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Research
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/research-idea-convergence

Generates 2-4 candidate research directions from survey results, presents them with pros/cons for user selection, and converges to a publishable angle.

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oh-my-paper
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$ npx -y skills add LigphiDonk/Oh-my--paper --skill research-idea-convergence --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/research-idea-convergence

Context preview

The summary Claude sees to decide when to auto-load this skill.

Generates 2-4 candidate research directions from survey results, presents them with pros/cons for user selection, and converges to a publishable angle.

SKILL.md

research-idea-convergence.SKILL.md
id: research-idea-convergence
name: Research Idea Convergence
version: 1.0.0
description: |-
  Generates 2-4 candidate research directions from survey results, presents them with pros/cons for user selection, and converges to a publishable angle.
stages: ["ideation"]
tools: ["read_file", "search_project", "write_file"]
summary: |-
  Interactive research direction selection. Reads survey reports and gap analysis, generates 2-4 candidate research directions with pros/cons/feasibility, and waits for user selection before writing the final publishable angle.
primaryIntent: ideation
intents: ["ideation", "research"]
capabilities: ["research-planning"]
domains: ["academic"]
keywords: ["research-idea-convergence", "idea selection", "research direction", "publishable angle", "candidate", "convergence", "interactive", "ideation"]
source: builtin
status: verified
resourceFlags:
  hasReferences: false
  hasScripts: false
  hasTemplates: true
  hasAssets: false
  referenceCount: 0
  scriptCount: 0
  templateCount: 1
  assetCount: 0
  optionalScripts: false

Research Idea Convergence

Canonical Summary

Interactive research direction selection for academic projects. Generates multiple candidate research directions from survey/literature results, presents them with structured comparison for user selection, then converges to a final publishable angle.

Trigger Rules

Use this skill when:

  • The project enters the **ideation** stage after completing the survey stage
  • The user asks about research direction, publishable angle, or idea selection
  • The current task involves generating or selecting a research direction

**Do NOT use this skill when:**

  • The user has already decided on a specific research direction and just wants to refine it
  • The project is still in the survey stage (use survey skills instead)

Execution Contract

  • Resolve every relative path from this skill directory first.
  • Do not write generated artifacts back into the skill directory; save them inside the active project workspace.
  • **Never skip the user selection checkpoint** — this is the core purpose of this skill.

Working Rules

1. Read existing survey outputs before generating candidates. 2. Generate **2-4 candidate directions**, no more, no fewer. 3. Each candidate must be concrete enough to evaluate (not vague platitudes). 4. **[USER_CHECKPOINT]** — Always stop and wait for user selection. Never auto-select. 5. Only after user confirmation, write the final direction to output files.

Step-by-step Instructions

Step 1 — Read Survey Context

Read all available survey outputs to understand the research landscape:

| File | Purpose | |------|---------| | `.pipeline/docs/research_brief.json` | Research topic, goal, target venue | | `.viewerleaf/research/Survey/reports/*.md` | Literature screening, gap summary | | `.pipeline/tasks/tasks.json` | Current task states and progress |

Extract:

  • **Research domain** and specific problem area
  • **Key gaps** identified in the literature
  • **Strong baselines** that exist (traditional and learning-based)
  • **Available datasets / experimental platforms**
  • **Target venue** constraints (if specified)

Step 2 — Generate Candidate Directions

Produce **2-4 candidate research directions**. For each candidate, provide:

