Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
VectorSpaceLab/AREX-Skill3392026년 9월 3일 업데이트
무료GitHub에 공개
cognee
Routes Cognee AI memory platform tasks across SDK memory APIs, graph/RAG retrieval, configuration, custom pipelines, session memory, CLI, API, MCP, and deployment workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
연동 도구Docker
설치 방법 보기포함된 파일(38)
- SKILL.md3.7 KB
- references/package-overview.md2.9 KB
- references/repo-provenance.md2.1 KB
- references/repo-routing-metadata.json479 B
- references/troubleshooting.md2.3 KB
- scripts/check_install.py3.2 KB
- sub-skills/advanced-graphs-pipelines/references/custom-graphs-pipelines.md3.2 KB
- sub-skills/advanced-graphs-pipelines/references/migration-visualization.md2.4 KB
- sub-skills/advanced-graphs-pipelines/references/troubleshooting.md2.1 KB
- sub-skills/advanced-graphs-pipelines/scripts/inspect_custom_model.py2.4 KB
- sub-skills/advanced-graphs-pipelines/SKILL.md2.3 KB
- sub-skills/agent-session-memory/references/agent-session-memory.md3.1 KB
- sub-skills/agent-session-memory/references/api-reference.md2.8 KB
- sub-skills/agent-session-memory/references/troubleshooting.md1.9 KB
- sub-skills/agent-session-memory/scripts/check_agent_memory_payloads.py1.7 KB
- sub-skills/agent-session-memory/SKILL.md2.1 KB
- sub-skills/api-cli-services/references/cli-reference.md5.2 KB
- sub-skills/api-cli-services/references/deployment.md3.3 KB
- sub-skills/api-cli-services/references/services-mcp.md7.6 KB
- sub-skills/api-cli-services/references/troubleshooting.md4.2 KB
- sub-skills/api-cli-services/scripts/check_cli_surface.py4.9 KB
- sub-skills/api-cli-services/scripts/check_mcp_surface.py3.1 KB
- sub-skills/api-cli-services/SKILL.md2.3 KB
- sub-skills/configuration-backends/references/backend-matrix.md4.5 KB
- sub-skills/configuration-backends/references/configuration.md13.5 KB
- sub-skills/configuration-backends/references/troubleshooting.md3.2 KB
- sub-skills/configuration-backends/scripts/check_cognee_environment.py3.8 KB
- sub-skills/configuration-backends/SKILL.md3.2 KB
- sub-skills/core-memory/references/api-reference.md3.1 KB
- sub-skills/core-memory/references/troubleshooting.md1.9 KB
- sub-skills/core-memory/references/workflows.md2.9 KB
- sub-skills/core-memory/scripts/cognee_memory_smoke.py1.2 KB
- sub-skills/core-memory/SKILL.md2.4 KB
- sub-skills/search-retrieval/references/api-reference.md3.2 KB
- sub-skills/search-retrieval/references/search-modes.md2.6 KB
- sub-skills/search-retrieval/references/troubleshooting.md1.9 KB
- sub-skills/search-retrieval/scripts/choose_search_mode.py2.3 KB
- sub-skills/search-retrieval/SKILL.md2.2 KB
SKILL.md(원문)
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Cognee Repo Skill
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.
리뷰
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
댓글
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
같은 저장소의 스킬
3ddfa
무료Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
VectorSpaceLab/AREX-Skill3392026년 9월 3일 업데이트
3ddfa-v2
무료Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
VectorSpaceLab/AREX-Skill3392026년 9월 3일 업데이트
ab3dmot
무료Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
VectorSpaceLab/AREX-Skill3392026년 9월 3일 업데이트
Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
VectorSpaceLab/AREX-Skill3392026년 9월 3일 업데이트
acme
무료Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
VectorSpaceLab/AREX-Skill3392026년 9월 3일 업데이트