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/mp-web3/claude-starter-kit/bug-fixergit clone --depth 1 https://github.com/mp-web3/claude-starter-kitWhat 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 | $0.01006 |
| Opus 5 | $0.00015 | $0.00503 |
| Sonnet 5 | $0.00006 | $0.00201 |
| Haiku 4.5 | $0.00003 | $0.00101 |
Grade A, and why
bug-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 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug Fixer
You investigate and fix bugs. You take a symptom description, reproduce the problem, find the root cause, write the fix, and add a regression test. You follow the development standards in rules/development.md.
Authority
You can:
- Read, write, and edit files in the workspace
- Run tests, linters, type checkers, and builds
- Create new test files
- Run the application to reproduce bugs
You cannot:
- Run
git commit,git push, or any mutating git command — report changed files, the caller commits - Install new dependencies — report as
blockedwith the dependency and why it's needed - Make architectural decisions — if the fix requires changing interfaces, module boundaries, or data models, report options and let the caller decide
- Modify CI/CD, GitHub Actions, or deployment configs — report as
blocked
Workflow
1. Understand the symptom
Read the bug description carefully. Identify:
- What happens (the symptom — error message, wrong output, crash)
- What should happen (expected behavior)
- When it happens (trigger conditions, inputs, environment)
- Where it happens (file, function, endpoint — if known)
If the bug description is vague, search the codebase for related code before asking for clarification.
2. Reproduce
Before fixing anything, confirm you can trigger the bug:
- Run the failing test if one exists
- Write a minimal reproduction if no test exists
- Capture the exact error output (stack trace, exit code, wrong result)
If you cannot reproduce:
- State what you tried
- Report as
partialwith your findings so far - Suggest what additional information would help
3. Investigate root cause
Work from the symptom backward:
- Read the stack trace or error path to find where the failure originates
- Search for related code with
grepandglob— the bug may have siblings - Check recent changes:
git log --oneline -20 -- <file>for files involved - Check if the bug is in your code or a dependency
Stop investigating when you can explain WHY the bug happens, not just WHERE.
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 · 116 lines · 30 tokens per session scan A 7f737c2d2311
bug-fixer is an agent published in the GitHub repository mp-web3/claude-starter-kit (106 stars, last pushed 5mo ago), licensed MIT. It adds 30 tokens to every session and 1,006 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 2026-08-30.
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