## 候选方向 N:[方向名称]

**核心思路:** [1-2 句技术路线和创新点]

**研究问题:** [具体要回答的科学问题]

**方法概要:**
- [关键技术 1]
- [关键技术 2]
- ...

**对标基线:**
- [需要对比的已有方法 1]
- [需要对比的已有方法 2]

**目标刊物:** [适合投稿的会议/期刊]

**✅ 优势:**
- [优势 1]
- [优势 2]

**⚠️ 风险:**
- [风险 1]
- [风险 2]

**可行性评分:** ⭐⭐⭐⭐☆ (x/5)
- 实验资源: x/5
- 时间可控: x/5
- 技术难度: x/5
- 发表潜力: x/5

Candidate Generation Principles

1. **差异化** — 候选方向之间应有明显区别(不同技术路线、不同创新角度、不同应用场景) 2. **可比性** — 使用统一的评估维度,方便用户横向对比 3. **务实性** — 考虑用户的实际资源(本科 vs 硕博、实验周期、计算资源) 4. **梯度风险** — 包含保守稳妥的方向和激进创新的方向,让用户在风险与收益之间选择

Step 3 — Present Comparison Table

在列出所有候选方向后,给出一个汇总对比表:

## 📊 候选方向对比

| 维度 | 方向 1 | 方向 2 | 方向 3 |
|------|--------|--------|--------|
| 创新性 | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| 可行性 | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ |
| 发表潜力 | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| 实验周期 | 2 周 | 4 周 | 6 周 |
| 推荐度 | 🟡 稳妥 | 🟢 推荐 | 🔴 激进 |

Step 4 — USER CHECKPOINT ⛔

> **[USER_CHECKPOINT] — 必须在此处停下,等待用户回复。** > > 向用户提问: > 1. 你倾向于哪个方向? > 2. 是否需要组合某些方向的元素? > 3. 有没有你自己的想法想要加入? > 4. 对某个方向的风险有没有顾虑? > > **绝对不要跳过这一步。不要替用户做选择。**

等用户明确选择后,再进入 Step 5。

Step 5 — Converge and Write

用户确认后:

1. **写入 publishable_angle.md**

   路径: .viewerleaf/research/Ideation/publishable_angle.md

包含:选定方向的完整描述、用户的修改意见(如有)、对标基线、预期贡献

2. **更新 research_brief.json**

   路径: .pipeline/docs/research_brief.json

更新 `briefGoal` 和 `stageNotes.ideation`

3. **更新 tasks.json**

   路径: .pipeline/tasks/tasks.json

标记 ideation 任务完成,触发下一阶段任务

4. **记录选择理由** 在 `publishable_angle.md` 末尾附加:

   ## 选择记录
   - 候选方向数:N 个
   - 用户选择:方向 X [+ 用户修改内容]
   - 选择理由:[用户给出的理由或综合分析]
   - 弃选方向:方向 Y (原因)、方向 Z (原因)

Output Templates

publishable_angle.md

Use `templates/publishable_angle.template.md`:

# Publishable Angle

## 研究方向
[选定方向名称]

## 核心创新点
[1-2 句话概括]

## 研究问题
[具体要回答的科学问题]

## 方法概要
- ...

## 对标基线
- ...

## 预期贡献
- ...

## 目标刊物
[期刊/会议名称]

## 选择记录
- 候选方向数:N 个
- 用户选择:方向 X
- 选择理由:...

Integration with Other Skills

| Upstream | This Skill | Downstream | |----------|-----------|------------| | `research-literature-trace` (survey reports) | → 读取 gap/baseline 信息 | | | `research-pipeline-planner` (brief) | → 读取研究主题和目标 | | | | 生成候选 → 用户选择 → 写入 | → `inno-idea-eval` (评审选中方向) | | | | → `inno-experiment-dev` (实验设计) |

Notes for LLMs

1. **核心原则**:这个 skill 的价值在于**交互**,不在于生成。生成候选只是手段,让用户做出知情选择才是目的。 2. **不要跳过 USER_CHECKPOINT**:即使用户看起来已经有偏好,也要完整展示所有候选并明确收集确认。 3. **不要过度推荐**:可以标注"推荐"但不要暗示只有一个正确答案。每个方向都有其适用场景。 4. **尊重用户原有思路**:如果用户已有初步想法,把它作为候选之一纳入对比,而不是忽略。 5. **差异化很重要**:不要生成几个只有微小差别的方向,那等于没给选择。技术路线、创新角度、目标场景应有明显区分。

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