ODS is a system for turning a PC, Mac, or Linux computer into a private local AI server, meaning a machine that runs models and related AI services itself. It supports local model inference, chat, voice, agents, workflows, document retrieval, search, and image generation. The catalogue includes commands and an instruction for operating or configuring this system.
Borrowing it
Nothing to install: this file belongs to Osmantic/ODS. 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/Osmantic/ODS/main/.claude/commands/code-review.mdgit clone --depth 1 https://github.com/Osmantic/ODSWrote 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/osmantic/ods/code-review)<a href="https://agentmods.dev/commands/osmantic/ods/code-review"><img src="https://agentmods.dev/badge/commands/osmantic/ods/code-review/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/osmantic/ods/code-review"><img src="https://agentmods.dev/badge/commands/osmantic/ods/code-review.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 | $0.04038 |
| Opus 5.5 | $0.00000 | $0.01615 |
| Sonnet 5.5 | $0.00000 | $0.00808 |
| Haiku 4.5 | $0.00000 | $0.00404 |
Grade A, and why
code-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 2mo 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 — 494 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Git Code Review with Multi-Model Consensus
Perform comprehensive code review using PAL MCP multi-model consensus. Reviews recent commits, staged changes, or branch comparisons with focus on security, quality, performance, and architecture.
Arguments
$ARGUMENTS- Review configuration:commits=N- Number of recent commits to review (default: 5)--staged- Review only staged changes instead of commits--branch <target>- Compare current branch against target branch (e.g.,main)--focus <area>- Focus area:security,performance,quality,architecture, orfull(default:full)--post-pr- Post review as PR comment if in PR context
Philosophy: Ask Early, Ask Often
This skill should liberally use AskUserQuestion at every decision point. Code review is subjective — what matters depends on context, and assumptions about reviewer priorities are frequently wrong. The cost of asking is low; the cost of reviewing the wrong scope or missing what the user cares about is high. Specifically:
- Before reviewing — confirm the review scope and what the user cares about
- When the diff is large — let the user choose what to focus on first
- When categorization is ambiguous — ask about severity levels
- When models disagree — let the user break the tie on issue severity
- After findings — ask what to do next (fix, re-review, post to PR)
- When tradeoffs exist — present them explicitly instead of picking silently
The user should feel like they're directing the review, not receiving a fire-and-forget report.
Workflow
1. Parse Arguments
Extract configuration from $ARGUMENTS:
- Default:
commits=5,focus=full - Flags:
--staged,--branch,--focus,--post-pr
Determine review mode (mutually exclusive):
| Mode | Trigger | Description |
|---|---|---|
| Commits | Default or commits=N |
Review last N commits |
| Staged | --staged flag |
Review staged changes only |
| Branch | --branch <target> |
Compare against target branch |
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.
- 2mo ago First seen · 494 lines · 0 tokens per session scan A 2d53b26c9a9e
code-review is a command published in the GitHub repository Osmantic/ODS (7,712 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 4,038 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 2026-08-30.
Other commands, from other repositories
review
Review code changes against project conventions.
code-review
Code review a pull request.
quality-gate
Run the ECC quality pipeline on demand for a file or project scope.
review-artifact-comments
Works through the review comments written into a task artifact (plan or research under .ork/tasks/TASK/): lists the open ones, asks how to proceed, then replies, resolves or hands off to iterate-plan or iterate-research, and approves the artifact once nothing is open. Use when a reviewer has commented on an artifact…
review
Review a skill for quality before merge.
review
Review the current diff against project memory.