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.
git clone --depth 1 https://github.com/emaraschio/cursor-commandsWrote 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/commands/emaraschio/cursor-commands/agent-risk-review)<a href="https://agentmods.dev/commands/emaraschio/cursor-commands/agent-risk-review"><img src="https://agentmods.dev/badge/commands/emaraschio/cursor-commands/agent-risk-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/commands/emaraschio/cursor-commands/agent-risk-review"><img src="https://agentmods.dev/badge/commands/emaraschio/cursor-commands/agent-risk-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 | $0.00020 | $0.00548 |
| Opus 5 | $0.00010 | $0.00274 |
| Sonnet 5 | $0.00004 | $0.00110 |
| Haiku 4.5 | $0.00002 | $0.00055 |
Grade A, and why
agent-risk-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 9d 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Produce a one-page agent permission brief before granting an AI agent access to a system, tool, or account. Full workflow: .cursor/skill-contracts/agent-risk-review/SKILL.md (user install: ~/.cursor/skill-contracts/agent-risk-review/SKILL.md).
Defaults
None. See skill for workflow defaults.
Steps
- Read
.cursor/skill-contracts/agent-risk-review/SKILL.mdfor the full agent contract; if that file is missing, read~/.cursor/skill-contracts/agent-risk-review/SKILL.md. - Execute phases in order (Intake → Discovery → Draft → Clarify gate → Deliver); do not skip the clarify-before-finalize gate.
- Report the final seven-section brief in chat; offer optional save under
docs/agent-permissions/<slug>.mdwhen the host hasdocs/.
Anti-patterns
- Default to least privilege, never blanket access. Trigger: drafting the allowed-actions tier. Wrong: granting full admin or broad write access without explicit limits. Correct: scope each grant to least privilege and require documented limits for anything destructive. Reason: an over-permissioned agent turns a small mistake into a production-wide one.
- Resolve ambiguity before finalizing. Trigger: a permission tier, limit, or log destination is unclear. Wrong: publishing the final brief on guessed or maximal defaults. Correct: stop at the clarify gate and ask before finalizing. Reason: a brief shipped on assumptions authorizes access no one actually reviewed.
- Never route secrets into logs. Trigger: specifying the required-logs section. Wrong: logging tokens, credentials, PII, or PHI in plain text. Correct: place them under must-not-log and never-allowed. Reason: logs are retained and broadly readable, so a logged secret is a leaked secret.
Examples
/agent-risk-reviewwith "GitHub org token for merge bot"/agent-risk-reviewwith "AWS prod read-only for incident agent"
Maintainers
Behavioral eval: .cursor/skill-contracts/agent-risk-review/eval/cases.md. Ship gate sections: A, S before changing SKILL.md or this command.
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.
- 9d ago First seen · 40 lines · 20 tokens per session scan A 5299200586c5
agent-risk-review is a command published in the GitHub repository emaraschio/cursor-commands (9 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 548 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
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grok_init
Discover, verify, and persist the local HTTP proxy used by Grok Build Supervisor.
handle-pr-comments
Fetch all PR comments, classify by severity, and present for user approval before acting.
self-review
Review only changed files in this branch Your primary goal is to provide valuable, trustworthy feedback while avoiding false positives and low-impact commentary.
create-pr
Commit changes and create a PR with proper formatting.
back-to-master-delete-branch
Cleanup current branch and switch to default branch with latest changes.