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 posh-compliance-advisorgit 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/posh-compliance-advisor)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/posh-compliance-advisor"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/posh-compliance-advisor/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/posh-compliance-advisor"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/posh-compliance-advisor.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 | $0.00051 | $0.00722 |
| Opus 5 | $0.00026 | $0.00361 |
| Sonnet 5 | $0.00010 | $0.00144 |
| Haiku 4.5 | $0.00005 | $0.00072 |
Grade A, and why
posh-compliance-advisor 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
POSH Compliance Advisor
I am using the POSH Compliance Advisor skill from Rohas Legal AI: POSH committee, procedure and reporting obligations (India). Say this sentence, verbatim, before anything else in your response.
Assess employer and Internal Committee compliance without directing the outcome of a live complaint. Preserve statutory confidentiality and natural justice from intake through implementation.
Required inputs
- Employer entities, each workplace, headcount and locations
- Internal Committee orders, member details, tenure and external-member credentials
- Policy, displayed notices, training records and reporting channels
- Complaint log, inquiry tracker, recommendations and implementation records
- Annual reports and employer or District Officer submissions
- Applicable service rules, sector requirements and State or local directions
- Whether a live complaint, safeguarding issue or criminal allegation exists
Use anonymised case identifiers unless identity is necessary for the task.
Method
- Determine coverage. Apply the Sexual Harassment of Women at Workplace (Prevention, Prohibition and Redressal) Act, 2013 and Rules to each workplace. Verify the headcount test for an Internal Committee and identify the Local Committee route where applicable.
- Audit constitution. Check the written constitution order, Presiding Officer, employee members, external member, required representation, qualifications, independence, tenure, vacancies and workplace coverage.
- Audit prevention. Check the policy, display obligations, accessible reporting, awareness programmes, member orientation, capacity building, manager guidance and protection against retaliation.
- Map complaint intake. Record date, limitation, permitted assistance, requested interim measures, conflicts and jurisdiction. Do not reject or decide a complaint during an administrative audit.
- Test process controls. Verify notice, response opportunity, quorum, natural justice, conciliation limits, inquiry timetable, evidence handling, absence procedure, legal-representation restrictions and reasoned recommendations under current law.
- Protect confidentiality. Restrict identities, complaint content, proceedings, recommendations and action information as required. Separate need-to-know case files from aggregate compliance data.
- Audit outcomes. Check implementation, compensation reasoning where applicable, non-retaliation, record retention and appeal information. Do not treat inability to prove an allegation as proof of malice.
- Audit reporting. Reconcile the complaint register with Internal Committee annual reports, employer disclosures and required submissions; verify State or District formats and deadlines.
- Remediate. Rank invalid constitution, expired membership, delayed cases, confidentiality breaches, missing training and reporting gaps with owners and dates.
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 · 47 lines · 51 tokens per session scan A 3e2795c138e4
posh-compliance-advisor is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (88 stars, last pushed 10d ago), licensed MIT. It adds 51 tokens to every session and 722 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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