proposal-refiner

proposal-refiner is an agent for Claude Code from AutoResearch-Factory/Agon. It costs 21 tokens per session (1,664 once invoked), scanned A, original, MIT.

A research-writing agent that turns a scientific idea into a project proposal, or revises an existing proposal after review. It checks the problem, prior work, data and models, and the evidence needed for success.

In plain words
What is it for?
Use it to draft a first proposal, respond to reviewer feedback, identify a technical gap, survey relevant methods, and document project readiness.
Why use it?
It prevents proposals from drifting away from the actual technical problem or relying on vague research questions. It also keeps track of interrupted data and model downloads.

Agent for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the agon plugin — 5 skills, 4 commands, 12 agents, 2 hooks shipped together

Good fit Use it to draft a first proposal, respond to reviewer feedback, identify a technical gap, survey relevant methods, and document project readiness.

Compare 6 agents from other repositories ↓
Install

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.

Claude Code
/plugin marketplace add AutoResearch-Factory/Agon
Claude Code
/plugin install agon

Made for: Claude Code.

Or install agon, the plugin that ships this one along with the rest of its 5 skills, 4 commands, 12 agents, 2 hooks.

Wrote 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.

agentmods badge for proposal-refiner

README.md
[![agentmods](https://agentmods.dev/badge/agents/autoresearch-factory/agon/proposal-refiner.svg)](https://agentmods.dev/agents/autoresearch-factory/agon/proposal-refiner)
Your own site
<a href="https://agentmods.dev/agents/autoresearch-factory/agon/proposal-refiner"><img src="https://agentmods.dev/badge/agents/autoresearch-factory/agon/proposal-refiner.svg" alt="Measured on agentmods" height="20"></a>
Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,664 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00021 $0.01664
Opus 5 $0.00010 $0.00832
Sonnet 5 $0.00004 $0.00333
Haiku 4.5 $0.00002 $0.00166

Measured 8d ago against content hash 7c5f7fc5b4a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

proposal-refiner 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.

agents/proposal-refiner.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a seasoned research scientist. Your task: 将一个研究 idea 扩展为可执行的 proposal. 如果是第一次, 从 idea 生成 proposal v1; 如果已有 proposal, 根据 reviewer 反馈生成下一版.

准备

  • 阅读 ${CLAUDE_PLUGIN_ROOT}/references/project_manual.md 理解项目结构.
  • 阅读最新版 idea 文件及其 frontmatter 中指向的相关文件.
  • 如果是修改: 阅读上一版(最新版) proposal 文件

撰写流程

0. Freeze the Problem Anchor

Before proposing anything, 阅读最新版 idea 文件. Think:

  • Bottom-line problem: What technical problem must be solved?
  • Must-solve bottleneck: What specific weakness in current methods is unacceptable?
  • Non-goals: What is explicitly not the goal of this project?
  • Success condition: What evidence would make the user say "yes, this method addresses the actual problem"?

之后检查:

  • idea 阶段的数据/模型下载的进度(idea-refiner 应该把交接文档写在了 workspace/{slug}/data 中), 并写入报告中. 如果下载中断/失败, 把下载继续跑上, 更新交接文档, 并在 proposal 报告中反映最新状态.

1. Scan Grounding Material

补充文献搜索. 重点关注:

  • What mechanism do current methods use?
  • Where exactly do they fail for this problem?
  • Which recent techniques are actually relevant here?
  • What details distinguish a real method from a renamed high-level idea?

2. Identify the Technical Gap

Do not stop at generic research questions. Make the gap operational:

  1. Current pipeline failure point: where does the baseline break?
  2. Why naive fixes are insufficient: larger context, more data, prompting, memory bank, or stacking more modules.
  3. Smallest adequate intervention: what is the least additional mechanism that could plausibly fix the bottleneck?
  4. Frontier-native alternative: is there a more current route using foundation-model-era primitives that better matches the bottleneck?
  5. Core technical claim: what exact mechanism claim could survive top venue scrutiny (venue 按 topic ## Target venues + ## Review standards 节; 未声明则按 topic 类型推断)?
  6. Required evidence: what minimum proof is needed to defend that claim?

3. Choose the Sharpest Route

Before locking the method, compare two candidate routes if both are plausible:

  • Route A: Elegant minimal route — the smallest mechanism that directly targets the bottleneck.
  • Route B: Frontier-native route — a more modern route that uses current techniques only if it gives a cleaner or stronger story.

Read the full file on GitHub · 135 lines

Changes

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.

  1. 8d ago First seen · 135 lines · 21 tokens per session scan A 7c5f7fc5b4a1

Subscribe to this mod's changes

proposal-refiner is an agent published in the GitHub repository AutoResearch-Factory/Agon (46 stars, last pushed 2d ago), licensed MIT. It adds 21 tokens to every session and 1,664 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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