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 RedHatProductSecurity/prodsec-skills --skill secdevai-reviewgit clone --depth 1 https://github.com/RedHatProductSecurity/prodsec-skillsWrote 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/redhatproductsecurity/prodsec-skills/secdevai-review)<a href="https://agentmods.dev/skills/redhatproductsecurity/prodsec-skills/secdevai-review"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/prodsec-skills/secdevai-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/redhatproductsecurity/prodsec-skills/secdevai-review"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/prodsec-skills/secdevai-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 | $0.00058 | $0.01347 |
| Opus 5 | $0.00029 | $0.00674 |
| Sonnet 5 | $0.00012 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00135 |
Grade A, and why
secdevai-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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Code Review
AI-powered security review of source code using OWASP Top 10, CWE/SANS Top 25, and OWASP WSTG patterns. Supports file review, commit review, and full codebase scan modes across all major languages.
When to Use This Skill
- Reviewing source code files or directories for security vulnerabilities
- Reviewing one or more git commits for security-relevant changes
- Scanning an entire codebase for OWASP Top 10 / CWE/SANS Top 25 issues
- Performing a security review pass before submitting a pull request
Workflow
Step 1: Determine Scope
Choose what to review (in priority order):
- If a specific number of recent commits is requested: review those commits
- If the last commit is requested: review the most recent commit
- If a specific file or directory is specified: review it
- Otherwise: scan the entire codebase
Step 2: Apply Ignore Patterns
Before scanning, exclude:
- Binary and media files (images, fonts, compiled artifacts, archives)
- Generated code and build output (
dist/,build/,*.pyc,*.class) - Dependency trees (
node_modules/,venv/,__pycache__/) - IDE and OS metadata (
.vscode/,.idea/,.DS_Store)
Note: documentation files (markdown, RST, plaintext) are not excluded — they can contain hardcoded secrets, leaked infrastructure details, or AI agent instructions.
If all files are excluded, report that no security-relevant content was found. If some files are excluded, proceed with the remaining files and list the skipped files at the end of the review.
Step 3: Load Security Context
Load context based on what is being reviewed:
-
Always: Apply OWASP Top 10 (2021) patterns from
./reference/security-review.context -
For web applications or services: Additionally apply OWASP WSTG v4.2 patterns from
./reference/wstg-testing.context -
For Go code (
.gofiles orgo.modpresent): Additionally apply Go security patterns from./reference/golang-security.context -
For native/systems code (C, C++, Rust, or build files such as
Makefile,CMakeLists.txt,Cargo.toml): Additionally apply CWE/SANS Top 25 patterns
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 153 lines · 58 tokens per session scan A d73a8a1bd346
secdevai-review is a skill published in the GitHub repository RedHatProductSecurity/prodsec-skills (52 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 58 tokens to every session and 1,347 once invoked, about $0.0003 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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