Claude for Legal is a collection of AI agents, skills, and data connectors for legal work such as commercial, privacy, employment, litigation, regulatory, and intellectual-property matters. Lawyers and legal teams use it through Claude Cowork, Claude Code, or the Claude Managed Agents API, with attorney review required for every output. The catalogue entries are its workflow plugins, skills, agents, and connectors.
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.
npx skills add anthropics/claude-for-legal --skill policy-monitorgit clone --depth 1 https://github.com/anthropics/claude-for-legalWrote 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.
[](https://agentmods.dev/skills/anthropics/claude-for-legal/policy-monitor)<a href="https://agentmods.dev/skills/anthropics/claude-for-legal/policy-monitor"><img src="https://agentmods.dev/badge/skills/anthropics/claude-for-legal/policy-monitor/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.
<a href="https://agentmods.dev/skills/anthropics/claude-for-legal/policy-monitor"><img src="https://agentmods.dev/badge/skills/anthropics/claude-for-legal/policy-monitor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00082 | $0.03390 |
| Opus 5 | $0.00041 | $0.01695 |
| Sonnet 5 | $0.00016 | $0.00678 |
| Haiku 4.5 | $0.00008 | $0.00339 |
Grade A, and why
policy-monitor 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 13d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- policy-monitor — 100% identical, 0 lines differ
- policy-monitor — 86% identical, 20 lines differ
How it starts
The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/policy-monitor
Sweep mode (no argument or --sweep):
- Read
~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md→ outputs folder path, AI policy document, last sweep date. - Use the framework below. Scan outputs folder for files since last sweep.
- For each output: extract approved practices → diff against current policy commitments and use case registry.
- Classify gaps: REQUIRED (policy misrepresents current practice) vs ADVISABLE (policy silent).
- For each gap: quote current policy, describe gap, draft suggested language.
- Flag any use cases in outputs not yet added to the
~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.mdregistry. - Present results to the human. Only after acknowledgment, update
Last policy sweepandgaps_foundin~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md.
Direct query mode (with description argument):
- Read
~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md→ current policy commitments, use case registry, actual policy document. - Parse proposed practice. Diff against policy: use case coverage, automation level, affected parties, disclosure, vendor data use, oversight.
- Output: covered / missing / conflicting + suggested language for each gap + registry entry if needed + timing recommendation.
Recurring runs:
Set up a recurring reminder in your own scheduler to run /ai-governance-legal:policy-monitor weekly. Scheduled execution requires a scheduled-tasks integration, which is not bundled with this plugin.
/ai-governance-legal:policy-monitor
/ai-governance-legal:policy-monitor "We want to use AI to automatically flag expense reports for review"
Purpose
AI policies drift from practice faster than almost any other policy document — the field moves quickly, use cases multiply, and each approved AIA or triage result represents a new commitment the policy may not have caught up with. An AIA approves a new AI use case with a human-oversight condition. A vendor AI agreement permits data processing the policy doesn't mention. A triage result marks a new category of deployment as conditional with a disclosure requirement. The policy sits there unchanged.
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.
- 13d ago First seen · 355 lines · 82 tokens per session scan A 76c8af655c05
policy-monitor is a skill published in the GitHub repository anthropics/claude-for-legal (9,433 stars, last pushed 21d ago), licensed Apache-2.0. It adds 82 tokens to every session and 3,390 once invoked, about $0.0004 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 2026-08-30.
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