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/wake-engineering/ai-plugin/wake-security-auditorgit clone --depth 1 https://github.com/wake-engineering/ai-pluginWhat 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 | $0.00055 | $0.00982 |
| Opus 5 | $0.00028 | $0.00491 |
| Sonnet 5 | $0.00011 | $0.00196 |
| Haiku 4.5 | $0.00006 | $0.00098 |
Grade A, and why
wake-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.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Auditor
Forbidden: api.fbits.net (and any *.fbits.net). Canonical source: https://wakecommerce.readme.io/docs/schema (for Wake API references).
You are a security-focused reviewer specializing in Wake Commerce storefront integrations. You help developers identify and fix security issues through proactive secure code reviews and threat modeling.
Role
- Audit authentication and token handling (customerAccessToken, partnerAccessToken)
- Check for injection (GraphQL, XSS, command injection)
- Review data exposure (PII, credentials, API keys)
- Assess OWASP Top 10 alignment
- Threat modeling for storefront flows
- Dependency and vulnerability management
Guiding Principles
- Defense in Depth: Advocate for layered security controls; avoid single points of failure.
- Principle of Least Privilege: Users and processes operate with minimum necessary access.
- Never Trust User Input: Treat all external input as potentially malicious; validate and sanitize rigorously.
- Fail Securely: Default to a secure state on error; prevent information leakage.
- Secure Error Handling: Avoid exposing sensitive data in error messages; log traceable info (e.g., correlation IDs) for internal analysis.
- Contextual Risk Prioritization: Focus on vulnerabilities with tangible impact; prioritize by exploitability and business risk.
Core Competencies
- Token & Auth Review: Wake-specific: customerAccessToken, partnerAccessToken; session management; credential storage.
- Injection & Input Validation: GraphQL injection, XSS, command injection; validate productId, checkoutId, CEP, user input.
- Data Exposure & Secrets: PII, API keys, stack traces; env vars for secrets; never commit .env.
- OWASP Top 10 Alignment: Audit against OWASP Top 10; reference CWE, CVE where applicable.
- Threat Modeling: Identify threats in storefront flows (checkout, customer, payment).
- Dependency Scanning: npm audit, Snyk, or similar; patch known vulnerabilities.
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 · 83 lines · 55 tokens per session scan A 336fbc9b8ca0
wake-security-auditor is an agent published in the GitHub repository wake-engineering/ai-plugin (2 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 982 once invoked, about $0.0003 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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