Cognee Repo Skill
SkillDocs & knowledge"Routes Cognee AI memory platform tasks across SDK memory APIs,
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Cognee Repo Skill skill
What this skill tells your AI
The instructions your AI receives, as published by vectorspacelab/arex-skill in skills/repositories/repo-skills/cognee/SKILL.md and read by ahel’s review.
Use this skill when the user asks about Cognee, AI memory, persistent agent memory, graph RAG, Cognee SDK/CLI/API/MCP usage, Cognee configuration, custom graph extraction, session memory, or self-hosted Cognee services.
Cognee is a Python package and service stack for ingesting data, building a graph/vector-backed memory layer, and recalling knowledge for agents.
First checks
For a safe installed-package check:
python scripts/check_install.py --help
python scripts/check_install.py --json
Minimal package install:
python -m pip install "cognee"
python - <<'PY'
import cognee
print(cognee.__version__)
print(cognee.SearchType.GRAPH_COMPLETION)
PY
Do not assume provider credentials or optional databases are configured. Most real ingestion/search workflows need an LLM and embedding provider; backend-specific workflows need matching extras and services.
Route map
| User intent | Read |
|---|---|
| Store, build, recall, improve, or delete memory with SDK calls | sub-skills/core-memory/SKILL.md |
Choose SearchType, tune recall/search, handle empty results or invalid query knobs | sub-skills/search-retrieval/SKILL.md |
| Configure LLMs, embeddings, database/storage backends, optional extras, env vars, and paths | sub-skills/configuration-backends/SKILL.md |
| Define custom graph schemas, custom tasks/pipelines, ontology workflows, memify, migration, export, or visualization | sub-skills/advanced-graphs-pipelines/SKILL.md |
| Use session memory, feedback entries, agent memory decorators, agent identities, or multi-agent isolation | sub-skills/agent-session-memory/SKILL.md |
| Operate Cognee through CLI, FastAPI, MCP, Docker Compose, UI, cloud/local service connection, or push/sync | sub-skills/api-cli-services/SKILL.md |
Shared references
- references/package-overview.md — package identity, public surface, and sub-skill boundaries.
- references/troubleshooting.md — cross-cutting install/import/credential/backend issues.
- references/repo-provenance.md — source snapshot and refresh baseline.
- references/repo-routing-metadata.json — structured router placement used by DisCo repo-skills import tooling.
Operating rules
- Prefer
remember/recallfor memory-shaped user requests; preferadd/cognify/searchfor explicit pipeline control. - Before diagnosing workflow failures, separate three causes: package install, provider credentials, and database/storage backend state.
- Never tell a future agent to open original Cognee docs, examples, notebooks, tests, or scripts. Use the bundled references and scripts in this skill tree.
- Keep real API keys, cloud tokens, local filesystem paths, and service URLs in the user’s runtime configuration, not in copied guidance.
- Treat Docker, MCP, UI, and API servers as long-running services; run only
--help, version, or check scripts unless the user asks to start them. - If a current checkout has changed from the provenance snapshot, refresh this skill before relying on implementation-specific details.
Signals
- GitHub stars
- 266
- Forks
- 21
- Last commit
- Sep 2026
ahel review
K1binfo
installs-packagesK1binfo
installs-packages (in references/package-overview.md)K1binfo
installs-packages (in sub-skills/api-cli-services/references/deployment.md)K1binfo
installs-packages (in sub-skills/configuration-backends/references/configuration.md)
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Catalog kind
- skill
- Gateway key
cognee-vectorspacelab- Source
- github.com/vectorspacelab/arex-skill