- Skill ID
- anthropics/claude-for-legal/launch-review
- Publisher
- anthropics
- Repository
- claude-for-legal
- Installs
- 0
- Files
- 2
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
anthropics/claude-for-legal/launch-reviewInstalls these files- SKILL.md
- references/seven-category-framework.md
What this skill tells the agent
/launch-review
- Load
~/.claude/plugins/config/claude-for-legal/product-legal/CLAUDE.md→ framework + calibration. Stop if placeholders. - Get PRD + related docs. If tracker connected, pull ticket and comments.
- Walk every framework category using the workflow below.
- Calibrate each finding against the table. Novel = flag explicitly.
- Output review memo in house format. Post summary to ticket if connected.
- Hand off: marketing-claims-review if substantial marketing; feature-risk-assessment if a finding needs depth.
/product-legal:launch-review PROJ-1234Matter 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 /product-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/product-legal/matters/<matter-slug>/. Never read another matter's files unless Cross-matter context is on.
Destination check
Before producing output, check where it's going. If the user has named a destination (a channel, a distribution list, a counterparty, "everyone"), ask whether it's inside the privilege circle. Public channels, company-wide lists, counterparty/opposing counsel, vendors, and clients (for work product) waive the protection. When the destination looks outside the circle, flag it and offer (a) the privileged version for legal only, (b) a sanitized version for the broader channel, or (c) both — don't silently apply a privileged header and then help paste it somewhere the header won't protect it. See the canonical ## Shared guardrails → Destination check in this plugin's CLAUDE.md.
Purpose
Read the PRD, check every category in this team's framework, calibrate against what actually blocks here (per ~/.claude/plugins/config/claude-for-legal/product-legal/CLAUDE.md), and output a review in house format. Goal: a PM reads it and knows exactly what has to happen before they ship.
Load calibration
Read ~/.claude/plugins/config/claude-for-legal/product-legal/CLAUDE.md:
## Review framework— the categories to check## Risk calibration— what blocks vs. what's FYI at this company## Launch review process— output format## Escalation— when to route up
The calibration table is the difference between this skill and a generic checklist. If the table says "new data collection → PIA, ships in 1-2 days," don't write "this might require a full DPIA and regulatory consultation." Match the team's actual practice.
Workflow
Step 1: Get the inputs
- PRD — from file, Drive, or the launch tracker ticket
- Spec/design doc — if separate
- Marketing plan — if there is one (hands off to marketing-claims-review if substantial)
- Launch date — for urgency calibration
- Launch tracker ticket — if connected, pull it for context and comments
If Jira/Linear MCP is connected, pull the ticket history — often there's context in earlier comments that the PRD doesn't capture.
Step 2: Understand what's launching
Before the checklist, answer in plain English:
- What does this thing do?
- Who uses it — existing users, new users, a new segment?
- What's new vs. what's an extension of something already reviewed?
- Any new data, new vendors, new claims, new jurisdictions?
AI detection — run before the framework walk. Check whether this launch uses AI in any form: a third-party model, an internally built model, an AI-powered vendor feature, automated scoring or classification, generative content, recommendations, predictions. Look for this even if the PRD doesn't label it "AI" — words like "intelligent", "automated", "personalized", "generated", "suggested" are tells.
If AI component detected → flag it, then run /ai-governance-legal:use-case-triage [feature] alongside the framework walk. Category 8 below handles the detail; this flag ensures it's never skipped even if the PRD is vague.
Step 3: Walk the framework
For each category in ~/.claude/plugins/config/claude-for-legal/product-legal/CLAUDE.md → Review framework. If the team doesn't have one, use the 8-category default below. The categories are stable framing concepts; within each category, research the regulatory regimes applicable to the product's sector, audience, and jurisdictions before calibrating severity. What blocks in one jurisdiction or sector may be routine in another — ~/.claude/plugins/config/claude-for-legal/product-legal/CLAUDE.md captures the team's calibration.
| # | Category | Key question | Auto-skip if |
|---|---|---|---|
| 1 | Contractual commitments | Does this conflict with any customer-facing promise (ToS, SLA, marketing)? | No customer-facing changes |
| 2 | Privacy | New data collection, new purpose, new sharing? | No data changes |
| 3 | Security | New attack surface, new data at rest, new access patterns? | UI-only, no backend change |
| 4 | IP | Third-party code/content? Open-source license check? Outputs that could infringe? | No new dependencies, no user-generated content |
| 5 | Third-party | New vendor, partner, or integration? | No new external parties |
| 6 | Regulatory | Does this touch a regulated sector, audience, or jurisdiction? Research the applicable regimes. | Same users, same sectors, same jurisdictions as existing product |
No silent supplement. If a research query to the configured legal research tool (Westlaw, CourtListener, regulator sites, or firm platform) returns few or no results for a regime, enforcement precedent, or regulator guidance, 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 review 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., FTC Act § 5, GDPR Art. 33, CCPA § 1798.100). Still verify before relying on it to clear a launch, but lower priority. -[verify]— model-knowledge citations that are real but should be verified: specific implementing regulations, agency guidance, enforcement actions, case holdings, thresholds, effective dates, post-2023 amendments. -[verify-pinpoint]— pinpoint citations (specific subsection letters, volume/page numbers, paragraph numbers) carry the highest fabrication risk and should ALWAYS be verified against a primary source. Tool-retrieved citations keep their source tag ([Westlaw],[CourtListener],[regulator site], or the MCP tool name); web-search citations remain[web search — verify]; user-supplied citations (from the PRD or seed materials) remain[user provided]. The tiering surfaces the real verification work — a reader who verifies everything verifies nothing. Never strip or collapse the tags.
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