> Diff a new or changed regulation against current privacy policy and practice — outputs a gap list and a remediation plan with owners and dates. Use when a new reg drops, the user asks "does [regulation] affect us", "gap analysis for [state privacy law]", "compliance check against [reg]", or pastes regulatory text.
npx skills add https://github.com/anthropics/claude-for-legal --skill reg-gap-analysis
~/.claude/plugins/config/claude-for-legal/privacy-legal/CLAUDE.md → privacy policy commitments, regulatory footprint, DSAR systems./privacy-legal:reg-gap-analysis "Colorado Privacy Act"
/privacy-legal:reg-gap-analysis
[paste guidance / reg text]
A state passes a new privacy law. The ICO issues new guidance. The CPPA finalizes regulations. Something moves — and now you need to know what, if anything, you have to change.
This skill diffs the new requirement against what you currently do (per ~/.claude/plugins/config/claude-for-legal/privacy-legal/CLAUDE.md → Privacy policy commitments + the practices documented in PIAs) and produces a gap list with a remediation plan.
Read ~/.claude/plugins/config/claude-for-legal/privacy-legal/CLAUDE.md:
## Privacy policy commitments — what you've publicly promised## Regulatory footprint — what already applies## DSAR process → systems list — what you actually do operationallyIf the regulation doesn't apply to you (wrong jurisdiction, below threshold, different sector), the gap analysis is one line: "Doesn't apply. Here's why: [reason]. No action needed."
Before diffing, answer:
Read the regulation (or summary/guidance). List every substantive requirement as a discrete item:
| # | Requirement | Citation | Category |
|---|---|---|---|
| 1 | [requirement as stated] | [section] | [Notice / Rights / Security / Vendor / Other] |
Categories:
For each requirement:
### [Requirement #N]: [short name]
**Regulation says:** [requirement, quoted or paraphrased]
**We currently:** [what the config CLAUDE.md / privacy policy / practice shows]
**Gap:** [None | Partial | Full]
**If partial/full gap — what's missing:** [specific]
**Effort to close:** [Policy update only | Product change | Vendor renegotiation |
New process]
**Risk of non-compliance:** [regulatory penalty range, enforcement likelihood,
reputational]
Not every gap is equal. Sort by:
Prepend the work-product header from ~/.claude/plugins/config/claude-for-legal/privacy-legal/CLAUDE.md ## Outputs (it differs by user role — see ## Who's using this).
> Research-connector pre-flight. Before emitting the remediation plan, check whether a legal research connector is reachable for this session — Westlaw, an EUR-Lex / regulator-site connector, or any firm-configured research MCP. Collect this into the reviewer note per CLAUDE.md ## Outputs: if no connector returns results in Step 2 or the Common regulation categories research step (or none is configured at run time), record it in the Sources: line of the reviewer note — e.g., not connected — cites from training knowledge; the highest-fabrication items in privacy gap analyses are new state-law effective dates, enforcement-begins dates, and article/section pinpoints — spot-check those first. Per-citation [model knowledge — verify] tags remain inline. Do not emit a standalone banner above the output.
[WORK-PRODUCT HEADER — per plugin config ## Outputs]
## Remediation Plan: [Regulation name]
**Effective date:** [date]
**Enforcement begins:** [date]
### Must-do before enforcement
| Gap | Fix | Owner | Due | Status |
|---|---|---|---|---|
| [gap] | [specific fix] | [name] | [date] | [ ] |
### Should-do (lower risk, not blocking)
[same table]
### Already compliant
[list of requirements where gap = None — useful for the "we're mostly fine" message]
### Accepted gaps (risk-accepted, not fixing)
[if any — with documented rationale and who accepted the risk]
When scoping the delta, it helps to place the new regulation into a rough category and then research the specifics:
For each category relevant to the new regulation, research the currently operative requirements before drafting the gap analysis. Cite primary sources. Verify currency — new state laws come online each legislative session, and regulators issue interpretive guidance that shifts what "compliance" means for a given control. Flag uncertainty for attorney verification rather than assert a rule you haven't confirmed.
> No silent supplement. If a research query to the configured legal research tool (Westlaw, regulator databases, or firm platform) returns few or no results for a regulation, guidance document, or enforcement action, 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 [regime / topic]. 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 the issuing authority before relying, or (4) flag as unverified and stop. Which would you like?" A lawyer decides whether to accept lower-confidence sources.
>
> Source attribution tiering. Tag every citation in the gap analysis with its source. For model-knowledge citations, use one of three tiers rather than a single blanket "verify" tag:
>
> - [settled] — stable, well-known statutory and regulatory references unlikely to have changed (e.g., GDPR Art. 33, CCPA § 1798.100, FTC Act § 5). Still verify before filing, but lower priority.
> - [verify] — model-knowledge citations that are real but should be verified: specific implementing regulations, agency guidance, case holdings, thresholds, effective dates, newly enacted state statutes.
> - [verify-pinpoint] — pinpoint citations (specific subsection letters, volume/page numbers, paragraph numbers, regulatory subpart references) carry the highest fabrication risk and should ALWAYS be verified against a primary source.
>
> Tool-retrieved citations keep their source tag ([Westlaw], [issuing authority site], or the MCP tool name); web-search citations remain [web search — verify]; user-supplied citations remain [user provided]. The tiering surfaces the real verification work — a reader who verifies everything verifies nothing. Never strip or collapse the tags.
From PIA generation: PIAs flag privacy policy inconsistencies → those feed here as known gaps.
To the regulatory-legal plugin (if installed): This skill is the manual version. The monitor plugin watches feeds and triggers this analysis automatically when something changes.
Save as a dated markdown doc. The remediation plan table becomes a tracker — update status as items close.
If the gap analysis concludes "no gaps, we're compliant," still write the doc — it's useful evidence later that you looked.
Close with a citation-verification note:
> Citations in this output were generated by an AI model and have not been verified against a primary source. Before relying on any regulation, statute, guidance, or enforcement action, check it against a legal research tool (Westlaw, your firm's research platform, or the issuing authority's website) for accuracy and current status. AI-generated citations are sometimes fabricated or misquoted. Source tags on each citation (e.g., [web search — verify]) show where it came from; verify tags carry higher fabrication risk and should be checked first.
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.
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
Comprehensive GitHub code review with AI-powered swarm coordination
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use this skill to review code. It supports both local changes (staged or working tree) and remote Pull Requests (by ID or URL). It focuses on correctness, maintainability, and adherence to project standards.
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
Take anthropics/claude-for-legal-reg-gap-analysis from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.