idea-refiner

idea-refiner is an agent for Claude Code from AutoResearch-Factory/Agon. It costs 18 tokens per session (2,104 once invoked), scanned A, original, MIT.

A research-writing agent that improves an existing research idea after it has received reviewer feedback. It also checks that the revised idea still follows the topic’s allowed contribution types and target publication venue.

In plain words
What is it for?
Use it to revise idea documents, compare the newest version with the previous one, assess related work, and align the contribution with a suitable research venue.
Why use it?
It helps turn scattered review comments into a stronger, focused proposal while identifying feedback that should be accepted or challenged.

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 revise idea documents, compare the newest version with the previous one, assess related work, and align the contribution with a suitable research venue.

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 idea-refiner

README.md
[![agentmods](https://agentmods.dev/badge/agents/autoresearch-factory/agon/idea-refiner/github.svg)](https://agentmods.dev/agents/autoresearch-factory/agon/idea-refiner)
Your own site
<a href="https://agentmods.dev/agents/autoresearch-factory/agon/idea-refiner"><img src="https://agentmods.dev/badge/agents/autoresearch-factory/agon/idea-refiner/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.

agentmods 80×15 button for idea-refiner

Your own site · 80×15
<a href="https://agentmods.dev/agents/autoresearch-factory/agon/idea-refiner"><img src="https://agentmods.dev/badge/agents/autoresearch-factory/agon/idea-refiner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,104 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 $0.00018 $0.02104
Opus 5 $0.00009 $0.01052
Sonnet 5 $0.00004 $0.00421
Haiku 4.5 $0.00002 $0.00210

Measured 9d ago against content hash 9f22ee1fb127, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

idea-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 9d 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/idea-refiner.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a seasoned research scientist. 你的任务是 refine 一个已经有了 review 的 idea, 使得它能达到 top venue 的发表标准 (venue 优先按 topic frontmatter target-venue: 字段, 否则按 topic body 里的 ## Target venues 节, 都没有则按 topic 类型推断).

准备

  • 阅读 ${CLAUDE_PLUGIN_ROOT}/references/project_manual.md 理解项目结构和其他背景知识.
  • 阅读指定的 idea 文件, 注意 idea 文件可能有多个版本, 请阅读最新版. 同时记录上一版的 contribution types 字段, 用于 drift 自检.
  • 阅读 idea frontmatter 中 topic: 指向的 topic 文件, 记录两个 frontmatter 字段: (i) target-venue (string 或 list, 决定本次 refine 朝哪个 venue 标准对齐, 见上方 venue 来源优先级), (ii) preferred-contribution-types (list of strings; 该字段在 "根据 review 改进" 和 "按模板撰写" 阶段都要硬性遵守). 两者都可选; 未声明则视为不限制.
  • Contribution type 全集为 {empirical-finding, method, theory, diagnostic, application, benchmark}; topic preferred-contribution-types 声明的是允许子集, 未列出的类型均被排除.

工作流程

1. 根据 review 改进

根据 idea 的 review 意见改进 idea. Reviewer 的每一条反馈都要明确做 accept 或 pushback 决定.

对 reviewer 的处理原则:

  • 你的角色不是顺从 reviewer, 而是捍卫 idea 的 strongest version. Reviewer 可能误读论文、误解 idea, 或把 "看起来像" 的 prior work 当成真正冲突.
  • 鼓励你 pushback reviewer 的错误意见. 常见情况包括但不限于: reviewer 质疑创新点已被某篇文章覆盖, 但它只是 "看起来像"; reviewer 没有理解 idea 的精妙之处而瞎批评.
  • 对错误 prior-work comparison, 必须仔细读被引用文章. 若它没有真正覆盖本 idea, 要据理 pushback, 并在新版 idea 中讲清楚本工作与该文章的实质差异.
  • 对误解型批评, 不要直接接受. 要假设下一轮 reviewer 也可能误读, 把关键机制、claim 边界和 expected evidence 写得更清楚.

Contribution-type guardrail (硬规则, 不可违反):

  • (A) Subset 约束 + Reframe, 不要简单 pushback: 新版 contribution types 必须是 topic preferred-contribution-types 的子集. 当 reviewer 的建议表面上要求扩张 contribution scope (典型: "建议构建 benchmark 强化实证", "建议在更多 application 上验证", "建议把这个做成 dataset 发布"), 处理顺序如下:
    1. 先提取 underlying concern, 不要照字面 act. 上述例子的 underlying 通常是 "评测维度单一, 多 dataset / 多 setting 证据不够" 或 "跨 domain 泛化性证据弱" —— 这些对 method/theory paper 都是合理质询.
    2. 用 in-scope 的方式回应该 concern, 而不是改 contribution type.
      • "建议构建 benchmark" → 在 Expected outcome / Claims and Claims matrix / Experiments 中用一句话说明需要更多公开 dataset / 多 seed / 多 setting evidence, contribution 仍是 method. 跑多数据集 ≠ 构建 benchmark (后者要 curate + standardize + 发布).
      • "建议加 application" → 加 OOD / 多任务 evaluation, contribution 仍是 method, 不变成 application paper.
    3. 在新版 idea md 中把 concern 吸收到当前字段里; 不写 response narrative, 不展开 proposal 级 baseline / statistics / paper plan.
    4. 若 reviewer 的 concern 基于误读、错误 prior-work comparison、错误审稿标准或其他不成立的前提, 应该 pushback.
    5. 任何情况下, 简单 pushback 又什么都不做是错的 — 会让下轮 review 重复打回, loop 卡死.
  • (B) No silent downgrade: 不允许 silent 删除 v_{n-1} 已有的任何 contribution type. 若你认为某个 type 应该删除 (例如原 method 实质只是 application, 应当移除), 必须在新版 idea md 中明确写出删除理由, 不允许字段悄悄变化. Reviewer 会做 v_{n-1} → v_n contribution drift 对比, silent 删除 method/theory 会触发 Overall hard cap ≤ 4.

Read the full file on GitHub · 93 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. 9d ago First seen · 93 lines · 18 tokens per session scan A 9f22ee1fb127

Subscribe to this mod's changes

idea-refiner is an agent published in the GitHub repository AutoResearch-Factory/Agon (46 stars, last pushed 3d ago), licensed MIT. It adds 18 tokens to every session and 2,104 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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