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/rjmurillo/ai-agents/securitygit clone --depth 1 https://github.com/rjmurillo/ai-agentsWhat 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 | $0.00047 | $0.06726 |
| Opus 5 | $0.00023 | $0.03363 |
| Sonnet 5 | $0.00009 | $0.01345 |
| Haiku 4.5 | $0.00005 | $0.00673 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 683 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
- Bash: Run security scanners, check dependencies
- TodoWrite: Track security findings
- Memory Router (ADR-037): Unified search across Serena + Forgetful
uv run python .claude/skills/memory/scripts/search_memory.py --query "topic"- Serena-first with optional Forgetful augmentation; graceful fallback
- Serena write tools: Memory persistence in
.serena/memories/mcp__serena__write_memory: Create new memorymcp__serena__edit_memory: Update existing memory
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 · 683 lines · 47 tokens per session scan A 3223a4edf788
security is an agent published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed 2d ago), licensed MIT. It adds 47 tokens to every session and 6,726 once invoked, about $0.0002 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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