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 LegalQuants/lq-ai --skill nda-reviewgit clone --depth 1 https://github.com/LegalQuants/lq-aiWrote 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/legalquants/lq-ai/nda-review)<a href="https://agentmods.dev/skills/legalquants/lq-ai/nda-review"><img src="https://agentmods.dev/badge/skills/legalquants/lq-ai/nda-review/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/legalquants/lq-ai/nda-review"><img src="https://agentmods.dev/badge/skills/legalquants/lq-ai/nda-review.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 | $0.00079 | $0.03523 |
| Opus 5 | $0.00039 | $0.01761 |
| Sonnet 5 | $0.00016 | $0.00705 |
| Haiku 4.5 | $0.00008 | $0.00352 |
Grade A, and why
nda-review 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NDA Review
Conduct a structured review of a non-disclosure agreement from the user's stated perspective and produce a report that an in-house lawyer can act on without redoing the analysis. The output is a draft for human review, not a final word; treat it accordingly.
When this skill applies
Apply when the user provides an NDA (sometimes called a confidentiality agreement, CDA, or confidential disclosure agreement) and asks for review, redline guidance, risk assessment, or a recommendation. The user's perspective — discloser, recipient, or mutual — fundamentally changes the analysis; require it before proceeding if not supplied.
Do not apply this skill to:
- Confidentiality clauses inside larger agreements (MSAs, employment agreements, settlement agreements). Those clauses interact with the surrounding agreement; isolated review misleads. Tell the user a separate review of the parent agreement is needed.
- Documents that are not NDAs, even if they touch on confidentiality (data processing agreements, security addenda, BAAs). Refer the user to the appropriate skill.
- NDAs in employment contexts (employee confidentiality agreements, separation agreements with NDA components). These have employment-law overlays this skill does not cover.
Inputs
The skill requires the NDA itself and the user's perspective. If perspective is not provided, ask:
"Before I review, which side are you on? Discloser (you're sharing information and want strong protections on the recipient), recipient (you're receiving information and want narrow obligations on yourself), or mutual (both parties are exchanging information and you want balanced, symmetric terms)?"
If the user describes a situation that does not cleanly fit one of these (e.g., "we're sharing information but only a small amount; mostly we're receiving"), default to the perspective covering the larger exposure and note the asymmetry in the report. For mostly-receiving-with-some-sharing, treat as recipient and add a note about the discloser-side exposure.
What ships with it
7 files 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 · 212 lines · 79 tokens per session scan A 32bdabc4a8ec
nda-review is a skill published in the GitHub repository LegalQuants/lq-ai (136 stars, last pushed yesterday), licensed Apache-2.0. It adds 79 tokens to every session and 3,523 once invoked, about $0.0004 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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