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.
Adopted by
Most recently taken up by
- ddehart/claude-code-pluginstheir own version, first seen Nov 8, 2026
- debjan/knowledge-graphtheir own version, first seen Nov 6, 2026
- nikhilw/structured-agentic-workflowtheir own version, first seen Nov 6, 2026
- digitalgym/aipathway-standardstheir own version, first seen Nov 4, 2026
- AsiaOstrich/universal-dev-standardsword for word, first seen Nov 4, 2026
- Happy-Technologies-LLC/happy-platform-skillstheir own version, first seen Nov 1, 2026
Other versions23 projects use a version of this.
Word for word · 1
- AsiaOstrich/universal-dev-standards★ 84100% same
Edited · 0
None found.
Wrote their own version · 22
- llopresto87/Cypress★ 119same name
- Happy-Technologies-LLC/happy-platform-skills★ 41same name
- iagocavalcante/claude-turbo-search★ 16same name
- iuiaoin/agent-skills★ 16same name
- ariaxhan/kernel-claude★ 15same name
- Alexander-Tyagunov/magician★ 14same name
- nikhilw/structured-agentic-workflow★ 7same name
- cirwel/unitares★ 6same name
- urmzd/saige★ 6same name
- Bartosh16/claude-skills★ 3same name
12 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository55 other files it gives its agents.
- AGENTS.mdAGENTS.md
- ac-coverageSkill
- adrSkill
- ai-collaboration-standardsSkill
- ai-friendly-architectureSkill
- ai-instruction-standardsSkill
- api-designSkill
- atddSkill
- auditSkill
- bddSkill
- brainstormSkill
- changelogSkill
- checkinSkill
- ci-cdSkill
- code-reviewSkill
- commitSkill
- contract-testSkill
- databaseSkill
- deploySkill
- methodologySkill
- dev-workflowSkill
- docgenSkill
- documentation-guideSkill
- durableSkill
- e2eSkill
- error-code-guideSkill
- git-workflow-guideSkill
- incidentSkill
- journey-test-assistantSkill
- logging-guideSkill
- metricsSkill
- migrateSkill
- observabilitySkill
- orchestrateSkill
- planSkill
- prSkill
- discoverSkill
- project-structure-guideSkill
- pushSkill
- refactorSkill
- releaseSkill
- requirementSkill
- retrospectiveSkill
- reverseSkill
- runbookSkill
- securitySkill
- scanSkill
- skill-builderSkill
- sloSkill
- spec-deriveSkill
- sddSkill
- sweepSkill
- tddSkill
- coverageSkill
- testing-guideSkill
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
- Very specific: line 54
If degraded mode hit a reading-depth limit, tell the user a graph engine (e.g.
- Distinctive: line 55
If a referenced id was not found, surface it as a dangling reference to fix.
“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.
Files
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:
| 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
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