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 mshadmanrahman/pm-pilot --skill security-reviewgit clone --depth 1 https://github.com/mshadmanrahman/pm-pilotWrote 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/mshadmanrahman/pm-pilot/security-review)<a href="https://agentmods.dev/skills/mshadmanrahman/pm-pilot/security-review"><img src="https://agentmods.dev/badge/skills/mshadmanrahman/pm-pilot/security-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/mshadmanrahman/pm-pilot/security-review"><img src="https://agentmods.dev/badge/skills/mshadmanrahman/pm-pilot/security-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00011 | $0.00840 |
| Opus 5 | $0.00005 | $0.00420 |
| Sonnet 5 | $0.00002 | $0.00168 |
| Haiku 4.5 | $0.00001 | $0.00084 |
Grade A, and why
security-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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Review
Systematic security checklist for code changes. Catch vulnerabilities before they ship.
When to Use
- After writing authentication or authorization code
- After handling user input (forms, query params, file uploads)
- After creating or modifying API endpoints
- After touching secrets, tokens, or credentials
- Before any commit that touches security-sensitive code
Procedure
Step 1: Identify Scope
Determine which checks apply based on changed files:
- Auth code: full checklist
- API endpoints: input validation, injection, rate limiting
- Frontend: XSS, CSRF
- Config/infra: secrets, permissions
Step 2: Run Checklist
| Check | Severity | What to Look For |
|---|---|---|
| Hardcoded secrets | CRITICAL | API keys, passwords, tokens in source |
| SQL injection | CRITICAL | String concatenation in queries |
| Auth bypass | CRITICAL | Missing auth checks on protected routes |
| XSS | HIGH | Unsanitized user input in HTML output |
| CSRF | HIGH | Missing CSRF tokens on state-changing requests |
| Input validation | HIGH | Unvalidated user input passed to logic |
| Rate limiting | MEDIUM | Endpoints without rate limits |
| Error leaks | MEDIUM | Stack traces or internal details in responses |
| Authz checks | HIGH | Missing permission verification |
| Dependency vulns | MEDIUM | Known CVEs in dependencies |
Step 3: Scan Code
# Check for hardcoded secrets (patterns)
grep -rn "password\s*=\s*['\"]" --include="*.{ts,js,py,go}" .
grep -rn "api_key\s*=\s*['\"]" --include="*.{ts,js,py,go}" .
grep -rn "secret\s*=\s*['\"]" --include="*.{ts,js,py,go}" .
# Check for SQL string concatenation
grep -rn "SELECT.*+.*FROM\|INSERT.*+.*INTO" --include="*.{ts,js,py,go}" .
# Check dependency audit
npm audit 2>/dev/null || pip-audit 2>/dev/null || true
Step 4: Report
Security Review: {scope description}
CRITICAL:
- {finding with file:line and fix}
HIGH:
- {finding with file:line and fix}
MEDIUM:
- {finding or "none"}
LOW:
- {finding or "none"}
Verdict: PASS | BLOCKED ({count} CRITICAL issues)
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 · 117 lines · 11 tokens per session scan A 6d2baf943b05
security-review is a skill published in the GitHub repository mshadmanrahman/pm-pilot (20 stars, last pushed 3d ago), licensed MIT. It adds 11 tokens to every session and 840 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 skills, from other repositories
verify-implementation
A workflow that runs a project’s verification skills to produce a report on coding patterns, architecture rules, and project conventions. It is intended for work after implementation, before a pull request, or during code review.
review-loop
Run the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified"…
frontend-code-review
Trigger when the user requests a review of frontend files (e.g., .tsx, .ts, .js). Support both pending-change reviews and focused file reviews while applying the checklist rules.
no-mistakes
Validate committed feature-branch changes through the no-mistakes pipeline: intent, rebase, review, test, docs, lint, push, PR, and CI. Use when the user asks to run no-mistakes, ship safely, validate before pushing, or gate a change before it reaches upstream.
ai-slop-cleaner
Post-implementation cleanup that removes AI-generated bloat while preserving functionality. Runs pass-by-pass with test verification after each pass. Activate after kraken/spark complete a feature, or when a codebase needs hygiene work.
coding-standards
Universal coding standards - naming, formatting, error handling, immutability, SOLID principles.