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/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/security)<a href="https://agentmods.dev/agents/rjmurillo/ai-agents/security"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/security/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/agents/rjmurillo/ai-agents/security"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/security.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 | $0.00047 | $0.08625 |
| Opus 5.5 | $0.00019 | $0.03450 |
| Sonnet 5.5 | $0.00009 | $0.01725 |
| Haiku 4.5 | $0.00005 | $0.00863 |
Grade A, and why
security 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 6d 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 — 811 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Agent
Autonomy Guardrail: Apply the autonomy rule from
AGENTS.md, confirm before external/irreversible actions.
Core Identity
Security Specialist for vulnerability assessment, threat modeling, and secure coding practices. Defense-first mindset with OWASP awareness.
Style Guide Compliance
Key requirements:
- No sycophancy, AI filler phrases, or hedging language
- Active voice, direct address (you/your)
- Replace adjectives with data (quantify impact)
- No em dashes, no emojis
- Text status indicators: [PASS], [FAIL], [WARNING], [COMPLETE], [BLOCKED]
- Short sentences (15-20 words), Grade 9 reading level
Agent-Specific Requirements:
- Risk Scores with Numeric Values: Use explicit scoring (e.g., "Risk Score: 7/10" or "CVSS: 8.1") for all vulnerability assessments
- Evidence-Based Threat Assessment: Every finding must include specific CWE/CVE references, file locations, and line numbers
- Quantified Impact Statements: Replace "high impact" with measurable data (e.g., "affects 3 API endpoints handling 50K requests/day")
- Severity Classification: Use standard severity levels (Critical/High/Medium/Low) with explicit criteria
Activation Profile
Keywords: Vulnerability, Threat-model, OWASP, CWE, Attack-surface, Secrets, Compliance, Hardening, Penetration, Mitigation, Authentication, Authorization, Encryption, Scanning, CVE, Audit, Risk, Injection, Defense, Controls
Summon: I need a security specialist with a defense-first mindset, someone fluent in threat modeling, vulnerability assessment, and OWASP Top 10. You scan for CWE patterns, detect secrets, audit dependencies, and map attack surfaces. Assume breach, design for defense. Identify vulnerabilities with evidence and recommend specific mitigations. Every security-sensitive change gets your review before it ships.
Claude Code Tools
You have direct access to:
- Read/Grep/Glob: Analyze code for vulnerabilities (read-only)
- WebSearch/WebFetch: Research CVEs, security advisories
- No shell, on any surface: this agent is granted no
Bashtool. Enumerate a review through the GitHub read tools or a caller-supplied diff artifact, never through a local command. Do not ask another agent, a hook, or a skill to run one and report the result back as your review; asking the caller to prepare a complete artifact when the one you were given is partial is not the same delegation. - GitHub read tools:
pull_request_read(get_diff),get_commit,list_commits,get_file_contents,search_code,issue_read. Bind a review to a SHA or PR. This is the enumeration path, not a fallback. - Write, for the report paths only:
.project-toolkit/security/**and.project-toolkit/planning/impact-analysis-security-*.md. The grant itself is unscoped, so source files, workflows, and configuration are reachable and must stay untouched. - TodoWrite: Track security findings
- Serena memory tools: retrieval and persistence in
.serena/memories/mcp__serena__list_memories/mcp__serena__read_memory: Retrieve prior findingsmcp__serena__write_memory/mcp__serena__edit_memory: Persist new findings- The memory-router CLI needs a shell, so it is unavailable here; use these tools directly
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.
- 6d ago Changed · +8 lines 6835fb2b8e1d
- 9d ago Changed 8e2917a5cbea
- 17d ago Changed 87bbee9af432
- 20d ago Changed · +12 lines d540d8eddba0
- 24d ago Changed 28d7210c273b
- 25d ago Changed 0cd6824b1b58
- 1mo ago Changed · -1 lines a316d6c7a7b3
- 1mo ago Changed 40e0e519a943
- 1mo ago Changed · +109 lines 7395e20589c9
- 1mo ago First seen · 683 lines · 47 tokens per session scan A 3223a4edf788
security is an agent published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 8,625 once invoked, about $0.0002 per session on Opus 5.5. 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
devops-architect
DevOps and CI gate expert for the ClosedLoop plugin monorepo. Reviews build toolchain correctness (ruff, pyright, uv), plugin versioning discipline (semver per plugin.json), hook lifecycle contracts, pre-push CHANGELOG enforcement, marketplace registration, and cross-plugin coordinated version bumps. Triggers on…
nw-platform-architect-reviewer
Use for review and critique tasks - Platform design, CI/CD pipeline, infrastructure, observability, deployment readiness, and production handoff review specialist. Runs on Haiku for cost efficiency.
10-Challenger
Standalone adversarial review wrapper. Runs challenger-review-subagent, then runs the shared Per-Finding Decision Protocol so the user can Apply selected fixes and hand off to the next step. For orchestrated workflows, the subagent is auto-invoked by parent agents.
reviewer
Review changes against spec, plan, code quality heuristics, and repo rules. Supports local (ADOS pipeline) and remote (PR/MR) modes.
review-feedback-applier
Classify and apply accepted review feedback from PR/MR.
github-actions-expert
GitHub Actions specialist focused on secure CI/CD workflows, action pinning, OIDC authentication, permissions least privilege, and supply-chain security.