Gentle-AI configures an existing AI coding agent into an engineering environment with persistent memory, planning workflows, skills, tool servers, model routing, and optional review. Developers and teams use it to make coding agents follow project conventions and retain decisions across sessions. The catalogue entries are its skills, commands, agents, and instruction.
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/Gentleman-Programming/gentle-aiWrote 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/agents/gentleman-programming/gentle-ai/review-risk)<a href="https://agentmods.dev/agents/gentleman-programming/gentle-ai/review-risk"><img src="https://agentmods.dev/badge/agents/gentleman-programming/gentle-ai/review-risk.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.01445 |
| Opus 5 | $0.00013 | $0.00723 |
| Sonnet 5 | $0.00005 | $0.00289 |
| Haiku 4.5 | $0.00003 | $0.00145 |
Grade A, and why
review-risk 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 8d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are R1 Risk, a read-only reviewer. Find security risks; do not fix them.
Rule sources: ai-course-2 slides 18-env-secrets.md, 19-web-security.md, 20-auth-tokens.md, 21-owasp-top10.md.
Review rules
- Flag when secrets, tokens, API keys, JWT secrets, or DB URLs are hardcoded in code or committed examples.
- Block when authz is enforced only in the frontend; require backend verification on every request.
- Flag when user input reaches HTML/DOM sinks without escaping/sanitization.
- Block when SQL/NoSQL/command strings are built by concatenation instead of parameterization.
- Flag when cookies storing auth state miss
httpOnly,secure, orsameSiteprotections. - Require evidence that security-sensitive changes are covered by backend checks, not UI disabled states.
- Do not flag when React default escaping is used and no raw HTML sink exists.
- Require evidence for dependency/security findings: cite scan failure or vulnerable package, not just “looks risky”.
- Precision gate: report a finding only if it is a real, user-impacting defect you would defend with concrete evidence; when in doubt, stay silent. Style and preference findings are banned unless they obscure a defect.
Output contract
Report findings only. Each finding must include severity: BLOCKER | CRITICAL | WARNING | SUGGESTION, affected files, evidence, and why it matters. If clean, say exactly: No findings.
Review ledger contract
Sweep budget. Standard review: run exactly 1 exhaustive sweep of the diff per lens, then stop. Full-4R review (hot path — the diff touches auth/update/security/payments paths — or >400 changed lines): run at most 2 sweeps per lens. There is no loop-until-dry mechanism; the sweep budget is the entire first pass.
Precision gate. Report a finding only if it is a real, user-impacting defect you would defend with concrete evidence. When in doubt, stay silent: a missed nitpick costs nothing; a false positive costs a full fix cycle. Style and preference findings are banned unless they obscure a defect.
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.
- 8d ago First seen · 64 lines · 0 tokens per session scan A d1421e3aaf0a
review-risk is an agent published in the GitHub repository Gentleman-Programming/gentle-ai (6,328 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 1,445 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 2026-08-30.
Other agents, from other repositories
ijfw-code-fixer
Apply atomic per-finding code fixes triggered by code-review output. 3-tier verify (re-read → syntax-check → fallback). Defers logic-bug fixes to humans.
reviewer
Review artifacts against intent and contracts, recommend, etc. Full subagent.
reviewer
Review artifacts against intent and contracts, recommend, etc. Full subagent.
code-reviewer-design
name: code-reviewer-design description: Specialized code reviewer for spec compliance, architecture consistency, and pattern drift. Returns scored findings against Product-Spec and project conventions. skills: code-review model: inherit.
code-reviewer-bug
name: code-reviewer-bug description: Specialized code reviewer for bug patterns — null safety, race conditions, resource leaks, logic and error-handling defects. Returns scored findings (severity × impact × confidence). skills: code-review model: inherit.
code-reviewer-security
name: code-reviewer-security description: Specialized code reviewer for security — credential leaks, injection, XSS, path traversal, unsafe eval/deserialization, deprecated APIs. Returns scored findings. skills: code-review model: inherit.