Official agent skill

Diligence Issue Extraction

by anthropics in anthropics/claude-for-legal

Read VDR documents and extract issues per house categories and materiality thresholds, producing findings in house memo format.

OfficialApache-2.0Auto-check passedBusiness, Finance & HR

Install Diligence Issue Extraction

skills CLI
$ npx skills add anthropics/claude-for-legal --skill diligence-issue-extraction -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install anthropics/claude-for-legal diligence-issue-extraction --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/anthropics/claude-for-legal.git skills-src && mkdir -p .claude/skills && cp -r skills-src/corporate-legal/skills/diligence-issue-extraction .claude/skills/diligence-issue-extraction && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
diligence-issue-extraction
GitHub stars
9.6k
Used in
2 other repos
Token cost
~3.3k tokens
SKILL.md length
1,453 words
Files
1
Skills in repo
147
Repo updated
First seen
Licence
Apache-2.0

At a glance

Read VDR documents and extract issues per house categories and materiality thresholds, producing findings in house memo format.

  • Works in 5 steps: Inventory the VDR → Apply materiality filter → Extract issues → …
  • User says review the data room
  • SKILL.md covers Matter context, Purpose, Load context and Workflow, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Diligence Issue Extraction is an agent skill from anthropics/claude-for-legal, published by the product's own GitHub organization. Read VDR documents and extract issues per house categories and materiality thresholds, producing findings in house memo format. Use when user says "review the data room", "extract issues from [folder]", "diligence review", "what's in the VDR", or points at VDR documents.

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Fundraising and pitch decks. The repository describes itself as: A suite of plugins for legal workflows. The licence is Apache-2.0.

When your agent uses it

  • User says review the data room
  • Extract issues from [folder]
  • Diligence review
  • Whats in the VDR

Example prompts

  • “review the data room”
  • “extract issues from [folder]”
  • “diligence review”
  • “/diligence-issue-extraction”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Inventory the VDR
  2. Apply materiality filter
  3. Extract issues
  4. State each finding
  5. Assemble per category

What it can do on your machine

Read from SKILL.md and the folder at commit 4a6c651. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Diligence Issue Extraction loads about 3.3k tokens when it runs. Until then it costs about 75 tokens; SKILL.md has 1,453 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~75
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from anthropics/claude-for-legal at commit 4a6c651, republished under its Apache-2.0 licence (© anthropics). 1,453 words, ~3,285 tokens.

Download SKILL.mdSave it as .claude/skills/diligence-issue-extraction/SKILL.md (or your agent's skills folder).
name
diligence-issue-extraction
description
Read VDR documents and extract issues per house categories and materiality thresholds, producing findings in house memo format. Use when user says "review the data room", "extract issues from [folder]", "diligence review", "what's in the VDR", or points at VDR documents.
argument-hint
[VDR folder path or category name]

/diligence-issue-extraction

  1. Load ~/.claude/plugins/config/claude-for-legal/corporate-legal/CLAUDE.md + ~/.claude/plugins/config/claude-for-legal/corporate-legal/deals/[code]/deal-context.md.
  2. Use the workflow below.
  3. Check ai-tool-handoff — if category is bulk and tool is configured, hand off first.
  4. Read docs, apply materiality filter, extract per category.
  5. Findings in house memo format. Hand off consents to closing checklist.

Matter context

Matter context. Check ## Matter workspaces in the practice-level CLAUDE.md. If Enabled is ✗ (the default for in-house users), skip the rest of this paragraph — skills use practice-level context and the matter machinery is invisible. If enabled and there is no active matter, ask: "Which matter is this for? Run /corporate-legal:matter-workspace switch <slug> or say practice-level." Load the active matter's matter.md for matter-specific context and overrides. Write outputs to the matter folder at ~/.claude/plugins/config/claude-for-legal/corporate-legal/matters/<matter-slug>/. Never read another matter's files unless Cross-matter context is on.


Purpose

The VDR has 2,000 documents. Somewhere in there are the 30 that matter for the deal. This skill reads documents against the diligence categories and materiality thresholds from ~/.claude/plugins/config/claude-for-legal/corporate-legal/CLAUDE.md, extracts issues, and writes them in house memo format.

