Borrowing it
Nothing to install: this file belongs to MilindGaharwar/fettle. 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/MilindGaharwar/fettle/main/.opencode/commands/fettle-review.mdgit clone --depth 1 https://github.com/MilindGaharwar/fettleWrote 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/commands/milindgaharwar/fettle/fettle-review)<a href="https://agentmods.dev/commands/milindgaharwar/fettle/fettle-review"><img src="https://agentmods.dev/badge/commands/milindgaharwar/fettle/fettle-review.svg" alt="Measured on agentmods" 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 | $0.00014 | $0.00196 |
| Opus 5 | $0.00007 | $0.00098 |
| Sonnet 5 | $0.00003 | $0.00039 |
| Haiku 4.5 | $0.00001 | $0.00020 |
Grade A, and why
fettle-review 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- review — 86% identical, 5 lines differ
What it actually says
/fettle:review
Run an independent cross-review of a file using a different LLM.
Usage
When the user invokes /fettle:review:
- Identify the file to review (ask if not obvious from context).
- Run:
python3 -m fettle.review --file PATH - Present the review findings.
Configuration
# .fettle.toml
[review]
provider = "ollama" # ollama | proxy | openai
endpoint = "http://localhost:11434/v1"
model = "llama3.2"
Purpose
Gets a "second opinion" from a different model. Useful for:
- Critical code paths
- Security-sensitive changes
- Before merging complex PRs
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.
- 6d ago First seen · 37 lines · 14 tokens per session scan A 1c6eb89795cd
fettle-review is a command published in the GitHub repository MilindGaharwar/fettle (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 14 tokens to every session and 196 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
done
Finish a task - document, create PR or merge, close.
afe
Evaluate feature - code review or comparison (shortcut for feature-eval).
note
Add a note to the active task - progress, decisions, context. --session (aliases --snapshot, --pre-compact, --compact) writes a resume-grade session snapshot without ending the session.
pr-ready
Run the project's pre-commit review loop to determine whether the current branch is ready to push — lint, tests, parallel pr-review-toolkit agents plus an over-engineering audit, fix-and-re-run until convergence.
address-pr-feedback
Systematically address PR review comments. Fetches all threads, categorizes by status (acknowledged, silently fixed, unaddressed), and guides user through posting replies and implementing fixes with explicit approval.