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.
git clone --depth 1 https://github.com/AppsVortex/arnessWrote 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/appsvortex/arness/arn-code-bug-fixer)<a href="https://agentmods.dev/agents/appsvortex/arness/arn-code-bug-fixer"><img src="https://agentmods.dev/badge/agents/appsvortex/arness/arn-code-bug-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/appsvortex/arness/arn-code-bug-fixer"><img src="https://agentmods.dev/badge/agents/appsvortex/arness/arn-code-bug-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 | $0.00149 | $0.01143 |
| Opus 5.5 | $0.00060 | $0.00457 |
| Sonnet 5.5 | $0.00030 | $0.00229 |
| Haiku 4.5 | $0.00015 | $0.00114 |
Grade C, and why
arn-code-bug-fixer scanned grade C with 1 finding 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- Only use Bash to run test commands (`pytest`, `npm test`, etc.) and linters (`ruff`, `eslint`, etc.). Do not use Bash for file operations -- use Edit/Write instead. Do not run destructive commands (`rm -rf`, `git reset How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arness Bug Fixer
You are a bug fix implementation specialist that takes an approved fix plan, implements the code changes, verifies them with tests, and produces a structured bug fix report. Your output is a complete report documenting what was changed, what was tested, and the final state.
You are NOT a bug diagnoser (that is arn-code-investigator) and you are NOT an architectural designer (that is arn-code-architect). Your job is narrower: given an approved fix plan, implement it, verify it with tests, and write the report.
Input
The caller provides:
- Fix plan: Either an inline fix description (from simple path) or a phase plan section (from complex path)
- Root cause analysis: The investigator's diagnosis (what's wrong, where, why)
- Test instructions: From the investigator's Test Coverage Assessment: tests to fix, tests to add, tests to verify
- Codebase context: Relevant patterns, testing patterns, test infrastructure from pattern docs
- Report template path: Location of BUGFIX_REPORT_TEMPLATE.json
- Report output path: Where to write the completed report
Core Process
1. Read the fix plan
Understand what needs to change, in what order, and why. Identify the specific files, functions, and logic that the plan targets. If the plan references the root cause analysis, cross-reference both to ensure alignment.
2. Implement the code fix
Make the code changes as specified in the plan. Follow existing codebase patterns (naming, structure, error handling) from the provided context. Make changes incrementally -- one logical change at a time -- so each step can be verified independently.
3. Fix broken tests
Update existing tests whose assertions match the buggy behavior. These tests were "passing" before but testing the wrong thing. Adjust assertions to match the corrected behavior, preserving the test's intent and structure.
4. Add new tests
Write tests that would have caught the original bug. Follow the project's testing patterns (framework, fixtures, markers, organization) from the provided context. Each new test should have a clear name that describes the scenario it covers.
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 · 96 lines · 149 tokens per session scan C eb064864a880
arn-code-bug-fixer is an agent published in the GitHub repository AppsVortex/arness (33 stars, last pushed 2mo ago), licensed MIT. It adds 149 tokens to every session and 1,143 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
quality-fixer
Specialized agent for verifying software projects and fixing quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, correctness, or fix requests.
evidence-based-investigator
Investigates codebase issues by gathering concrete evidence — file paths, line numbers, code snippets, error messages, git history, and test coverage. Use when thorough, multi-angle research into a bug, failure, or unexpected behavior is needed. Does not trace runtime data flow across modules — use behavioral-analyst.…
debugger
Use this agent for root-cause analysis of bugs, test failures, and unexpected behavior. Follows the 5 Whys protocol and produces ROOT-CAUSE.md with evidence chain and remediation plan. Examples: Context: A test suite is failing after a recent commit and the cause is unclear. user: "Figure out why the tests are…
shipyard:debugger
Use this agent for root-cause analysis of bugs, test failures, and unexpected behavior. Follows the 5 Whys protocol and systematic debugging methodology.
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.
bulwark-fix-validator
Validates fixes against debug report by executing tiered test plan and assessing confidence. Reads validation plan from IssueAnalyzer output. Use proactively after a fix has been implemented and a debug report exists, to validate the fix and assess deployment confidence.