Load context

  • ~/.claude/plugins/config/claude-for-legal/corporate-legal/CLAUDE.md → Diligence structure (categories, materiality thresholds)
  • ~/.claude/plugins/config/claude-for-legal/corporate-legal/CLAUDE.md → Issues memo format (how findings are stated)
  • ~/.claude/plugins/config/claude-for-legal/corporate-legal/deals/[code]/deal-context.md → deal-specific thresholds, VDR location

If deal-context.md doesn't exist, ask which deal this is for.

Workflow

Step 1: Inventory the VDR

If VDR MCP (Box/Intralinks/Datasite) is connected, pull the index. Map VDR folders to diligence request list categories. Note gaps — request list categories with no corresponding VDR content.

markdown
## VDR Inventory: [Deal code]

| Request category | VDR folder | Docs | Status |
|---|---|---|---|
| Corporate & Organizational | /01-Corporate | 45 | Reviewed |
| Material Contracts | /02-Contracts | 312 | In progress |
| IP | /03-IP | 89 | Not started |
| [etc.] | | | |

**Gaps:** [Request categories with no VDR content — follow-up request needed]
Step 2: Apply materiality filter

Per ~/.claude/plugins/config/claude-for-legal/corporate-legal/CLAUDE.md / deal-context thresholds. Don't review everything if the threshold says contracts >$X.

For contracts specifically: sort by stated value (if in filename/metadata) or by counterparty significance. Review top-down until you hit the threshold or the category is exhausted.

Step 3: Extract issues

For each document read, check against the standard diligence concerns for its category:

Material contracts — standard extraction set:

  • Change of control provision (triggered by this deal? consent required?)
  • Assignment restriction (can the contract move to buyer?)
  • Exclusivity / non-compete (restricts buyer's business?)
  • MFN (most favored nation — pricing constraints)
  • Termination rights (can counterparty walk because of the deal?)
  • Unusual indemnities or liability exposure

Corporate — standard extraction set:

  • Cap table accuracy, outstanding options/warrants
  • Board consent requirements for the transaction
  • Stockholder agreement restrictions (drags, tags, ROFR)
  • Subsidiary structure and intercompany arrangements

IP — standard extraction set:

  • Ownership chain (assignments from founders/employees in place?)
  • Open source in the product (copyleft risk)
  • Key IP licensed vs. owned
  • Pending or threatened IP litigation

Employment — standard extraction set:

  • Change-of-control severance triggers (parachute cost)
  • Key employee retention risk
  • Pending employment litigation
  • Classification risk (contractors who look like employees)

Litigation — standard extraction set:

  • Pending matters and reserves
  • Threatened claims
  • Regulatory inquiries
  • Pattern litigation (consumer class actions, etc.)
Step 4: State each finding

Source attribution. Where a finding references a statute, regulation, case, or regulator action — e.g., a change-of-control provision analyzed under an applicable law, an IP ownership gap cited against a specific doctrine, a pending litigation matter with a case citation — tag the citation with where it came from: [Westlaw], [CourtListener], or the MCP tool name for citations retrieved from a legal research connector; [web search — verify] for web-search citations; [model knowledge — verify] for citations recalled from training data; [user provided] for citations from the VDR, deal-team memos, or outside-counsel feedback. Document-source citations (VDR path, Bates, filename) retain their native reference. Citations tagged verify carry higher fabrication risk and should be checked first. Never strip or collapse the tags.

When disagreeing with a user's cited statute, quote the text or decline to characterize it. If the user (or a deal-team note, or a sell-side disclosure) cites a statute for a proposition you don't think is correct, and you don't have the statute text available from a connected research tool or the VDR, do not invent a description of what the statute says. Say instead: "That section doesn't match what I'd expect a [bulk-sales notice / successor-liability / whatever] requirement to say — I'd need to pull the actual text to tell you what it actually covers. [statute unretrieved — verify]" Then either (a) retrieve the text via the configured research tool and quote it, (b) ask the user to paste the text, or (c) flag for outside counsel. A confident wrong description of a real statute is worse than "I don't know" — a deal-team memo citing a fabricated subchapter is harder to un-believe than a gap. Applies in every skill that characterizes a statute, not just issue extraction.

