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/homenshum/nodebenchai/agentic-reliability-auditgit clone --depth 1 https://github.com/HomenShum/NodeBenchAIWhat 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 | $0.00000 | $0.00609 |
| Opus 5 | $0.00000 | $0.00304 |
| Sonnet 5 | $0.00000 | $0.00122 |
| Haiku 4.5 | $0.00000 | $0.00061 |
Grade A, and why
agentic-reliability-audit 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Reliability Audit
Run a comprehensive audit of agent-facing infrastructure against the 8-point reliability checklist.
Instructions
You are an Agentic Systems Reliability Engineer. Your job is to find where the system lies to itself — where code tells agents everything is fine while silently leaking memory, inflating scores, or masking failures.
Phase 1: Scan (parallel agents)
Launch 3 parallel scan agents:
Agent 1 — Memory & Bounds Scan all TypeScript and Python files for:
new Map(),new Set(),const.*=.*[]without correspondingMAX_*+ evictionresponse.text()orresponse.json()without size limitsfetch(where URL is a variable without SSRF validation Report: file, line, pattern, severity (P0/P1/P2)
Agent 2 — Honesty Audit Scan all files for:
res.status(2in catch/fallback/else branches (fake success)passed: true,score:.*1.0,"VERIFIED","healthy"literals that bypass computationJSON.stringifyfeedingcreateHashwithout sorted keys Report: file, line, pattern, severity
Agent 3 — Error & Timeout Coverage Scan all route handlers for:
async.*req.*reswithout try/catch or asyncHandler wrapperawaitcalls to external services without AbortController/timeout- Missing
!res.headersSentguards before error responses Report: file, line, pattern, severity
Phase 2: Classify
Merge findings into a single table: | # | File | Line | Check | Finding | Severity | Fix Pattern | Sort by severity (P0 first), then by file.
Phase 3: Fix P0s
For each P0 finding:
- Read the file
- Apply the fix pattern from
.claude/rules/agentic_reliability.md - Verify tsc passes
- Move to next P0
Phase 4: Verify
- Run
npx tsc --noEmiton affected packages - Run
npx vitest runon affected test suites - Report: findings count by severity, fixes applied, build status
Output format
## Agentic Reliability Audit Report
**Scope**: [files scanned]
**Findings**: X total (Y P0, Z P1, W P2)
**Fixes applied**: N P0 fixes
### P0 Findings & Fixes
| # | File | Check | Finding | Fix Applied |
...
### P1 Findings (fix in same session)
| # | File | Check | Finding |
...
### P2 Findings (fix when touched)
| # | File | Check | Finding |
...
**Build**: tsc [pass/fail], vitest [X/Y passed]
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 · 77 lines · 0 tokens per session scan A 9937cdd71278
agentic-reliability-audit is a command published in the GitHub repository HomenShum/NodeBenchAI (14 stars, last pushed 19d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 609 tokens. 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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