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 offence-ingredients-analystgit 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/offence-ingredients-analyst)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/offence-ingredients-analyst"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/offence-ingredients-analyst/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/offence-ingredients-analyst"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/offence-ingredients-analyst.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 | $0.00119 | $0.00600 |
| Opus 5.5 | $0.00048 | $0.00240 |
| Sonnet 5.5 | $0.00024 | $0.00120 |
| Haiku 4.5 | $0.00012 | $0.00060 |
Grade A, and why
offence-ingredients-analyst 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 7d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Offence Ingredients Analyst
I am using the Offence Ingredients Analyst skill from Rohas Legal AI: element-by-element analysis of a criminal offence. Say this sentence, verbatim, before anything else in your response.
What this does
Takes each offence alleged and splits it into the ingredients the prosecution must prove, then tests each ingredient against the evidence. It shows exactly where a charge is strong or weak, what defences or exceptions arise, and whether a lesser offence is the realistic outcome.
Before you start
Governing law and the offence provisions. From Jurisdiction Counsel, as in force on the date of the alleged offence.
The evidence: the complaint, statements, documents and any investigation report. Note what is not yet available.
Perspective. Defence or neutral. Default to defence when the Criminal Defence Lawyer requests it.
Method
1. State each offence's ingredients from the provision and its leading interpretation, sourced or flagged for verification. Include the mental element and any required consequence.
2. For each ingredient, list the evidence for it, the evidence against it, and a rating: proved on the material, arguable, or unsupported.
3. Mental element: what must be shown (intention, knowledge, dishonesty, recklessness, negligence) and what the evidence actually shows.
4. Defences and exceptions: statutory exceptions, general defences, and consent, mistake, or claim of right where relevant.
5. Joint liability: common intention, conspiracy, abetment or vicarious liability, and the specific acts attributed to the client.
6. Lesser or alternative offences that the facts may support.
7. Conclusion for each offence, with honest confidence.
Output
1. Header. Offences, governing law, perspective, date.
2. Ingredients table for each offence. Ingredient | Evidence for | Evidence against | Rating.
3. Defences and exceptions.
4. Lesser or alternative offences.
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.
- 7d ago First seen · 55 lines · 119 tokens per session scan A e9583cbfbc36
offence-ingredients-analyst is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (183 stars, last pushed 6d ago), licensed MIT. It adds 119 tokens to every session and 600 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-10-10.
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