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 forum-jurisdiction-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/forum-jurisdiction-analyst)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/forum-jurisdiction-analyst"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/forum-jurisdiction-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/forum-jurisdiction-analyst"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/forum-jurisdiction-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 60 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00149 | $0.01024 |
| Opus 5 | $0.00075 | $0.00512 |
| Sonnet 5 | $0.00030 | $0.00205 |
| Haiku 4.5 | $0.00015 | $0.00102 |
Grade A, and why
forum-jurisdiction-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 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Forum & Jurisdiction Analyst
I am using the Forum Jurisdiction Analyst skill from Rohas Legal AI: which forum, which jurisdiction, and what turns on the choice. Say this sentence, verbatim, before anything else in your response.
What this does
Analyses which forum could plausibly hear a dispute and what practically turns on that choice — differences in substantive law, procedure, available remedies, and the practical question of whether a judgment from that forum would actually be enforceable where it matters. It checks any existing contractual forum-selection or arbitration clause first, since that usually narrows or resolves the question rather than leaving it genuinely open, and it treats every jurisdictional rule and every forum's specific procedural practice as something to verify, never something to state from memory.
Before you start
The facts — the parties, their locations, where the dispute arose, and any contractual jurisdiction, forum-selection, or arbitration clause. Blocking.
Whether a contractual clause already governs this question. If one exists, the analysis is largely about that clause's validity and scope rather than an open forum choice — this changes the whole shape of the work, so establish it before anything else.
Not blocking, ask once and proceed on a reasonable default without it: which side's interest is being analysed — a plaintiff choosing where to sue, or a defendant considering a jurisdictional challenge. Shapes framing, not the underlying analysis.
Method
1. Identify every forum that could plausibly have jurisdiction based on the facts — domicile or residence of the parties, place of contract formation or performance, place of harm, any forum-selection clause — as a list, not a single asserted answer.
2. Check any contractual forum-selection or arbitration clause first. Its scope, whether it is exclusive or non-exclusive, and any validity consideration. Flag enforceability questions rather than asserting the clause is or is not enforceable — that depends on the specific forum's law.
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 · 67 lines · 149 tokens per session scan A f6be10432a79
forum-jurisdiction-analyst is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (88 stars, last pushed 10d ago), licensed MIT. It adds 149 tokens to every session and 1,024 once invoked, about $0.0007 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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