`: Unified spatial snapshot and time-travel management (save, restore, diff, list, undo, history). * `generate_game_inputs`: Generate Playwright MCP automation inputs or project/unproject 3D coordinates and screen pixels. * `wait_for_spatial_state`: Poll and wait until an entity reaches a specific spatial condition. <!-- world-model-mcp:end -->
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Your trail
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Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

