NDA Snapshot
SkillDocs & knowledgeLets your agent compare key confidentiality terms across multiple NDAs side by side.
Use NDA Snapshot in Claude, ChatGPT or Ahel Desktop
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Also: Claude Code · Cursor · Codex
Then ask your AI: use the NDA Snapshot skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
About this skill
Use when the user wants to compare the substantive NDA-specific terms across N non-disclosure agreements side-by-side, the definition of Confidential Information, permitted recipients, return/destruction obligation, and remedies clause across each agreement. Returns a row-per-document × column-per-
What this skill tells your AI
The instructions your AI receives, as published by legalquants/lq-ai in skills/nda-snapshot/SKILL.md and read by Ahel’s review.
A reference skill for the M3-C output_format: table mode, tuned for non-disclosure agreement portfolios. Produces a side-by-side grid of NDA-specific terms across N agreements — the in-house lawyer's "compare these NDAs we have with vendors / counterparties / candidates" workflow. Each cell carries a citation back to the source document; failed extractions render as not found rather than confidently-wrong text.
When this skill applies
Apply when the user has a portfolio of NDAs and wants to see how key substantive terms compare across them. Examples:
- "I have NDAs with our top 20 vendors — show me how the definition of Confidential Information varies and where the carveouts are tightest."
- "Compare the return/destruction obligations across these 10 candidate NDAs before we standardize our template."
- "What remedies are available across the 5 mutual NDAs in this M&A diligence box?"
Do not apply this skill to:
- Single-NDA review — use
nda-reviewfor one document at a time. - General contract comparison across mixed types — use
contract-snapshotfor the general Term/Survival/Carveouts/Governing-Law grid. - Free-form Q&A about an NDA — that's the regular Chat surface.
Pairing with the synthetic corpus
This skill ships paired with the synthetic NDA corpus in docs/quickstart/sample-ndas/ (5 mutual NDAs with varying terms). Operators trying LQ.AI for the first time can attach those 5 PDFs to a Knowledge Base and run this skill to see the tabular workflow end-to-end without committing real documents to the system.
Fork-and-tune notes
The four columns here are deliberately NDA-specific — they don't overlap with the general contract-snapshot columns (Term, Survival, Carveouts, Governing Law). Operators who want both can run the two skills in sequence, or fork this skill and add a Term/Governing-Law column for a combined view.
When forking for your own NDA template / counterparty patterns, common modifications include:
- Adding a Term column if you care about NDA duration (often 2–5 years).
- Adding a Notice of Compelled Disclosure column if you negotiate that provision frequently.
- Replacing the Permitted Recipients column with a narrower Affiliate Permission column if your business has a specific affiliate-sharing pattern.
- Bumping
minimum_inference_tierto 3 on all columns if you need higher-fidelity extraction for high-stakes deals.
The four columns chosen here reflect the questions a junior associate or paralegal would most often be asked to extract during NDA portfolio review — they are the highest-frequency, highest-value comparison points across typical mutual-NDA practice.
Output expectations
For each document × column cell:
- A quoted phrase or short paragraph from the source document, anchored by character offsets to enable the citation modal.
- A brief plain-language summary when the operative clause is long or convoluted.
not foundwhen the requested term is genuinely absent from the document (not when extraction failed — those surface as a parse error in the cell footer).
Signals
- GitHub stars
- 149
- Forks
- 62
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
nda-snapshot- Source
- github.com/legalquants/lq-ai
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