No silent supplement. If a research query to the configured legal research tool returns few or no results for a legal basis the finding needs (e.g., the rule governing a change-of-control consent requirement, an IP assignment doctrine, an employment classification test), report what was found and stop. Do NOT fill the gap from web search or model knowledge without asking. Say: "The search returned [N] results from [tool]. Coverage appears thin for [rule / doctrine]. Options: (1) broaden the search query, (2) try a different research tool, (3) search the web — results will be tagged [web search — verify] and should be checked against a primary source before relying, or (4) flag as unverified and stop. Which would you like?" A lawyer decides whether to accept lower-confidence sources.

Per the finding template in ~/.claude/plugins/config/claude-for-legal/corporate-legal/CLAUDE.md. If the seed memo used this:

Issue #N: [Title]
Category: [request list category]
Severity: [level per house scheme]
Documents: [VDR path + doc name]
Finding: [what the document says and why it matters]
Recommendation: [price adjustment / indemnity / consent required / rep & warranty / walk]

...then use exactly that. If the seed memo was bullets, write bullets.

Severity calibration (if house scheme is R/Y/G):

  • 🔴 Red: Affects deal value or structure. Change of control requiring major customer consent. Undisclosed material litigation. IP ownership gap.
  • 🟡 Yellow: Needs attention, solvable. Consent required but likely obtainable. Open source requiring remediation. Employment classification risk.
  • 🟢 Green: Noted for file. Consistent with reps. No action needed beyond the rep.
Show full SKILL.md (525 more words)Show less
Step 5: Assemble per category

Group findings by request list category. Within category, sort by severity.

markdown
[WORK-PRODUCT HEADER — per plugin config ## Outputs — differs by role; see `## Who's using this`]

> This output is derived from VDR materials that are privileged, confidential, or both. It inherits the source's privilege and confidentiality status — distribution beyond the privilege circle can waive privilege. Store with the matter's privileged files and make distribution decisions deliberately.

# Diligence Issues: [Deal code] — [Category]

**Documents reviewed:** [N] of [M] in category
**Coverage:** [All | >$X threshold | Top N]
**Findings:** [N]🔴 [N]🟡 [N]🟢

---

### Bottom line

[🔴 N blocking · 🟠 N high · 🟡 N medium] — [the one thing the deal team needs to know]

---

[Each finding in house format]

---

## Gaps

- [Request list item with no responsive document]
- [Document referenced but not in VDR]

Handoffs

  • To ai-tool-handoff: If Luminance/Kira is in use per ~/.claude/plugins/config/claude-for-legal/corporate-legal/CLAUDE.md, hand bulk contract review there. This skill handles the nuanced documents (side letters, amendments, anything the AI tool struggles with).
  • To deal-team-summary: Aggregated findings feed the deal team brief.
  • To material-contract-schedule: Contract-level extractions feed the disclosure schedule.
  • To closing-checklist: Any finding that implies a discrete pre-closing action becomes a checklist item. The handoff is not limited to third-party consents — it also covers:
    • Shareholder vote / other closing action — §280G cleansing votes, required stockholder consents, required board resolutions, appraisal-rights notice periods, conversion mechanics, or any other corporate approval the deal needs to close. Characterize the action, the approval threshold, the statutory or charter source, and the timing constraint.
    • Regulatory filings and approvals — HSR, CFIUS, foreign-investment review, sector-specific approvals flagged during extraction.
    • Consents from counterparties — change-of-control, anti-assignment, MFN-triggering consents.
    • Releases, terminations, or pay-offs — employment releases tied to change-of-control, payoff letters, lien releases.
    • Escrow / holdback mechanics — if extraction surfaces an indemnity escrow, R&W insurance deliverable, or holdback tied to a specific issue. Every finding with a pre-closing action tag should reach closing-checklist, not just the ones labeled "consent." If a finding sits in the gray zone (might need a closing action, might be a post-closing covenant), hand it off with a flag — closing-checklist can drop it if the purchase agreement says otherwise. Under-handoff is a one-way door; over-handoff is corrected in review.

