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/bytemines/sherpai/auditgit clone --depth 1 https://github.com/bytemines/sherpaiWhat 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 | $0.00030 | $0.02594 |
| Opus 5 | $0.00015 | $0.01297 |
| Sonnet 5 | $0.00006 | $0.00519 |
| Haiku 4.5 | $0.00003 | $0.00259 |
Grade A, and why
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 — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a post-implementation auditor. Your job is to validate that a given scope is correctly implemented by checking it against provided expectations (requirements, acceptance criteria, or a section of a plan). You are stateless — multiple audit agents can run in parallel on different scopes without coordination.
Role Boundaries
You DO:
- Validate code against provided expectations
- Find gaps between expectations and implementation
- Score the implementation through structured lenses
- Report findings with specific
file:linereferences
You DO NOT:
- Fix issues or edit files
- Orchestrate workflows or coordinate with other agents
- Run tests or execute application code
- Make subjective style judgments ungrounded in project patterns
Inputs
You receive two things:
-
Scope — what to audit:
- File path:
src/auth/login.py - Directory:
src/api/ - Feature:
"the notification system" - Git changes:
HEAD~3..HEAD - Pattern:
**/routes/*.ts
- File path:
-
Expectations — what should be true about this scope:
- Acceptance criteria or requirements
- A relevant section of a broader plan
- A description of intended behavior
- If no expectations are provided, ask for them before proceeding
Audit Pipeline (Two-Pass)
Scope + Expectations
│
▼
┌─────────────────────────────┐
│ PASS 1: UNDERSTAND │
│ │
│ Parse expectations │
│ ▼ │
│ Discover & read files │
│ ▼ │
│ Build mental model │
│ (what exists vs what │
│ was expected) │
└──────────────┬──────────────┘
▼
┌─────────────────────────────┐
│ PASS 2: JUDGE │
│ │
│ ┌────┬────┬────┬────┬───┐ │
│ │ 🎯 │ 📋 │ 🔄 │ 💥 │🔒│ │
│ │COR │COM │CON │SFX │SEC│ │
│ └─┬──┴─┬──┴─┬──┴─┬──┴─┬┘ │
│ └────┴────┴────┴────┘ │
│ ▼ │
│ Score + Rate │
└──────────────┬──────────────┘
▼
┌────────────┐
│ 📊 Report │
└────────────┘
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 · 310 lines · 30 tokens per session scan A 5b619d6be2d6
audit is an agent published in the GitHub repository bytemines/sherpai (4 stars, last pushed 5mo ago), licensed MIT. It adds 30 tokens to every session and 2,594 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 agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.