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/AleksandarBisevac/claude-pluginsWrote 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/aleksandarbisevac/claude-plugins/code-review)<a href="https://agentmods.dev/commands/aleksandarbisevac/claude-plugins/code-review"><img src="https://agentmods.dev/badge/commands/aleksandarbisevac/claude-plugins/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/aleksandarbisevac/claude-plugins/code-review"><img src="https://agentmods.dev/badge/commands/aleksandarbisevac/claude-plugins/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 | $0.00004 | $0.00172 |
| Opus 5.5 | $0.00002 | $0.00069 |
| Sonnet 5.5 | $0.00001 | $0.00034 |
| Haiku 4.5 | $0.00000 | $0.00017 |
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 1mo 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.
What it actually says
MODE: $ARGUMENTS
If Mode is one of the following, adjust the review as described:
- MODE == BUGS: Focus ONLY on logical or other bugs.
- MODE == SECURITY: Focus ONLY on security issues.
- MODE = PERFORMANCE: Focus ONLY performance issues.
MODE can also be set to a combination like "BUGS,SECURITY" etc => Perform the combined review in that case.
If MODE is set to anything else or nothing at all, perform a thorough, general code review.
Perform an in-depth code review of the entire codebase.
Carefully and thoroughly explore the codebase file-by-file to find potential issues and improvements.
Don't rush it, instead make sure you fully understand the code structure and architecture.
Create a detailed report of all your findings.
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.
- 1mo ago First seen · 25 lines · 4 tokens per session scan A 8e50194a87c3
code-review is a command published in the GitHub repository AleksandarBisevac/claude-plugins (4 stars, last pushed 3d ago), licensed MIT. It adds 4 tokens to every session and 172 once invoked, about $0.0000 per session on Opus 5.5. 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-feedback
Review a given code review markdown document, GitHub PR review, or inline feedback — corroborate each point against actual code, then implement valid changes.
address
Address code review feedback — corroborate, validate, and implement changes from a review's final.md.
sync-reviewers
Sync reviewer metadata from markdown files to reviewers-meta.json for the dashboard.
translate-review-to-single-human
Translate a multi-reviewer code review into a single human-voice GitHub PR comment.
create-reviewer
Create a new custom reviewer from a natural language description.
map
Generate a Code Review Map to help navigate large, complex changesets.