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 commands/alphaaiservice/cortex/audit-setupgit clone --depth 1 https://github.com/alphaaiservice/cortexWhat 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 | $0.00040 | $0.07079 |
| Opus 5 | $0.00020 | $0.03540 |
| Sonnet 5 | $0.00008 | $0.01416 |
| Haiku 4.5 | $0.00004 | $0.00708 |
Grade A, and why
audit-setup 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 yesterday.
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 — 837 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Audit Logging System
Action: $ARGUMENTS (default: init)
Parse $ARGUMENTS:
init— Generate the complete audit logging system (schema, middleware, service, dashboard)report— Generate an audit report for a specified time periodalerts— Configure alerting rules for suspicious activity patternscompliance— Generate compliance checklist and evidence for GDPR/SOC 2/HIPAA- No argument =
init
Step 0: Detect Project Context
echo "=== Project Type ==="
ls package.json pyproject.toml build.gradle.kts pom.xml 2>/dev/null
echo "=== Backend Language ==="
if [ -f "pyproject.toml" ] || [ -f "requirements.txt" ]; then
echo "Python/FastAPI detected"
elif [ -f "package.json" ] && grep -q "nestjs" package.json 2>/dev/null; then
echo "NestJS detected"
elif [ -f "build.gradle.kts" ] || [ -f "pom.xml" ]; then
echo "Spring Boot detected"
fi
echo "=== Existing Audit/Logging ==="
grep -rn "audit\|AuditLog\|audit_log" --include="*.py" --include="*.ts" --include="*.java" . 2>/dev/null | grep -v node_modules | head -20
echo "=== Auth System ==="
find . -maxdepth 5 -path "*/auth*" -name "*.py" -o -path "*/auth*" -name "*.ts" -o -path "*/auth*" -name "*.java" 2>/dev/null | grep -v node_modules | head -10
echo "=== Database ==="
grep -rn "mysql\|mongodb\|DATABASE_URL\|MONGO" .env* 2>/dev/null | head -5
Determine:
- Backend language (Python/NestJS/Spring Boot)
- Which database to use for audit logs (MySQL for structured, MongoDB for high-volume)
- Whether auth system exists (to instrument login/logout events)
Step 1: Audit Event Categories
Define the complete list of auditable events:
Authentication Events (MUST audit)
| Event | Severity | Data Captured |
|---|---|---|
auth.login.success |
INFO | user_id, IP, user_agent, method (password/oauth) |
auth.login.failure |
WARNING | email_attempted, IP, user_agent, failure_reason |
auth.logout |
INFO | user_id, IP |
auth.token.refresh |
INFO | user_id, IP |
auth.password.change |
WARNING | user_id, IP |
auth.password.reset.request |
WARNING | email, IP |
auth.password.reset.complete |
WARNING | user_id, IP |
auth.2fa.enable |
WARNING | user_id, IP |
auth.2fa.disable |
CRITICAL | user_id, IP |
auth.account.lockout |
CRITICAL | user_id, IP, failed_attempts |
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.
- yesterday First seen · 837 lines · 40 tokens per session scan A 11473a6bc710
audit-setup is a command published in the GitHub repository alphaaiservice/cortex (1 stars, last pushed 26d ago), licensed MIT. It adds 40 tokens to every session and 7,079 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.
Other commands, from other repositories
alfred
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audit
Auditoría completa del proyecto con 4 agentes en paralelo.
discuss
Refina una idea o feature antes de abrir un flujo completo de implementación.