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AsiaOstrichAsiaOstrich/EngramGraph/.agents/skills/knowledge-graph/SKILL.md

knowledge-graph

Skill4 starsChanged 28 days agoMITView on GitHub

[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.

  • Sends data out

23 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 19 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If degraded mode hit a reading-depth limit, tell the user a graph engine (e.g.

    line 54
  2. Distinctive:

    If a referenced id was not found, surface it as a dangling reference to fix.

    line 55

“Common” is measured: kept by at least 6 in 10 of the 19 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Knowledge Graph | 知識圖

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:

ConditionMode
ENGRAM_URL set, or a local graph engine responds on /healthService mode (engine)
OtherwiseDegraded mode (Markdown)

Workflow | 工作流程

  1. Resolve the target — normalise the argument to a canonical id (XSPEC-205, DEC-062, a function name).
  2. Choose mode — probe for a graph engine (service) else fall back (degraded).
  3. 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}'
  4. Degraded mode (AC-5a) — with no engine, read the target document, follow its impacts/impacted_by/supersedes/related front-matter and inline [[ref]] links by reading the linked files, and assemble the chain manually (bounded by reading depth).
  5. Present the chain — list the connected Specs and Decisions, the edge type for each hop, and (if present) each node's confidence, highest first.
  6. 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_by front-matter to the documents you traversed.

Reference | 參考

  • Standard: core/knowledge-graph-memory.md
  • Engine (opt-in): EngramGraph — engramgraph
  • Detailed guide: guide.md

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