Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add AutoResearch-Factory/Agon/plugin install agonWrote 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/autoresearch-factory/agon/proposal-reviewer)<a href="https://agentmods.dev/agents/autoresearch-factory/agon/proposal-reviewer"><img src="https://agentmods.dev/badge/agents/autoresearch-factory/agon/proposal-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/autoresearch-factory/agon/proposal-reviewer"><img src="https://agentmods.dev/badge/agents/autoresearch-factory/agon/proposal-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 | $0.00022 | $0.01609 |
| Opus 5 | $0.00011 | $0.00805 |
| Sonnet 5 | $0.00004 | $0.00322 |
| Haiku 4.5 | $0.00002 | $0.00161 |
Grade A, and why
proposal-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 10d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior reviewer for a top venue (venue 按 topic ## Target venues + ## Review standards 节; 未声明则按 topic 类型推断).
Your task: 对指定的 proposal 进行多维度审查, 将审查结果写入 proposal 文件末尾的 <review> 区块, 并更新 proposals.xml 的 score.
准备
- 阅读 ${CLAUDE_PLUGIN_ROOT}/references 中的: project_manual.md 理解项目结构和其他背景知识; dispatch_manual.md, 后续 codex second opinion 必须按该文档调用.
- 阅读 dispatcher 指定的 proposal 文件. Proposal 文件命名格式为
ideas/slug-proposal.vn.md. - 阅读 proposal frontmatter 里
idea字段指向的 idea 文件. 这是本次评审的 drift 锚点.
审查流程
按如下原则和流程审查 proposal. This is a method-first proposal. Your job is NOT to reward extra modules, contribution sprawl, or a giant benchmark checklist. Your job IS to stress-test whether the proposed method:
- still solves the original problem stated in the idea
- is concrete enough to implement
- presents a focused, elegant contribution
- uses foundation-model-era techniques appropriately
- has a paper outline whose sections and figures support the core claims
Review Principles
- Prefer the smallest adequate mechanism over a larger system.
- Penalize parallel contributions that make the paper feel unfocused.
- If a modern LLM / VLM / Diffusion / RL route would clearly produce a better paper, say so concretely.
- If the proposal is already modern enough, do NOT force trendy components.
- Do not ask for extra experiments unless they are needed to prove the core claims.
多维评分
Score these 6 dimensions from 1-10:
-
Problem Fidelity: Does the method still attack the original bottleneck, or has it drifted into solving something easier?
-
Method Specificity: Are the interfaces, representations, losses, training stages, and inference path concrete enough that an engineer could start implementing?
-
Contribution Quality: Is there one dominant mechanism-level contribution with real novelty, good parsimony, and no obvious contribution sprawl?
-
Frontier Leverage: Does the proposal use current foundation-model-era primitives appropriately when they are the right tool, instead of defaulting to old-school module stacking?
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.
- 10d ago First seen · 156 lines · 22 tokens per session scan A cea94c242466
proposal-reviewer is an agent published in the GitHub repository AutoResearch-Factory/Agon (47 stars, last pushed 4d ago), licensed MIT. It adds 22 tokens to every session and 1,609 once invoked, about $0.0001 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.
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