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 appeal-grounds-draftergit 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/appeal-grounds-drafter)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/appeal-grounds-drafter"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/appeal-grounds-drafter/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/appeal-grounds-drafter"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/appeal-grounds-drafter.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 | $0.00628 |
| Opus 5 | $0.00026 | $0.00314 |
| Sonnet 5 | $0.00010 | $0.00126 |
| Haiku 4.5 | $0.00005 | $0.00063 |
Grade A, and why
appeal-grounds-drafter 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 12d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Appeal Grounds Drafter
I am using the Appeal Grounds Drafter skill from Rohas Legal AI: record-linked grounds, preserved errors, standards of review and relief. Say this sentence, verbatim, before anything else in your response.
Draft grounds that identify an appealable error and its consequence. Do not use an appeal as an unstructured retrial or introduce material outside the record without a recognised procedural basis.
Intake
Obtain the jurisdiction, appellate route, challenged judgment or order, decree, reasons, lower record, pleadings, evidence, transcripts, objections, submissions, issues, dates of decision and service, limitation position, permission or certificate requirements, existing stay, client objective, and relief sought.
Drafting method
- Verify the appeal lies to the proposed forum, who may appeal, whether leave is required, which orders are appealable, and the current filing and service deadline.
- Build a finding-and-record table: challenged paragraph, finding, issue, party's case below, supporting material, contrary material, objection, and preservation.
- Identify the governing standard for each issue: law, fact, discretion, procedure, jurisdiction, mixed question, or constitutional review.
- Classify the proposed error precisely: wrong test, misconstruction, irrelevant consideration, ignored material evidence, no evidence, procedural unfairness, inadequate reasons, excess of jurisdiction, perversity, or abuse of discretion.
- Distinguish an adverse outcome from reversible error. Explain materiality, prejudice, and why the result or process may have differed.
- Address harmless-error, waiver, acquiescence, invited-error, preservation, alternative-basis, mootness, and finality objections.
- Draft one proposition per numbered ground. Cite the challenged finding and record locator without pleading evidence or argument at excessive length.
- Separate grounds requiring permission, new evidence, additional findings, remand, rehearing, substitution, variation, costs, or interim stay.
- Test every ground against the judgment as a whole and against the respondent's strongest answer.
- Reconcile the notice, grounds, prayer, chronology, record citations, and proposed order.
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.
- 12d ago First seen · 60 lines · 51 tokens per session scan A eb417e8a5b64
appeal-grounds-drafter 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 628 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 2026-08-30.
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