scope-map
Skill95 starsChanged 6 days agoMITView on GitHub
Maps the audit scope to the standard's clauses and required evidence types with the deterministic clause_map engine. Use when the user says "we have an audit coming", "map the audit scope", "what clauses apply", or when an audit-readiness run begins.
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
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
- Distinctive: line 11
Start of every audit-readiness run.
- Very specific: line 16
Run python3 scripts/clause_map.py --audit audit.json --clauses references/clause-table.json --out mapped.json from this skill's folder, …
- Distinctive: line 21
Every clause row cites the clause table.
- Distinctive: line 23
No readiness opinions here.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Scope Map
Purpose
Deterministic scope-to-clause mapping: which clauses apply, what evidence each requires, how fresh it must be.
When to use
Start of every audit-readiness run.
Inputs
Audit notice (standard, date, scope areas, active roles); clause table reference. Emits the entry hop of mfg.audit-readiness.v1 (schema in contracts/).
Steps
- Extract audit_id, standard, audit_date, scope[], active_roles, clause owners from the notice.
- Run
python3 scripts/clause_map.py --audit audit.json --clauses references/clause-table.json --out mapped.jsonfrom this skill's folder, using workspace paths for the audit input and generated output. - Quote the clause list verbatim.
Output
mapped.json - the {clause_map} hop.
Grounding requirements
Every clause row cites the clause table; scope comes from the audit notice verbatim.
Constraints
- No readiness opinions here; mapping only.
Escalation / uncertainty
Unknown standard or ambiguous scope: ask the audit lead; record in escalations[].
In this repository199 other files it gives its agents.
- .github/copilot-instructions.mdCopilot instructions
- accessibility-passSkill
- acroform-writerSkill
- action-items-todoSkill
- agent-evaluation-designerSkill
- agent-harness-explorerSkill
- agent-performance-triageSkill
- agent-red-teamSkill
- ai-demo-assistantSkill
- ai-first-process-redesignSkill
- ai-usecase-assessmentSkill
- anonymised-case-study-writerSkill
- evidence-gatherSkill
- gap-checkSkill
- readiness-packSkill
- b2b-outreach-suiteSkill
- blog-content-auditorSkill
- blog-post-structure-passSkill
- booth-loop-videoSkill
- brand-template-enforcerSkill
- brand-voice-passSkill
- breathing-roomSkill
- browser-uat-analystSkill
- business-osSkill
- call-for-speakers-digestSkill
- campaign-deck-builderSkill
- chart-builderSkill
- classic-text-adventureSkill
- clipchamp-videoSkill
- clt-hr-assistantSkill
- commenting-contentSkill
- competitive-battlecard-builderSkill
- conditional-chat-reminderSkill
- conference-session-abstract-packSkill
- contradiction-flagSkill
- insight-briefSkill
- provenance-checkSkill
- research-retrieveSkill
- trend-compareSkill
- content-quality-auditorSkill
- copilot-agent-advisorSkill
- copilot-studio-adaptive-card-builderSkill
- copilot-studio-agent-testSkill
- copilot-studio-harness-pickerSkill
- copilot-studio-knowledge-readinessSkill
- copilot-studio-mcp-readinessSkill
- copilot-studio-topic-blueprintSkill
- cowork-plugin-engineerSkill
- cowork-use-case-one-pagerSkill
- create-copilot-adoption-dashboardSkill
- context-assembleSkill
- handoff-packetSkill
- inquiry-intakeSkill
- knowledge-retrieveSkill
- resolution-draftSkill
- doc-format-converterSkill
- bom-impactSkill
- ecn-draftSkill
- ecr-ingestSkill
- standards-checkSkill
- The first 60 shown.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

