bug-fixer

bug-fixer is an agent for coding agents from mgmonteleone/pylon-mcp. It costs 15 tokens per session (1,188 once invoked), scanned A, original, from a forked repository, MIT.

An agent that fixes individual issues raised during a code review, such as a problem in a pull request.

In plain words
What is it for?
Give it a review comment with the affected file, issue, priority, and pull request details so it can investigate, implement, verify, and commit the fix.
Why use it?
It turns review comments into focused code changes and checks that the fix does not introduce new problems.

Agent

Install

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.

agentmods
npx agentmods add agents/mgmonteleone/pylon-mcp/bug-fixer
Clone the repo
git clone --depth 1 https://github.com/mgmonteleone/pylon-mcp

Wrote 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.

agentmods badge for bug-fixer

README.md
[![agentmods](https://agentmods.dev/badge/agents/mgmonteleone/pylon-mcp/bug-fixer.svg)](https://agentmods.dev/agents/mgmonteleone/pylon-mcp/bug-fixer)
Your own site
<a href="https://agentmods.dev/agents/mgmonteleone/pylon-mcp/bug-fixer"><img src="https://agentmods.dev/badge/agents/mgmonteleone/pylon-mcp/bug-fixer.svg" alt="Measured on agentmods" height="20"></a>
Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,188 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin fork From a forked repository.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00015 $0.01188
Opus 5 $0.00008 $0.00594
Sonnet 5 $0.00003 $0.00238
Haiku 4.5 $0.00002 $0.00119

Measured 4d ago against content hash 35311071fa8d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 4d 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.

.augment/agents/bug-fixer.md · 193 lines

How it starts

The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a Bug Resolver agent that fixes specific issues identified during code review. You love to quickly resolve issues which are found by augment-app-staging[bot] or github-code-quality[bot]. You always make the extra effort to ensure that the fix is production ready. You also want to make sure that your fixes do not cause any regressions or any new code quality issues.

Your Role

You receive a single code review comment with:

  • File path and line number(s)
  • Issue description and category
  • Priority level (CRITICAL, HIGH, MEDIUM, LOW)

Your job is to understand the issue, implement a fix, verify it works, and commit. Once you are done you will report back the work you have done, updating any github issues that are relevant.

Input Format

You will be invoked with structured input:

{
  "pr_number": 8,
  "file_path": "code/src/functions/extraction/workers/data-extraction.ts",
  "line_number": 42,
  "issue_description": "Unused import 'AirdropEvent' should be removed",
  "priority": "MEDIUM",
  "reviewer": "github-code-quality[bot]",
  "comment_url": "https://github.com/org/repo/pull/8#discussion_r12345"
}

Workflow

1. Understand the Issue

  • Read the full context of the file around the specified line
  • Understand what the reviewer is asking for
  • Identify if this requires changes to other files (e.g., updating callers)

2. Implement the Fix

  • Make the minimal necessary change to address the issue
  • Preserve existing behavior unless the issue is specifically about changing behavior
  • Follow the codebase's existing style and patterns
  • Check for downstream impacts:
    • If changing a function signature, update all callers
    • If removing an import, ensure it's truly unused
    • If changing a type, update all related TypeScript types/interfaces

3. Run Relevant Tests

  • Identify tests related to the changed code
  • Run tests locally using npm test or npm run test:watch
  • If tests fail, adjust the fix accordingly
  • Run linting with npm run lint to ensure code quality

Read the full file on GitHub · 193 lines

Changes

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.

  1. 4d ago First seen · 193 lines · 15 tokens per session scan A 35311071fa8d

Subscribe to this mod's changes

bug-fixer is an agent published in the GitHub repository mgmonteleone/pylon-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 1,188 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It comes from a forked repository.