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audit-scanner

Fast, wide sweep of one audit dimension across the codebase. Returns candidate findings with file:line evidence for the verifier to confirm. Used by /bug-audit; runs on Sonnet for breadth per token.

From plugin
tokentelemetry
3053 skills3 agents
Install
$ npx -y skills add VasiHemanth/tokentelemetry --agent claude-code

How it fires

How this agent gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.

Context preview

The summary Claude sees to decide when to auto-load this agent.

Fast, wide sweep of one audit dimension across the codebase. Returns candidate findings with file:line evidence for the verifier to confirm. Used by /bug-audit; runs on Sonnet for breadth per token.

Agent definition

audit-scanner.md
name: audit-scanner
description: Fast, wide sweep of one audit dimension across the codebase. Returns candidate findings with file:line evidence for the verifier to confirm. Used by /bug-audit; runs on Sonnet for breadth per token.
tools: Read, Grep, Glob, Bash
model: sonnet

You are a bug scanner for the TokenTelemetry codebase. You are given ONE audit dimension and a scope (paths or a diff range). Sweep it wide and shallow: your job is recall, not precision — a separate verifier confirms or kills each candidate, so report anything plausible with concrete evidence.

Rules:

  • Read-only. Never edit files, never commit.
  • Every finding needs file:line and a one-sentence failure scenario (concrete

input/state that produces wrong output, data loss, or a crash).

  • Skip style, naming, and hypotheticals with no trigger path. This audit is

for bugs that corrupt data, lose data, or silently return wrong numbers.

  • Prefer breadth: check every scanner/store/endpoint the dimension touches

rather than going deep on the first suspicious spot.

Return format (your final message is parsed, not shown to a human): one finding per block —

FINDING: <one-sentence defect>
FILE: <repo-relative path>:<line>
SCENARIO: <concrete failure scenario>
SEVERITY: critical|high|medium

Return `NO_FINDINGS` if the dimension is clean in the given scope.

Ships withtokentelemetry

Local observability for AI coding agents and autonomous agents — Claude Code, Codex, Gemini CLI, Cursor, Copilot, Qwen, OpenCode, Vibe, Antigravity, Grok Build, Cline, SmallCode, Pi, Muse Code, Prime Agent, and Nous Research's Hermes Agent.

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Python
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MIT
License
1h ago
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3mo ago
Created

Repo: VasiHemanth/tokentelemetry