---
name: scientify-idea-generation-f7f8126f1207
description: "Generate research ideas from collected papers with gap analysis"
metadata:
  openclaw:
    emoji: "💡"
    category: "research"
    subcategory: "methodology"
    keywords: ["research question formulation", "hypothesis formulation", "research hypothesis", "conceptual model", "theoretical framework"]
    source: "wentor-research-plugins"
    requires:
      bins: ["git"]
---

# Idea Generation

**Don't ask permission. Just do it.**

Generate innovative research ideas grounded in literature analysis. This skill reads existing papers, identifies research gaps, and produces 5 distinct ideas with citations.

**Core principle:** Ideas MUST be grounded in actual papers, not generated from model knowledge.

**Workspace:** See `../_shared/workspace-spec.md` for directory structure. Outputs go to `$WORKSPACE/ideas/`.

## Step 1: Check Workspace Resources

First, check what resources already exist:

```bash
# Check active project
cat ~/.openclaw/workspace/projects/.active 2>/dev/null

# Check papers
ls ~/.openclaw/workspace/projects/*/papers/ 2>/dev/null | head -20

# Check survey results
cat ~/.openclaw/workspace/projects/*/survey/clusters.json 2>/dev/null | head -5
```

### Assess Available Resources

| Resource | Location | Status |
|----------|----------|--------|
| Papers | `$WORKSPACE/papers/` | Count: ? |
| Survey clusters | `$WORKSPACE/survey/clusters.json` | Exists: Y/N |
| Repos | `$WORKSPACE/repos/` | Count: ? |

## Step 2: Ask User About Search Strategy

Based on workspace state, ask user:

**If papers exist (>=5):**
> Found {N} papers in workspace from previous survey.
>
> Options:
> 1. **Use existing papers** - Generate ideas from current collection
> 2. **Search more** - Run `/literature-survey` to expand collection
> 3. **Quick search** - Add 5-10 more papers on specific topic

**If no papers:**
> No papers found in workspace.
>
> To generate grounded ideas, I need literature. Options:
> 1. **Run /literature-survey** - Comprehensive search (100+ papers, recommended)
> 2. **Quick search** - Fetch 10-15 papers on your topic now
> 3. **You provide papers** - Point me to existing PDFs/tex files

## Step 3: Acquire Resources (if needed)

### Option A: Delegate to /literature-survey (Recommended)

If user wants comprehensive search:
```
Please run: /literature-survey {topic}

This will:
- Search 100+ papers systematically
- Filter by relevance (score >=4)
- Cluster into research directions
- Save to $WORKSPACE/papers/

After survey completes, run /idea-generation again.
```

### Option B: Quick Search (5-10 papers)

For fast iteration, do minimal search:

1. **ArXiv search:**
```
Tool: arxiv_search
Arguments:
  query: "{user_topic}"
  max_results: 10
```

2. **Clone 3-5 reference repos:**
```bash
mkdir -p $WORKSPACE/repos
git clone --depth 1 {repo_url} $WORKSPACE/repos/{name}
```

3. **Download paper sources:**
```bash
mkdir -p $WORKSPACE/papers/{arxiv_id}
curl -L "https://arxiv.org/src/{arxiv_id}" | tar -xz -C $WORKSPACE/papers/{arxiv_id}
```

## Step 4: Analyze Literature

**Prerequisites:** At least 5 papers in `$WORKSPACE/papers/`

### 4.1 Read Papers

For each paper, extract:
- Core contribution (1 sentence)
- Key method/formula
- Limitations mentioned
- Future work suggestions

**Long papers (>50KB):** See `references/reading-long-papers.md`

### 4.2 Identify Research Gaps

Look for:
- Common limitations across papers
- Unexplored technique combinations
- Scalability issues
- Assumptions that could be relaxed

Document gaps in `$WORKSPACE/ideas/gaps.md`:
```markdown
# Research Gaps Identified

## Gap 1: [Description]
- Mentioned in: [paper1], [paper2]
- Why important: ...

## Gap 2: [Description]
...
```

## Step 5: Generate 5 Ideas

Create `$WORKSPACE/ideas/idea_1.md` through `idea_5.md` using template in `references/idea-template.md`.

**Requirements:**
- Each idea cites >=2 papers by arXiv ID
- Use different strategies:

| Idea | Strategy |
|------|----------|
| 1 | Combination - merge 2+ techniques |
| 2 | Simplification - reduce complexity |
| 3 | Generalization - extend to new domain |
| 4 | Constraint relaxation - remove assumption |
| 5 | Architecture innovation - new design |

**REJECTED if:** No arXiv IDs cited, or ideas not grounded in literature

## Step 6: Select and Enhance Best Idea

### 6.1 Score All Ideas

| Idea | Novelty | Feasibility | Impact | Total |
|------|---------|-------------|--------|-------|
| 1 | /5 | /5 | /5 | /15 |
| ... | | | | |

### 6.2 Enhance Selected Idea

Create `$WORKSPACE/ideas/selected_idea.md` with:
- Detailed math (loss functions, gradients)
- Architecture choices
- Hyperparameters
- Implementation roadmap

### 6.3 (Optional but recommended) OpenReview Evidence Check

For the top 1-2 shortlisted ideas, validate novelty/positioning risk with `openreview_lookup`:

- Query using core title keywords or representative baseline paper title
- Extract evidence:
  - decision (if available)
  - average rating/confidence
  - reviewer weakness patterns
- Add a short "submission risk note" section per idea:
  - likely reviewer concern
  - mitigation experiment to add
  - positioning adjustment

Do not claim accept/reject predictions as facts. Report evidence-backed risk signals only.

## Step 7: Code Survey

Map idea concepts to reference implementations.

See `references/code-mapping.md` for template.

**Output:** `$WORKSPACE/ideas/implementation_report.md`

## Step 8: Summary

Create `$WORKSPACE/ideas/summary.md`:
- All 5 ideas with scores
- Selected idea details
- Next steps: `/research-pipeline` to implement

## Commands

| User Says | Action |
|-----------|--------|
| "Generate ideas for X" | Check workspace -> ask strategy -> generate |
| "I have papers, generate ideas" | Skip to Step 4 |
| "Enhance idea N" | Jump to Step 6 |
| "Map to code" | Jump to Step 7 |

## Integration

- **Before:** `/literature-survey` to collect papers
- **After:** `/research-pipeline` to implement selected idea
- **Alternative:** `/write-review-paper` to write survey instead


---
Source attribution: wentorai
Original project: https://github.com/wentorai/research-plugins/blob/bf44b3cd617fa94c8a1b254c5d1987142ca3d631/skills/research/methodology/scientify-idea-generation/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Wentor AI

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: wentorai
Original project: https://github.com/wentorai/research-plugins/blob/bf44b3cd617fa94c8a1b254c5d1987142ca3d631/skills/research/methodology/scientify-idea-generation/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Education & Research, Product Management
Roles: Data Scientist, Product Manager, Researcher
Specialties: API
Tools: Arxiv_Search
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 61016f3a6d636883297026da69a0e5d63fc2194f73fbac6c609715491b9e0849