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 anylegal-ai/anylegal-oss --skill reviewgit clone --depth 1 https://github.com/anylegal-ai/anylegal-ossWrote 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/anylegal-ai/anylegal-oss/review)<a href="https://agentmods.dev/skills/anylegal-ai/anylegal-oss/review"><img src="https://agentmods.dev/badge/skills/anylegal-ai/anylegal-oss/review/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/anylegal-ai/anylegal-oss/review"><img src="https://agentmods.dev/badge/skills/anylegal-ai/anylegal-oss/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00039 | $0.01138 |
| Opus 5 | $0.00019 | $0.00569 |
| Sonnet 5 | $0.00008 | $0.00228 |
| Haiku 4.5 | $0.00004 | $0.00114 |
Grade A, and why
review 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Contract Review
When to Use
Use this skill when:
- The user asks to review a contract or document
- The user wants a risk assessment or issue-spotting pass
- The user says /review
- The user asks to "check", "flag", "audit", or "assess" a document
- The user asks to review and then apply changes (review + redline is one flow)
Process
- Identify which document to review — Check the "Active document" in your context. If the active document is a contract/agreement in the workspace documents list, review it. If the active document is an instructions file, playbook, template, or other non-contract file (or if no document is active), ask the user which document they want reviewed. List the available workspace documents and let them pick.
- Read the document via
read_document— always read the full document first - Read the relevant playbook(s) — check the "Available Playbooks" manifest in your context, then call
read_document("Playbook/<filename>")to load the one(s) relevant to this contract type, jurisdiction, or client - Research jurisdiction-specific requirements — identify the governing law from the contract, then:
- Use
web_searchwith the jurisdiction set to find relevant statutes and regulations for the contract type - Use
web_fetchto retrieve full statutory text from authoritative sources (government domains, official gazettes) - Cross-reference: for any cited statute, run a follow-up search to verify it is current and not superseded
- Use
web_searchfor case law, regulatory guidance, and market standards (recent enforcement trends, standard market positions for the industry)
- Use
- Analyze each key clause:
- Identify clause type (indemnification, limitation of liability, termination, etc.)
- Assess position: favorable, balanced, or unfavorable for the represented party
- Determine risk level: low, medium, high, or critical
- Check alignment with playbook positions
- Flag any clauses that conflict with mandatory statutory requirements — cite the exact source URL retrieved via
web_fetch - Use
web_searchto check market standards if the clause deviates from typical positions - Consider market standards and jurisdiction-specific requirements
- Present findings in structured format with specific recommendations
- If user asks to apply changes ("redline", "implement", "apply", "do it"):
- Invoke
Skill(skill="docx-editing")for the full edit-pattern library, then calledit_documentfor each change. Edit the document in place — do not clone to a_v2copy. - Copy the EXACT text span from the document — do not paraphrase or reconstruct from memory. Use the shortest unique snippet for
old_text. edit_documentemits<w:ins>/<w:del>tracked-change markup automatically. Author defaults to"Anylegal.ai"— pass an explicit author only if the user supplies a different name.- Do NOT just describe changes — actually call
edit_documentfor each one. - Do NOT use
run_codefor text edits.
- Invoke
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.
- 12d ago First seen · 77 lines · 39 tokens per session scan A 96725472c54b
review is a skill published in the GitHub repository anylegal-ai/anylegal-oss (11 stars, last pushed 4mo ago), licensed MIT. It adds 39 tokens to every session and 1,138 once invoked, about $0.0002 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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