← ClaudeAtlas

graph-engineeringlisted

Use when work spans multiple components, an unfamiliar codebase needs dependency mapping, impact analysis depends on architecture or constraints, or durable evidence-backed project context must be created or refreshed.
douinc/agent-skills · ★ 1 · AI & Automation · score 72
Install: claude install-skill douinc/agent-skills
# Graph Engineering ## Overview Model a project as evidence-backed knowledge, not a pile of files. Build only the graph needed for the current decision, keep facts separate from inference, and persist only durable knowledge. ## Core Contract 1. Define the question and the smallest useful scope. 2. Inspect existing documentation before source code, tests, configuration, and history. 3. Attach a repository path, symbol, sanitized command result, or commit to every important claim. 4. Classify each claim as `observed`, `inferred`, `proposed`, or `unknown`. 5. Represent relevant entities and connections with the vocabulary in [knowledge-schema.md](references/knowledge-schema.md). 6. Apply [update-policy.md](references/update-policy.md) before changing durable documentation. 7. Report impact, risk, unresolved questions, and the evidence that supports each conclusion. Do not require a graph database, MCP server, external API, or special runtime. A compact Markdown table or diagram is enough when it preserves the required semantics. ## Output Contract Return these sections in order: 1. **Scope** — question, boundaries, and audited revision when available. 2. **Evidence** — strongest sources and any contradictions. 3. **Knowledge map** — relevant nodes and directed relations. 4. **Impact** — affected components, interfaces, constraints, and decisions. 5. **Risks and unknowns** — consequences, missing evidence, and validation needed. 6. **Persistence decision** — no change, up