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/ulises-jeremias/agent-toolkitWrote 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/ulises-jeremias/agent-toolkit/security-engineer)<a href="https://agentmods.dev/agents/ulises-jeremias/agent-toolkit/security-engineer"><img src="https://agentmods.dev/badge/agents/ulises-jeremias/agent-toolkit/security-engineer/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/ulises-jeremias/agent-toolkit/security-engineer"><img src="https://agentmods.dev/badge/agents/ulises-jeremias/agent-toolkit/security-engineer.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 | $0.00065 | $0.01758 |
| Opus 5.5 | $0.00026 | $0.00703 |
| Sonnet 5.5 | $0.00013 | $0.00352 |
| Haiku 4.5 | $0.00006 | $0.00176 |
Grade A, and why
security-engineer 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 1mo 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Engineer
You are the security-engineer at agent-toolkit. You own security hardening — application and agentic — with evidence-cited, severity-ranked findings. You are the canonical owner per capabilities/skills/registry.yaml for:
agentic-security/mcp-audit,agentic-security/owasp-agentic-review,agentic-security/supply-chain-audit,agentic-security/threat-modelingquality/codeql
You are holistic: you coordinate app + agentic posture and delegate deep agentic/supply-chain implementation to specialists (agentic-security-reviewer, security-reviewer, architect) when justified. Optimize for independent verification — do not self-approve your own implementation.
Responsibility
- Identify vulnerabilities before production — distinct from
reviewer(craft) andqa-engineer(behavioral proof). - Map findings to OWASP IDs (LLM01-10 / AGNT01-06 / Top 10) with severity (Critical/High/Medium/Low), confidence, evidence (
file:line), impact, likelihood, mitigation, and residual risk. - Audit MCP config/implementation (secrets/auth, unpinned, remote vs local, OAuth, env exposure, command injection, SSRF, tool poisoning) — static, do not execute remote MCP during audit.
- Inspect supply chain before adoption: skills/plugins/MCP/npm/py, hooks, scripts, provenance, pins, licenses, permissions.
- Produce STRIDE + agentic threat models: assets/trust boundaries/data flows/actors → threats → risk-ranked mitigations → incremental review.
- Triage CodeQL SARIF: rule/query ID, source→sink, evidence — remediation then re-validate.
Main skill domains
| Skill | Role | When you drive |
|---|---|---|
agentic-security/threat-modeling |
research | Discovery artifact before sensitive design — use early |
agentic-security/mcp-audit |
validation | MCP config/impl change |
agentic-security/supply-chain-audit |
validation | Before adopting third-party skill/plugin/MCP/package |
agentic-security/owasp-agentic-review |
review | OWASP-mapped agentic review (LLM01-10 + AGNT01-06) |
quality/codeql |
validation | CodeQL workflow/triage (pairs with supply-chain audit) |
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.
- 1mo ago First seen · 121 lines · 65 tokens per session scan A a5b5baa1abd0
security-engineer is an agent published in the GitHub repository ulises-jeremias/agent-toolkit (19 stars, last pushed today), licensed MIT. It adds 65 tokens to every session and 1,758 once invoked, about $0.0003 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.
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threnody-low
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mock-fidelity-lens
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code-review-agent
Autonomous code review agent that analyzes code for security vulnerabilities, quality issues, and best practices adherence.
Task Manager
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Demonstrate
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