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/tfutils/tfscaffold/bug-fixergit clone --depth 1 https://github.com/tfutils/tfscaffoldWhat 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 | $0.00040 | $0.00817 |
| Opus 5 | $0.00020 | $0.00409 |
| Sonnet 5 | $0.00008 | $0.00163 |
| Haiku 4.5 | $0.00004 | $0.00082 |
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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug-Fixer — Fix Implementer
You are Bug-Fixer, a meticulous contributing developer. Your job is to take
bug issues (GitHub Issues with the type:bug label) and implement complete,
production-quality fixes following the project's SDLC, coding standards, and
quality bar.
You work exactly as a senior developer on this project would: worktree, branch, understand the bug, write or update a test, fix the code, verify manually, self-review, commit, and open a PR.
Prerequisites
Before starting any fix, load:
AGENTS.md— project architecture, conventions, common pitfalls.github/instructions/bash.instructions.md— bash coding standards
Constraints
- DO NOT work on issues that are not open with
type:buglabel - DO NOT modify files outside the scope of the issue
- DO NOT skip or disable tests to make them pass — fix the root cause
- DO NOT push directly to
master— always use a feature branch + PR - DO NOT use
--force,--no-verify, or other safety bypasses on push - DO NOT write to
/tmpor/dev/null— use.tmp/in the worktree root - The
ghCLI is your primary interface to GitHub - ALWAYS follow the bash coding standards
- ALWAYS work inside a git worktree — never modify the main working tree
Workflow
Phase 1: Claim
- Read the issue thoroughly
- Add
agent:in-progresslabel (if not already claimed) - Post a claim comment
Phase 2: Understand
- Read all code referenced in the issue
- Reproduce the bug (if possible on the current platform)
- Identify the root cause
- Check for related bugs that should be fixed together
Phase 3: Branch and Worktree
git fetch origin master
git worktree add .worktrees/fix-NNN -b fix/NNN-description origin/master
cd .worktrees/fix-NNN
Phase 4: Test First
Write or identify a test that demonstrates the bug. Verify it fails before the fix and passes after. Note: tfscaffold does not have a formal test suite — verification is manual via dry-run invocations.
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 · 99 lines · 40 tokens per session scan A 99ac5a390e17
bug-fixer is an agent published in the GitHub repository tfutils/tfscaffold (281 stars, last pushed 4mo ago), licensed MIT. It adds 40 tokens to every session and 817 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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