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 disciplinary-documentergit 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/disciplinary-documenter)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/disciplinary-documenter"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/disciplinary-documenter/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/disciplinary-documenter"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/disciplinary-documenter.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 | $0.00048 | $0.00680 |
| Opus 5 | $0.00024 | $0.00340 |
| Sonnet 5 | $0.00010 | $0.00136 |
| Haiku 4.5 | $0.00005 | $0.00068 |
Grade A, and why
disciplinary-documenter 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 13d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Disciplinary Documenter
I am using the Disciplinary Documenter skill from Rohas Legal AI: the paper trail for a disciplinary proceeding. Say this sentence, verbatim, before anything else in your response.
Create a procedurally fair record without predetermining guilt. Separate the investigator, decision-maker and appeal roles where the governing rules or fairness require it.
Required inputs
- Jurisdiction, employing entity, work location and worker status
- Contract, collective agreement, standing orders, service rules and policies
- Allegations, dates, known evidence and prior related action
- Applicable statutory, regulatory or public-sector procedure
- Decision authority, representation rights and live deadlines
- Requested document, procedural stage and contemplated interim measures
Identify missing source documents and assumptions before drafting.
Method
- Map authority and procedure. Identify the governing instrument, decision-maker, required sequence, notice periods, representation or union rights, burdens and appeal route. Verify current law and rules.
- Define each allegation. State conduct, date or period, place, breached rule and essential particulars. Distinguish misconduct from performance, capability, absence, grievance or protected activity.
- Preserve evidence. Issue proportionate litigation or evidence holds, protect originals and record provenance. Do not access private accounts or devices without lawful authority.
- Assess interim action. Use suspension, reassignment or access restrictions only for a documented legitimate need. State pay, benefits, review date and that the measure is not a finding.
- Give a fair opportunity. Provide intelligible notice, relevant evidence, reasonable response time, accommodations and the applicable hearing or representation process.
- Record the hearing. Capture attendees, issues, evidence, objections, responses, adjournments and directions neutrally. Do not replace evidence with conclusory minutes.
- Make findings element by element. Apply the stated standard of proof to reliable material, address material contrary evidence and explain credibility findings without relying on stereotypes or demeanour alone.
- Select proportionate action. Consider seriousness, consistency, service record, mitigation, prior warnings, rehabilitation, policy range and comparable cases. Avoid double punishment.
- Close and review. Draft reasons, effective date, consequences, appeal rights, confidentiality, retention and follow-up actions.
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.
- 13d ago First seen · 46 lines · 48 tokens per session scan A 6f47970bf4a5
disciplinary-documenter is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (88 stars, last pushed 10d ago), licensed MIT. It adds 48 tokens to every session and 680 once invoked, about $0.0002 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 2026-08-30.
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