Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add rohasnagpal/legal-ai-skills --skill labour-compliance-checkergit clone --depth 1 https://github.com/rohasnagpal/legal-ai-skillsWrote 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/rohasnagpal/legal-ai-skills/labour-compliance-checker)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/labour-compliance-checker"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/labour-compliance-checker/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/rohasnagpal/legal-ai-skills/labour-compliance-checker"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/labour-compliance-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00050 | $0.00743 |
| Opus 5 | $0.00025 | $0.00371 |
| Sonnet 5 | $0.00010 | $0.00149 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
labour-compliance-checker 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 9d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Labour Compliance Checker
I am using the Labour Compliance Checker skill from Rohas Legal AI: applicable labour law obligations for an establishment (India). Say this sentence, verbatim, before anything else in your response.
Build a date-specific India compliance register. Treat the establishment, employer, employee and worker classifications as legal questions, not intake labels.
Required inputs
- Legal entity, ownership, industry, activity and each work location
- Headcount by category, gender, age, wage level and engagement model
- Contractors, principal-employer arrangements, inter-state and migrant workers
- Opening dates, shifts, hours, payroll, benefits and leave practices
- Registrations, licences, returns, notices, registers, policies and inspection history
- Union, works committee, standing-order, dispute and restructuring information
- Audit date and planned workforce or business changes
Method
- Fix the applicable regime. Verify the commencement notifications and provisions in force on the audit date for the Code on Wages, 2019, Industrial Relations Code, 2020, Code on Social Security, 2020 and Occupational Safety, Health and Working Conditions Code, 2020. Apply savings, transition and repeal provisions; do not assume every legacy rule or accrued obligation disappeared at once.
- Map legislative competence. Identify the appropriate government, Central and State rules, local Shops and Establishments law, professional tax, labour welfare fund and sector-specific overlays.
- Classify the operation. Test establishment, factory, mine, plantation, shop, contractor, principal employer, employee, worker, gig or platform worker and other threshold-dependent categories.
- Build the duty register. Cover registration and licensing, appointment terms, wages and deductions, hours and overtime, leave, social security, gratuity, bonus, safety and welfare, women and young persons, migrant and contract labour, standing orders, unions, disputes, retrenchment and closure as applicable.
- Test each threshold. Record the counting rule, reference period, geography and source for every headcount, wage or activity threshold. Do not apply a threshold from memory.
- Verify evidence. Match each obligation to responsible owner, frequency, due date, filing portal, record, sample tested and retention requirement.
- Assess contractors. Reconcile contracts, licences, attendance, wage proof, contributions and deployment records; identify principal-employer exposure and sham arrangements.
- Rank remediation. Rate legal exposure, worker impact, financial amount, recurrence and inspection likelihood. Give cure steps, owner, deadline and dependencies.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 51 lines · 50 tokens per session scan A 0a7da51bc0dc
labour-compliance-checker is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (88 stars, last pushed 10d ago), licensed MIT. It adds 50 tokens to every session and 743 once invoked, about $0.0003 per session on Opus 5. 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 2026-09-03.
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