MSA Snapshot
SkillDocs & knowledgeLets your agent compare key commercial terms across multiple master service agreements in a side-by-side table.
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Also: Claude Code · Cursor · Codex
Then ask your AI: use the MSA Snapshot skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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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 commercial terms across N master services agreements side-by-side, term and renewal, payment terms, limitation of liability, and indemnification posture across each agreement. Returns a row-per-document × column-per-question grid with citations per
What this skill tells your AI
The instructions your AI receives, as published by legalquants/lq-ai in skills/msa-snapshot/SKILL.md and read by Ahel’s review.
A reference skill for the M3-C output_format: table mode, tuned for master services agreement portfolios. Produces a side-by-side grid of MSA-specific commercial terms across N agreements — the in-house lawyer's "compare these vendor MSAs" or "diligence these target MSAs" 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 MSAs and wants to see how key commercial terms compare across them. Examples:
- "Pull liability caps, indemnification, and payment terms across these 8 vendor MSAs before our renewal cycle."
- "For this acquisition diligence, show me the renewal trigger and termination posture across the target's top 15 MSAs."
- "Compare the liability carveouts across our SaaS MSAs vs. our commercial-purchase MSAs."
Do not apply this skill to:
- Single-MSA review — use
msa-review-saasormsa-review-commercial-purchasefor one document at a time. - General contract comparison across mixed types — use
contract-snapshotfor the general Term/Survival/Carveouts/Governing-Law grid. - NDA portfolios — use
nda-snapshotfor NDA-specific columns (Confidential Information definition, permitted recipients, etc.).
Pairing with the synthetic corpus
This skill ships paired with the synthetic MSA corpus in docs/quickstart/sample-msas/ (5 MSAs with varying commercial 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 cover the highest-frequency MSA comparison questions for in-house counsel doing portfolio review or diligence. They do not overlap with the general contract-snapshot columns (Term, Survival, Carveouts, Governing Law) — operators wanting both can run the two skills in sequence.
When forking for your own MSA template / counterparty patterns, common modifications include:
- Adding a Termination for Convenience column if your business cares about exit flexibility (notice period + fee structure).
- Adding a SLA / Service Levels column for SaaS-heavy MSA portfolios (credit structure + measurement period).
- Adding a Data Processing column if you need to compare DPA references and data-residency commitments across vendors.
- Replacing the Indemnification column with a narrower IP Indemnification column if that is the only indemnification scope you care about.
- Bumping
minimum_inference_tierto 3 on all columns for high-stakes diligence work.
The Limitation of Liability and Indemnification columns default to minimum_inference_tier: 3 because these clauses are dense, fragmented across the document, and most prone to silent extraction errors. The carveouts in particular are the most-negotiated piece of an MSA — surfacing them inaccurately is worse than surfacing them not-at-all.
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 spans multiple paragraphs.
- An explicit "one-way (vendor-favorable)" / "one-way (customer-favorable)" / "mutual" tag where the column asks about directionality (e.g., Indemnification).
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
msa-snapshot- Source
- github.com/legalquants/lq-ai
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