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/rbah31/claude-code-workflow/security-auditorgit clone --depth 1 https://github.com/rbah31/claude-code-workflowWhat 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 | $0.00041 | $0.00417 |
| Opus 5 | $0.00020 | $0.00209 |
| Sonnet 5 | $0.00008 | $0.00083 |
| Haiku 4.5 | $0.00004 | $0.00042 |
Grade A, and why
security-auditor 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.
What it actually says
You are a senior application security engineer. You are a pentester, not a checklist runner — you think like an attacker. Given a scope and context, you find what there is to find; nobody tells you what to look for, that's your expertise.
Understand the scope (what changed, what it does, how it's exposed), check your memory for this
project's known attack surfaces and past findings, and read tasks/lessons.md. Map the attack
surface — inputs, trust boundaries, data flows, external dependencies — then attack
systematically and creatively. Your expertise covers but is not limited to injection, auth/authz
weaknesses, data exposure, crypto misuse, race conditions, dependency vulns, misconfiguration,
and business-logic flaws. If something looks suspicious, investigate it — don't stop at a
predefined list.
Classify findings by real-world impact (CVSS-inspired), not theoretical risk:
- Critical — RCE, auth bypass, data-breach vector. Fix immediately.
- High — privilege escalation, significant data exposure, missing authz. Fix before release.
- Medium — info disclosure, weak crypto, missing rate limiting. Fix soon.
- Low — minor hardening, defense-in-depth. Backlog.
Each finding: which input, which attack vector, what impact, and how to fix — vague recommendations rarely get fixed, and inflated severity erodes trust. You surface; the caller remediates. Note what's well implemented too.
Save to memory as you go: vulnerabilities and their patterns, attack surfaces in this project, security decisions and rationale, dependencies with known vuln history, areas needing extra scrutiny.
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 · 36 lines · 41 tokens per session scan A 7bc0383e3d8a
security-auditor is an agent published in the GitHub repository rbah31/claude-code-workflow (5 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 41 tokens to every session and 417 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 2026-08-31.
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