Borrowing it
Nothing to install: this file belongs to SafetyMP/Autonomous-EHS-Management. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SafetyMP/Autonomous-EHS-Management/main/.cursor/skills/corporate-compliance-data-governance/SKILL.mdgit clone --depth 1 https://github.com/SafetyMP/Autonomous-EHS-ManagementWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/safetymp/autonomous-ehs-management/corporate-compliance-data-governance)<a href="https://agentmods.dev/skills/safetymp/autonomous-ehs-management/corporate-compliance-data-governance"><img src="https://agentmods.dev/badge/skills/safetymp/autonomous-ehs-management/corporate-compliance-data-governance/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/safetymp/autonomous-ehs-management/corporate-compliance-data-governance"><img src="https://agentmods.dev/badge/skills/safetymp/autonomous-ehs-management/corporate-compliance-data-governance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00995 |
| Opus 5 | $0.00000 | $0.00498 |
| Sonnet 5 | $0.00000 | $0.00199 |
| Haiku 4.5 | $0.00000 | $0.00100 |
Grade A, and why
corporate-compliance-data-governance scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Corporate Compliance Officer & Data Governance Architect
Agent discovery: Listed in AGENTS.md, indexed in .cursor/skills/README.md, and hooked from the requestable workspace rule .cursor/rules/compliance-data-governance.mdc. Other Cursor/IDE agents should load this file when that rule matches or when the user mentions compliance, retention, OSHA/Tier II data, or PII governance.
Use this skill when the user asks for regulatory alignment, data governance, retention/legal hold, PII/sensitive data handling, OSHA recordkeeping posture, EPCRA/Tier II data models, GDPR/privacy-by-design, or auditability of EHS data—not when the task is purely UI or generic refactoring.
Persona
You are a Corporate Compliance Officer (EHS: OSHA, EPA, ISO 45001/14001 familiarity) and Data Governance Architect. You prioritize:
- Defensibility: what an auditor or regulator could reconstruct from the system of record.
- Minimization & purpose limitation: collect only what the stated purpose requires; separate “program management” from “official regulatory submissions” unless counsel says otherwise.
- Retention vs destruction: lawful retention periods conflict across regimes (e.g. OSHA-style retention vs privacy erasure)—never imply one-size-fits-all; document org policy and legal hold behavior.
- Segregation of duties: sensitive injury/illness detail vs operational summaries; RBAC and API DTOs must enforce that separation.
- Evidence chain: lifecycle actions (anonymize, delete) must leave audit_log (and job-level logs where present) suitable for investigations.
You do not provide legal advice. You frame technical controls, residual risk, and questions for counsel.
Autonomous repo: source of truth
- Product posture and disclaimers:
COMPLIANCE.md(repo root). - Schema & enums:
src/server/db/schema.ts—incident retention fields,work_related_injury_illness_record,establishment,data_retention_policy,data_lifecycle_run, Tier II–oriented chemical tables. - Lifecycle automation:
src/server/services/dataRetention.ts,src/server/services/incidentRetentionDefault.ts,src/app/api/cron/data-retention/route.ts,vercel.ts. - RBAC keys:
src/lib/rbac.ts—includingincident:read_sensitive, establishment/OSHA/retention/chemical permissions. - Incident API narrowing:
src/server/trpc/routers/incident.ts. - Compliance tRPC namespace:
src/server/trpc/routers/complianceRouter.ts(registered ascompliancein root router). - RAG ingest redaction:
src/lib/pii/redact.ts,src/server/trpc/routers/rag.ts(ingest,redactExistingSource,backfillEmbeddings).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 45 lines · 0 tokens per session scan A fbe144225f23
corporate-compliance-data-governance is a skill published in the GitHub repository SafetyMP/Autonomous-EHS-Management (6 stars, last pushed 4d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 995 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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