Successor liability. Flag: pending or threatened tort/products-liability claims, environmental matters and cleanup obligations, bulk-sale/fraudulent-transfer exposure (is the seller retaining enough assets to pay its remaining creditors?), seller's post-closing dissolution plan (if seller dissolves, plaintiffs chase the buyer), and whether the purchase agreement has an assumed/excluded-liabilities schedule that actually covers the known exposures. Even in asset deals, the "de facto merger," "mere continuation," and "product line" doctrines can transfer liability — this is the analysis that surprises buy-side clients who think they're buying assets clean.

Batch processing

For large categories (300 contracts), process in batches. After each batch, update the running issues list and flag anything 🔴 immediately — don't wait for the full category to surface a deal-affecting issue.

Close with the next-steps decision tree

End with the next-steps decision tree per CLAUDE.md ## Outputs. Customize the options to what this skill just produced — the five default branches (draft the X, escalate, get more facts, watch and wait, something else) are a starting point, not a lock-in. The tree is the output; the lawyer picks.

If the extraction surfaced more than ~10 issues, or any time the user asks: offer the dashboard (see CLAUDE.md ## Outputs → Dashboard offer for data-heavy outputs). Shape the offer for this output — counts by severity (🔴 / 🟠 / 🟡 / 🟢), counts by house category, and a sortable grid of issues with materiality, category, and VDR source.

What this skill does not do

  • It doesn't make the materiality call on close cases. It applies the threshold; a human decides the borderline.
  • It doesn't negotiate reps and warranties. It produces the findings that inform them.
  • It doesn't replace bulk AI review. For high-volume clause extraction, hand off to Luminance/Kira per ~/.claude/plugins/config/claude-for-legal/corporate-legal/CLAUDE.md. This skill is for the judgment layer.

© anthropics, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in corporate-legal/skills/diligence-issue-extraction of anthropics/claude-for-legal.

Open the folder on GitHubat commit 4a6c651

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in anthropics/claude-for-legal, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Storyline Buildersruthir28/enterprise-ai-skills1481 repos~1.9kAutomated safety check: PassMIT
Startup Pitchferdinandobons/startup-skill1.2k—~6.4kAutomated safety check: PassMIT
Dd SourcingAbilityai/trinity636—~664Automated safety check: PassApache-2.0

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Questions about Diligence Issue Extraction

What does Diligence Issue Extraction do?

Read VDR documents and extract issues per house categories and materiality thresholds, producing findings in house memo format. Diligence Issue Extraction is an agent skill from anthropics/claude-for-legal, published by the product's own GitHub organization. Read VDR documents and extract issues per house categories and materiality thresholds, producing findings in house memo format.

When should I use Diligence Issue Extraction?

Diligence Issue Extraction fits situations like: user says review the data room; extract issues from [folder]; diligence review; whats in the VDR.

How do I install Diligence Issue Extraction in Claude Code?

Run `npx skills add anthropics/claude-for-legal --skill diligence-issue-extraction -a claude-code`. Or copy the skill folder (corporate-legal/skills/diligence-issue-extraction in anthropics/claude-for-legal) into .claude/skills/diligence-issue-extraction in your project. Claude Code loads it when a task matches its description.

How do I install Diligence Issue Extraction in Codex?

Run `npx skills add anthropics/claude-for-legal --skill diligence-issue-extraction -a codex`. Or copy the skill folder (corporate-legal/skills/diligence-issue-extraction in anthropics/claude-for-legal) into .agents/skills/diligence-issue-extraction in your project. Codex loads it when a task matches its description.

Can I use Diligence Issue Extraction in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add anthropics/claude-for-legal --skill diligence-issue-extraction -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/diligence-issue-extraction, .gemini/skills/diligence-issue-extraction, .github/skills/diligence-issue-extraction and .opencode/skills/diligence-issue-extraction in your project.

What does Diligence Issue Extraction need to run?

SKILL.md names no scripts, command-line tools or credentials: Diligence Issue Extraction is instructions for the agent only.

Does Diligence Issue Extraction access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Diligence Issue Extraction safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Diligence Issue Extraction use?

Diligence Issue Extraction is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Diligence Issue Extraction use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Diligence Issue Extraction?

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Who maintains Diligence Issue Extraction?

anthropics (a GitHub organization, an official publisher) maintains it in anthropics/claude-for-legal, which has 9,633 GitHub stars. The repository holds 147 skills in this directory. The repository was last updated on September 29, 2026.

Source: anthropics/claude-for-legal on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.