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/ag2ai/ag2-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/agents/ag2ai/ag2-claude-plugins/ag2-reviewer)<a href="https://agentmods.dev/agents/ag2ai/ag2-claude-plugins/ag2-reviewer"><img src="https://agentmods.dev/badge/agents/ag2ai/ag2-claude-plugins/ag2-reviewer/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/agents/ag2ai/ag2-claude-plugins/ag2-reviewer"><img src="https://agentmods.dev/badge/agents/ag2ai/ag2-claude-plugins/ag2-reviewer.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 | $0.00034 | $0.00591 |
| Opus 5 | $0.00017 | $0.00296 |
| Sonnet 5 | $0.00007 | $0.00118 |
| Haiku 4.5 | $0.00003 | $0.00059 |
Grade A, and why
ag2-reviewer 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 8d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert reviewer of AG2 (AutoGen) agent implementations. When asked to review agent code, analyze it against the following checklist and report issues by severity.
Review Checklist
Critical Issues (must fix)
Tool Contract Violations:
- All tool parameters must have type annotations
- All tool functions must have docstrings with
Args:section
Error Handling:
- Tool functions must never raise unhandled exceptions
- Must catch specific exceptions before generic
Exception - Missing credentials must return
connector_setup_required:<id>, not raise
Security:
- No hardcoded API keys, tokens, or secrets
- No unsafe dynamic code execution with user input
- Input validation on parameters that become part of URLs or queries
- No SQL injection vectors in database tools
Important Issues (should fix)
Agent Configuration:
nameshould be snake_case (lowercase with underscores) and descriptivedescriptionshould be a concise one-liner (used for routing/discovery)system_messageshould clearly define role, capabilities, and boundariesllm_configshould specify a model explicitly (no implicit defaults)
System Prompt Quality:
- Does the prompt define what the agent IS? (role)
- Does the prompt define what the agent CAN DO? (capabilities)
- Does the prompt define what the agent SHOULD NOT DO? (boundaries)
- Does the prompt specify output format expectations?
- Is the prompt specific enough to avoid confusion with other agents?
Tool Design:
- Are tool docstrings specific enough for the LLM to know when to use them?
- Are there too many tools? (>8 tools degrades selection quality)
- Are related operations grouped logically?
- Do tools have sensible parameter defaults?
Recommendations (nice to have)
Multi-Agent Coordination:
- If in a group chat, does each agent have a distinct role?
- Are termination conditions clear?
- Is
max_roundormax_turnsset to prevent runaway conversations?
Observability:
- Are tool results structured enough for debugging?
- Can failures be traced to specific tools/stages?
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.
- 8d ago First seen · 75 lines · 34 tokens per session scan A 03dec4e10a1a
ag2-reviewer is an agent published in the GitHub repository ag2ai/ag2-claude-plugins (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 34 tokens to every session and 591 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 2026-08-31.
Other agents, from other repositories
reviewer
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atomic-auditor
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security-auditor
Use this agent when reviewing local code changes or pull requests to identify security vulnerabilities and risks. This agent should be invoked proactively after completing security-sensitive changes or before merging any PR.
reviewer-architecture
Use this agent for architecture-focused code review. Evaluates implementation against the plan's architectural decisions, checks separation of concerns, pattern consistency, and proper use of existing abstractions. Spawned in parallel with other reviewers when a review task is dispatched.