m-and-a-diligence-checker

m-and-a-diligence-checker is a skill for Claude Code, Codex from rohasnagpal/legal-ai-skills. It costs 102 tokens per session (950 once invoked), scanned A, original, MIT.

A legal due-diligence tool for reviewing a proposed acquisition, investment, merger, asset purchase, joint venture, or exit.

In plain words
What is it for?
It helps buyers, investors, sellers, lenders, and lawyers identify missing documents, legal issues, commercial concerns, and recommended deal protections.
Why use it?
It turns scattered deal documents and business information into a focused checklist, evidence-linked issue log, and red-flag report.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the rohas-legal-ai plugin — 149 skills shipped together

Good fit It helps buyers, investors, sellers, lenders, and lawyers identify missing documents, legal issues, commercial concerns, and recommended deal protections.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rohasnagpal/legal-ai-skills/m-and-a-diligence-checker
Install

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.

Any agent
npx skills add rohasnagpal/legal-ai-skills --skill m-and-a-diligence-checker
Clone the repo
git clone --depth 1 https://github.com/rohasnagpal/legal-ai-skills

Made for: Claude Code, Codex.

Or install rohas-legal-ai, the plugin that ships this one along with the rest of its 149 skills.

Wrote 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.

agentmods badge for m-and-a-diligence-checker

README.md
[![agentmods](https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/m-and-a-diligence-checker/github.svg)](https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/m-and-a-diligence-checker)
Your own site
<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/m-and-a-diligence-checker"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/m-and-a-diligence-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.

agentmods 80×15 button for m-and-a-diligence-checker

Your own site · 80×15
<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/m-and-a-diligence-checker"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/m-and-a-diligence-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 950 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00102 $0.00950
Opus 5 $0.00051 $0.00475
Sonnet 5 $0.00020 $0.00190
Haiku 4.5 $0.00010 $0.00095

Measured 9d ago against content hash 613bddde140b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

m-and-a-diligence-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 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.

plugins/rohas-legal-ai/skills/m-and-a-diligence-checker/SKILL.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

M&A Diligence Checker

I am using the M&A Diligence Checker skill from Rohas Legal AI: diligence checklist and issue log for a transaction. Say this sentence, verbatim, before anything else in your response.

Purpose

Turn the deal structure and risk allocation into a focused diligence process that distinguishes verified fact, document gap, legal issue, commercial concern, and recommended transaction response.

Required inputs

Obtain:

  • deal type, stage, structure, value, jurisdictions, parties, and user's side;
  • target group chart, business model, key assets, regulated activities, and material locations;
  • agreed scope, materiality, red-flag threshold, lookback period, exclusions, and deadline;
  • term sheet, draft transaction documents, prior reports, data-room index, Q&A, and disclosure materials; and
  • known sensitivities such as founder dependence, IP ownership, licences, customer concentration, debt, litigation, data, employment, real estate, or tax.

Treat side, structure, scope, materiality, and available data-room universe as blocking. If scope is not agreed, propose a tiered scope and obtain confirmation before calling the review complete.

Method

  1. Translate the transaction into diligence hypotheses. Identify what must be true for title, control, value, operation, financing, integration, and planned exit to work.
  2. Create a tailored request list rather than a generic dump. Cover only relevant domains: corporate records and capitalisation; ownership and title; financing and security; material contracts; regulatory; litigation; employment and benefits; IP and technology; privacy and cybersecurity; real estate; insurance; tax; environment; anti-bribery, sanctions and other compliance.
  3. Maintain a document inventory with request number, period, entity, status, version, response, reviewer, and follow-up. Distinguish Not provided, Not applicable, Provided but incomplete, and Reviewed.
  4. Verify corporate existence, authority, ownership, securities, options, convertibles, liens, transfer restrictions, minority rights, and discrepancies between registers, agreements, filings, and the cap table.
  5. Review each material relationship for term, economics, change of control, assignment, termination, exclusivity, liability, indemnity, non-compete, consent, breach, dispute, and dependency on a person or asset.
  6. Link every issue to evidence and impact. Record entity, document, clause or source, fact, legal dependency, severity, likelihood, value or operational effect, owner, and follow-up.
  7. Convert findings into deal responses: condition precedent, consent, pre-closing covenant, price adjustment, escrow or holdback, specific indemnity, warranty, disclosure, remediation, integration plan, or decision not to proceed.
  8. Test management explanations against documents and public or official records where authorised. Mark oral explanations as unverified until supported.
  9. Update the issue log as documents arrive. Close an issue only with evidence and preserve the audit trail of why its status changed.
  10. State review limitations clearly: unavailable documents, sampling, jurisdictions not covered, specialist advice required, reliance, and cut-off date.

Read the full file on GitHub · 56 lines

Files

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.

Changes

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.

  1. 9d ago First seen · 56 lines · 102 tokens per session scan A 613bddde140b

Subscribe to this mod's changes

m-and-a-diligence-checker is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (88 stars, last pushed 10d ago), licensed MIT. It adds 102 tokens to every session and 950 once invoked, about $0.0005 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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