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.

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 intentRead
Store, build, recall, improve, or delete memory with SDK callssub-skills/core-memory/SKILL.md
Choose SearchType, tune recall/search, handle empty results or invalid query knobssub-skills/search-retrieval/SKILL.md
Configure LLMs, embeddings, database/storage backends, optional extras, env vars, and pathssub-skills/configuration-backends/SKILL.md
Define custom graph schemas, custom tasks/pipelines, ontology workflows, memify, migration, export, or visualizationsub-skills/advanced-graphs-pipelines/SKILL.md
Use session memory, feedback entries, agent memory decorators, agent identities, or multi-agent isolationsub-skills/agent-session-memory/SKILL.md
Operate Cognee through CLI, FastAPI, MCP, Docker Compose, UI, cloud/local service connection, or push/syncsub-skills/api-cli-services/SKILL.md

Shared references

Operating rules

  • Prefer remember/recall for memory-shaped user requests; prefer add/cognify/search for 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-packages
  • K1binfo
    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