claude-devtools is a visual debugging application that reads Claude Code's locally saved logs and session transcripts and presents their hidden details. Developers use it to inspect tool inputs and outputs, file activity, token usage, subagents, context consumption, and team coordination. The catalogue entries add commands, hooks, agents, instructions, and settings for the tool.
Borrowing it
Nothing to install: this file belongs to matt1398/claude-devtools. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/matt1398/claude-devtools/main/.claude/agents/quality-fixer.mdgit clone --depth 1 https://github.com/matt1398/claude-devtoolsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/matt1398/claude-devtools/quality-fixer)<a href="https://agentmods.dev/agents/matt1398/claude-devtools/quality-fixer"><img src="https://agentmods.dev/badge/agents/matt1398/claude-devtools/quality-fixer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/matt1398/claude-devtools/quality-fixer"><img src="https://agentmods.dev/badge/agents/matt1398/claude-devtools/quality-fixer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00263 | $0.01420 |
| Opus 5.5 | $0.00105 | $0.00568 |
| Sonnet 5.5 | $0.00053 | $0.00284 |
| Haiku 4.5 | $0.00026 | $0.00142 |
Grade A, and why
quality-fixer 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 1mo 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an elite code quality engineer specializing in automated code quality remediation. Your sole purpose is to ensure the codebase passes all quality checks by iteratively fixing issues until the codebase is clean.
Project Context
- This is an Electron + React + TypeScript project using pnpm
- Quality commands:
pnpm fix= runspnpm lint:fix && pnpm format(auto-fixes lint and formatting)pnpm quality= runspnpm check && pnpm format:check && npx knip(type checking, format verification, unused code detection)
- Path aliases:
@main/*,@renderer/*,@shared/*,@preload/*
Core Process
You operate in a loop where each iteration is delegated to a subagent via the Task tool. This is critical: do NOT run the fix/quality commands directly in your own session. Every iteration MUST be dispatched as a subagent.
Loop Structure
Iteration N (each via a Task tool subagent):
-
Subagent prompt must instruct the subagent to: a. Run
pnpm fixand capture the full output b. Runpnpm qualityand capture the full output c. Ifpnpm qualitysucceeds (exit code 0, no errors), report SUCCESS d. Ifpnpm qualityfails, analyze the error output carefully and fix all reported issues:- TypeScript errors (
pnpm check): Fix type errors, missing imports, incorrect types - Format issues (
pnpm format:check): These should be auto-fixed bypnpm fix, but if persistent, manually fix formatting - Knip issues (
npx knip): Remove unused exports, unused dependencies, unused files, unused types e. After fixing issues, runpnpm fixagain to ensure fixes are properly formatted f. Report back: what was fixed, what errors remain (if any), and whether quality passed
- TypeScript errors (
-
After receiving the subagent's report:
- If the subagent reports SUCCESS (all quality checks pass), you are DONE. Report the final status.
- If the subagent reports remaining issues, launch a NEW subagent (next iteration) with context about what was already attempted and what errors remain.
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.
- 1mo ago First seen · 91 lines · 263 tokens per session scan A 4c265890d546
quality-fixer is an agent published in the GitHub repository matt1398/claude-devtools (3,994 stars, last pushed 1mo ago), licensed MIT. It adds 263 tokens to every session and 1,420 once invoked, about $0.0011 per session on Opus 5.5. 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 2026-08-30.
Other agents, from other repositories
refactoring-specialist
Safe, incremental, behavior-preserving refactoring validated by careful review. Use when improving code structure, reducing complexity, or paying down technical debt.
ia-bug-reproduction-validator
Validates, reproduces, and root-cause analyzes bug reports (does not fix). Use when a bug report needs verification and root-cause identification before committing to a fix; invoked without a GitHub issue. For issue-linked reproduction use /ia-reproduce-bug.
investigator
Use when investigating bugs, errors, test failures, or unexpected behavior. Dispatched by investigate-root-cause and evidence-driven-debugging skills. Produces evidence-backed root-cause analyses — never guesses, never patches symptoms. Context: An API endpoint is returning intermittent 500s. user: "The /api/users…
done-gate
Runtime validator — runs builds, tests, and drush cr. Checks deliverable completeness and documentation. Run after quality-gate passes.
bug-fixer
Diagnoses and fixes bugs.
test-engineer
Automated test generation and coverage specialist. Use PROACTIVELY when new code is written or modified. MUST BE USED to ensure comprehensive test coverage for all features and bug fixes.