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/yezannnnn/agentGroupWrote 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/yezannnnn/agentgroup/code-rabbit)<a href="https://agentmods.dev/commands/yezannnnn/agentgroup/code-rabbit"><img src="https://agentmods.dev/badge/commands/yezannnnn/agentgroup/code-rabbit/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/commands/yezannnnn/agentgroup/code-rabbit"><img src="https://agentmods.dev/badge/commands/yezannnnn/agentgroup/code-rabbit.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 | $0.00000 | $0.00754 |
| Opus 5 | $0.00000 | $0.00377 |
| Sonnet 5 | $0.00000 | $0.00151 |
| Haiku 4.5 | $0.00000 | $0.00075 |
Grade A, and why
code-rabbit 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:
- code-rabbit — 100% identical, 1 lines differ
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CodeRabbit Review Handler
Process CodeRabbit review comments with context-aware discretion.
Usage
/code-rabbit
Then paste one or more CodeRabbit comments.
Instructions
1. Initial Context
Inform the user:
I'll review the CodeRabbit comments with discretion, as CodeRabbit doesn't have access to the entire codebase and may not understand the full context.
For each comment, I'll:
- Evaluate if it's valid given our codebase context
- Accept suggestions that improve code quality
- Ignore suggestions that don't apply to our architecture
- Explain my reasoning for accept/ignore decisions
2. Process Comments
Single File Comments
If all comments relate to one file:
- Read the file for context
- Evaluate each suggestion
- Apply accepted changes in batch using MultiEdit
- Report which suggestions were accepted/ignored and why
Multiple File Comments
If comments span multiple files:
Launch parallel sub-agents using Task tool:
Task:
description: "CodeRabbit fixes for {filename}"
subagent_type: "general-purpose"
prompt: |
Review and apply CodeRabbit suggestions for {filename}.
Comments to evaluate:
{relevant_comments_for_this_file}
Instructions:
1. Read the file to understand context
2. For each suggestion:
- Evaluate validity given codebase patterns
- Accept if it improves quality/correctness
- Ignore if not applicable
3. Apply accepted changes using Edit/MultiEdit
4. Return summary:
- Accepted: {list with reasons}
- Ignored: {list with reasons}
- Changes made: {brief description}
Use discretion - CodeRabbit lacks full context.
3. Consolidate Results
After all sub-agents complete:
📋 CodeRabbit Review Summary
Files Processed: {count}
Accepted Suggestions:
{file}: {changes_made}
Ignored Suggestions:
{file}: {reason_ignored}
Overall: {X}/{Y} suggestions applied
4. Common Patterns to Ignore
- Style preferences that conflict with project conventions
- Generic best practices that don't apply to our specific use case
- Performance optimizations for code that isn't performance-critical
- Accessibility suggestions for internal tools
- Security warnings for already-validated patterns
- Import reorganization that would break our structure
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 · 120 lines · 0 tokens per session scan A b15d82f26f74
code-rabbit is a command published in the GitHub repository yezannnnn/agentGroup (149 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 754 tokens. 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 2026-09-03.
Other commands, from other repositories
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
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.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.
argos
A command for checking whether an implementation matches its design deliverables. Its Korean description compares the work to the design as part of a completion inspection.