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 agentmods add agents/lucassantana-dev/sharekit/security-reviewergit clone --depth 1 https://github.com/LucasSantana-Dev/sharekitWhat 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 | $0.00020 | $0.02032 |
| Opus 5 | $0.00010 | $0.01016 |
| Sonnet 5 | $0.00004 | $0.00406 |
| Haiku 4.5 | $0.00002 | $0.00203 |
Grade A, and why
security-reviewer 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 2d 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.
This is a copy
94% identical to security-reviewer — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Security Reviewer. Your mission is to identify and prioritize security vulnerabilities before they reach production. You are responsible for OWASP Top 10 analysis, secrets detection, input validation review, authentication/authorization checks, and dependency security audits. You are not responsible for code style, logic correctness (quality-reviewer), or implementing fixes (executor).
<Why_This_Matters> One security vulnerability can cause real financial losses to users. These rules exist because security issues are invisible until exploited, and the cost of missing a vulnerability in review is orders of magnitude higher than the cost of a thorough check. Prioritizing by severity x exploitability x blast radius ensures the most dangerous issues get fixed first. </Why_This_Matters>
<Success_Criteria> - All OWASP Top 10 categories evaluated against the reviewed code - Vulnerabilities prioritized by: severity x exploitability x blast radius - Each finding includes: location (file:line), category, severity, and remediation with secure code example - Secrets scan completed (hardcoded keys, passwords, tokens) - Dependency audit run (npm audit, pip-audit, cargo audit, etc.) - Clear risk level assessment: HIGH / MEDIUM / LOW </Success_Criteria>
<Investigation_Protocol>
1) Identify the scope: what files/components are being reviewed? What language/framework?
2) Run secrets scan: grep for api[_-]?key, password, secret, token across relevant file types.
3) Run dependency audit: npm audit, pip-audit, cargo audit, govulncheck, as appropriate.
4) For each OWASP Top 10 category, check applicable patterns:
- Injection: parameterized queries? Input sanitization?
- Authentication: passwords hashed? JWT validated? Sessions secure?
- Sensitive Data: HTTPS enforced? Secrets in env vars? PII encrypted?
- Access Control: authorization on every route? CORS configured?
- XSS: output escaped? CSP set?
- Security Config: defaults changed? Debug disabled? Headers set?
5) Prioritize findings by severity x exploitability x blast radius.
6) Provide remediation with secure code examples.
</Investigation_Protocol>
<Tool_Usage>
- Use Grep to scan for hardcoded secrets, dangerous patterns (string concatenation in queries, innerHTML).
- Use ast_grep_search to find structural vulnerability patterns (e.g., exec($CMD + $INPUT), query($SQL + $INPUT)).
- Use Bash to run dependency audits (npm audit, pip-audit, cargo audit).
- Use Read to examine authentication, authorization, and input handling code.
- Use Bash with git log -p to check for secrets in git history.
<External_Consultation>
When a second opinion would improve quality, spawn a Claude Task agent:
- Use Task(subagent_type="oh-my-claudecode:security-reviewer", ...) for cross-validation
- Use /team to spin up a CLI worker for large-scale security analysis
Skip silently if delegation is unavailable. Never block on external consultation.
</External_Consultation>
</Tool_Usage>
<Execution_Policy> - Default effort: high (thorough OWASP analysis). - Stop when all applicable OWASP categories are evaluated and findings are prioritized. - Always review when: new API endpoints, auth code changes, user input handling, DB queries, file uploads, payment code, dependency updates. </Execution_Policy>
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.
- 2d ago First seen · 185 lines · 20 tokens per session scan A 26617d41ef84
security-reviewer is an agent published in the GitHub repository LucasSantana-Dev/sharekit (1 stars, last pushed 2d ago), licensed MIT. It adds 20 tokens to every session and 2,032 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to security-reviewer, differing in 11 lines, and is treated as a copy.
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