Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
- Updated the example CORTEX_BASE_URL in the setup instructions to use https://q5p64iw9c9.execute-api.us-east-1.amazonaws.com/prod. - No functional or code changes; documentation only.
What This Skill Does
Cortex Memory provides structured long-term memory using a knowledge graph that extracts facts, entities, and relationships from text. It supports cross-session recall with hybrid search combining BM25, semantic, temporal, and graph traversal methods. Use it when native memory search returns noisy or incomplete results.
Unlike flat keyword search, Cortex builds a traversable knowledge graph that tracks how entities relate and how facts change over time, enabling queries that native memory cannot answer.
When to use it
- Recalling decisions made in past coding sessions
- Tracking how team members relate to specific projects
- Finding when a preference or fact changed over time
- Looking up entity relationships like service dependencies
- Storing key context from a productive work session for later retrieval
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: How does the auth service relate to the API gateway?
- 1Check if <cortex_memories> tag is already present in context
- 2If not, construct a factual retrieval query targeting the relationship between auth service and API gateway
- 3Send POST request to /v1/retrieve with query_type factual and full mode for graph traversal
- 4Parse results filtering for relationship edges between the two entities
- 5Present the retrieved relationships to the user
A list of stored facts and graph edges describing how the auth service connects to the API gateway, including any temporal changes
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.