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 consistency-checkergit 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/consistency-checker)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/consistency-checker"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/consistency-checker/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/consistency-checker"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/consistency-checker.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 | $0.00187 | $0.01039 |
| Opus 5 | $0.00093 | $0.00519 |
| Sonnet 5 | $0.00037 | $0.00208 |
| Haiku 4.5 | $0.00019 | $0.00104 |
Grade A, and why
consistency-checker 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Consistency Checker
I am using the Consistency Checker skill from Rohas Legal AI: checks facts, dates, defined terms and figures across a document set. Say this sentence, verbatim, before anything else in your response.
What this does
Checks a document, or a set of documents, for internal consistency: the same fact given the same way everywhere it appears, dates that do not contradict each other or create an impossible sequence, defined terms used the same way throughout, and figures — a price, a quantity, a percentage — that match across every mention. It flags every discrepancy found, states every conflicting version, and does not decide which one is correct; that determination belongs to the user.
Before you start
The document or document set. Ask how many documents are actually in scope if this is not clear — a single long document and a bundle of related documents need the same discipline, but the working map differs.
Not blocking, ask once and proceed on a reasonable default without it: which categories matter most — dates, figures, defined terms, party names. Default to checking all of them unless the user has asked for something narrower.
Method
1. Read every document in the set once before checking anything, building a working map of what is stated where. A discrepancy is often only visible once the whole set is in view; checking document by document in isolation misses contradictions between them.
2. Extract every date mentioned, with what it refers to and where it appears, and check for contradiction — the same event given two different dates, or a sequence of dates that is internally impossible, such as an event dated after a deadline that depended on it.
3. Extract every defined term and check it is used consistently — the same term always referenced the same way, not used in an inconsistent sense in different places, and not conflated with a similar but different term.
4. Extract every figure that appears more than once — a price, a quantity, a percentage — and check all instances match. Where a figure is derived from others, such as a total built from line items, check the arithmetic itself.
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 · 57 lines · 187 tokens per session scan A 77d1deb5f7de
consistency-checker is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (88 stars, last pushed 10d ago), licensed MIT. It adds 187 tokens to every session and 1,039 once invoked, about $0.0009 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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