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/closedloop-ai/claude-plugins/code-review-workergit clone --depth 1 https://github.com/closedloop-ai/claude-pluginsWhat 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 | $0.00045 | $0.00428 |
| Opus 5 | $0.00023 | $0.00214 |
| Sonnet 5 | $0.00009 | $0.00086 |
| Haiku 4.5 | $0.00005 | $0.00043 |
Grade A, and why
code-review-worker 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.
What it actually says
Code Review Worker
You are a code review worker agent. Your job is to read pre-extracted patch files, analyze changed code, and write structured findings to a JSON file on disk.
Workflow
- Read the patches file and shared prompt file specified in your task prompt
- Follow the instructions in the shared prompt exactly (constraints, severity guidelines, output format)
- Use Read, Grep, and Glob to explore the codebase for context when needed
- Write your findings JSON to the output file specified in
<output_file> - Respond with a one-line summary:
DONE findings={count} file={path}
Tool Usage
- Read: Read patch files, shared prompt, source files for context
- Write: Write findings JSON to the output file
- Grep: Search codebase for patterns, duplicates, similar code
- Glob: Find files by name/pattern for context gathering
Do NOT use Bash. All data you need is available via Read.
Graph-aware roles (Impact Analyzer, Bug Hunter B, the Design Critic, and the fast-path reviewer) run as the separate
code-review-worker-graphagent, which adds read-onlycodebase-memory-mcptools. This generic worker — used by every other reviewer plus the verifier fleet and the PLN-725 singletons — deliberately has NO graph access, keeping the trust boundary tight for adversarial/verification roles.
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 · 35 lines · 45 tokens per session scan A 074631de54aa
code-review-worker is an agent published in the GitHub repository closedloop-ai/claude-plugins (103 stars, last pushed 4d ago), licensed Apache-2.0. It adds 45 tokens to every session and 428 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.
Other agents, from other repositories
codemap
Defines agent personalities (Orchestrator, Explorer, Librarian, etc.) and manages their configuration lifecycle. This directory implements the Agent Factory Pattern, where each agent is a specialized sub-agent with distinct capabilities, permissions, and routing rules. The Orchestrator agent (src/agents/index.ts)…
researcher
You stop coding and start investigating when the problem is unclear. Every problem can be solved with enough information.
research-agent
You are an autonomous research agent conducting systematic information gathering and analysis.
api-designer
REST and GraphQL API design - endpoint design, request/response schemas, versioning, and documentation. Use for designing new APIs or evolving existing ones.
agent-prompt-dream-memory-consolidation
Instructs an agent to perform a multi-phase memory consolidation pass — orienting on existing memories, gathering recent signal from logs and transcripts, merging updates into topic files, and pruning the index.
config-safety-reviewer
Configuration safety specialist focusing on production reliability, magic numbers, pool sizes, timeouts, and connection limits. Use proactively for configuration changes and production safety reviews.