Knowledge Graph | 知識圖
SkillDocs & knowledge[UDS] Trace impact chains across specs, decisions, and code via a knowledge graph, with a Markdown fallback when no engine is present. Use when: asking what a spec or decision affects, finding which code implements an artifact, tracing dependencies between specs, ADRs, and modules. Not for: plain text search with no spec or decision anchor — use Grep; authoring the spec itself — use /sdd. Keywords: knowledge graph, impact chain, traceability, spec impact, decision graph, 知識圖, 影響鏈, 規格追蹤.
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Then ask your AI: use the Knowledge Graph | 知識圖 skill
What this skill tells your AI
The instructions your AI receives, as published by asiaostrich/universal-dev-standards in skills/knowledge-graph/SKILL.md and read by ahel’s review.
Language: English | 繁體中文
Answer structural questions across specs, decisions, and code — "what is the full impact chain of XSPEC-205?" — using the Knowledge Graph Memory relationship schema. Works with or without a graph engine.
回答橫跨規格、決策與程式碼的結構性問題——「XSPEC-205 的完整影響鏈是什麼?」——依據知識圖記憶標準的關係 schema。有無圖引擎皆可運作。
Implements: XSPEC-237 Phase 5 — knowledge-graph skill (EngramGraph opt-in)
Mode Selection | 模式選擇
Detect which mode to use before answering:
| Condition | Mode |
|---|---|
ENGRAM_URL set, or a local graph engine responds on /health | Service mode (engine) |
| Otherwise | Degraded mode (Markdown) |
Workflow | 工作流程
- Resolve the target — normalise the argument to a canonical id (
XSPEC-205,DEC-062, a function name). - Choose mode — probe for a graph engine (service) else fall back (degraded).
- Service mode (AC-5b) — issue a single multi-hop query and present the returned chain, including cross-domain links (code → spec → decision):
curl -s -X POST "$ENGRAM_URL/graph/impact-analysis" \ -H 'content-type: application/json' \ -d '{"nodeId":"XSPEC-205","maxHops":3}' - Degraded mode (AC-5a) — with no engine, read the target document, follow its
impacts/impacted_by/supersedes/relatedfront-matter and inline[[ref]]links by reading the linked files, and assemble the chain manually (bounded by reading depth). - Present the chain — list the connected Specs and Decisions, the edge type for each hop, and (if present) each node's
confidence, highest first. - State the mode used — always say whether the answer came from the engine or Markdown fallback, so completeness is clear.
Relationship Schema | 關係 schema
See knowledge-graph-memory. Front-matter fields: related, impacts, impacted_by, supersedes, implements. Edge derivation: Decision impacts Spec → IMPACTS; Decision supersedes Decision → SUPERSEDES.
關係欄位與邊推導見知識圖記憶標準。
Next Steps Guidance | 下一步引導
- If degraded mode hit a reading-depth limit, tell the user a graph engine (e.g. EngramGraph) would give a complete chain, and how to set
ENGRAM_URL. - If a referenced id was not found, surface it as a dangling reference to fix.
- Offer to add missing
impacts/impacted_byfront-matter to the documents you traversed.
Reference | 參考
- Standard: core/knowledge-graph-memory.md
- Engine (opt-in): EngramGraph —
engramgraph - Detailed guide: guide.md
Signals
- GitHub stars
- 73
- Forks
- 13
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
knowledge-graph- Source
- github.com/asiaostrich/universal-dev-standards