fastapi-clean-architecture
FastAPI and clean architecture study assistant backed by a public-safe ontology and knowledge graph extracted from verified OCR notes.
Skill by munlucky
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/munlucky-fastapi-clean-architecture
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: backend, productivity, agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/fastapi-clean-architecture
What's inside
- Skill name
fastapi-clean-architecture- Description
- FastAPI and clean architecture study assistant backed by a public-safe ontology and knowledge graph extracted from verified OCR notes. Use when Codex needs to explain or connect concepts such as FastAPI, APIRouter, Depends, Pydantic schemas, repository pattern, service layer, dependency inversion, SQLAlchemy, Alembic, JWT login, authentication/authorization, CRUD, or the book-specific TIL service architecture without loading the full OCR source text.
- License
- MIT
- Instructions
- 37 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (15)
- .gitignore
- SKILL.md
- openai.yaml · agents/
- chunks.jsonl · references/
- coverage_matrix.jsonl · references/
- edges.jsonl · references/
- graph_manifest.json · references/
- nodes.jsonl · references/
- ontology.yaml · references/
- query_qa.jsonl · references/
- expand_context.py · scripts/
- prepare_private_source.py · scripts/
- query_graph.py · scripts/
- query_knowledge.py · scripts/
- validate_graph.py · scripts/
SKILL.md (first lines)
# FastAPI Clean Architecture ## Overview Use this skill to answer FastAPI and clean architecture questions from the bundled ontology graph. The tracked references are public-safe summaries only; never infer that the full OCR text is bundled in the skill. ## Workflow 1. Start with `references/graph_manifest.json` to check graph version, source quality gates, and counts. 2. Use `scripts/query_graph.py --q "<question>" --json` to find matching nodes, chunks, and relations. 3. Use `scripts/expand_context.py --q "<question>" --out <path>` when a compact source pack is useful before answering or drafting code guidance. 4. Load `references/ontology.yaml` only when the user asks about schema, graph construction, or relation semantics. 5. Treat `source_refs` as provenance pointers, not as permission to quote the original book. Keep answers in Korean by default and preserve code identifiers exactly. ## Boundaries - Do not claim the bundled graph is a full book transcription. - Do not expose private OCR source paths unless the user is working locally and explicitly needs source diagnostics. - Do not quote long passages from OCR source text. Use short paraphrases and cite graph node IDs or source refs. - Keep `moonshotnote-ocr` responsible for OCR extraction and visual review. This skill consumes verified OCR artifacts and graph references. ## Resources - `references/nodes.jsonl`: public-safe graph nodes. - `references/edges.jsonl`: public-safe relations between nodes. - `references/chunks.jsonl`: public-safe topic chunks with source refs. - `references/ontology.yaml`: node types, relation labels, and required fields. - `scripts/query_graph.py`: keyword graph lookup. - `scripts/expand_context.py`: source-pack writer. - `scripts/validate_graph.py`: schema, provenance, and public-safety validator. - `scripts/prepare_private_source.py`: local-only helper that records absolute OCR source metadata under ignored `output/private-source/`. ## Answering Rules When answering implementation questions, connect the relevant graph concepts first, then provide pragmatic code guidance. If the graph has weak coverage for a question, say that the bundled v1 graph is core-structure only and continue from general FastAPI knowledge with that limitation stated.
From munlucky/moonshotnote-skills, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jun 8, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/munlucky/moonshotnote-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
fastapi-clean-architecture skill. Agent Mart. https://agentmart.dev/skills/munlucky-fastapi-clean-architecture (last updated 2026-10-24)