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 administrative-action-challenge-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/administrative-action-challenge-analyst)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/administrative-action-challenge-analyst"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/administrative-action-challenge-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/administrative-action-challenge-analyst"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/administrative-action-challenge-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 | $0.00137 | $0.00636 |
| Opus 5.5 | $0.00055 | $0.00254 |
| Sonnet 5.5 | $0.00027 | $0.00127 |
| Haiku 4.5 | $0.00014 | $0.00064 |
Grade A, and why
administrative-action-challenge-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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Administrative Action Challenge Analyst
I am using the Administrative Action Challenge Analyst skill from Rohas Legal AI: grounds and routes to challenge public decisions. Say this sentence, verbatim, before anything else in your response.
What this does
Tests a public body's decision against the grounds on which courts review administrative action, and works out the best route: internal review, a statutory appeal, judicial review or a writ, or a fresh representation. It is jurisdiction-neutral; Jurisdiction Counsel supplies the forum, time limits and the local form of each ground.
Before you start
The decision: the document, its date, the decision-maker, the power relied on, and the date the client received it.
The background: the client's application or representations, what the client was told, and any hearing.
Jurisdiction. From Jurisdiction Counsel: the court with review or writ jurisdiction, time limits, and alternative remedies.
Method
1. Source and limits of power: the statute or rule relied on, conditions for its exercise, and whether the decision-maker had authority.
2. Grounds: test each:
- illegality: acting without or beyond power, misdirection in law, irrelevant considerations, improper purpose;
- procedural unfairness: no notice, no hearing, bias, no reasons where required;
- irrationality or unreasonableness, and proportionality where the law uses it;
- legitimate expectation and consistency;
- rights-based grounds, for constitutional-rights-analyst.
3. Alternative remedies: appeal, revision or review under the statute; whether the court will require them to be used first.
4. Standing, delay and timing.
5. Remedies available: quashing, mandatory or prohibiting orders, declarations, interim relief, and damages where available.
6. Recommend a route with the first step and its deadline.
Output
1. Header. Decision, decision-maker, date, client.
2. Grounds table. Ground | Facts | Strength.
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 · 58 lines · 137 tokens per session scan A e4bd5197256f
administrative-action-challenge-analyst is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (183 stars, last pushed 6d ago), licensed MIT. It adds 137 tokens to every session and 636 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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