scientify-idea-generation

Generate research ideas from collected papers with gap analysis

191 stars

Best use case

scientify-idea-generation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Generate research ideas from collected papers with gap analysis

Teams using scientify-idea-generation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/scientify-idea-generation/SKILL.md --create-dirs "https://raw.githubusercontent.com/wentorai/research-plugins/main/skills/research/methodology/scientify-idea-generation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/scientify-idea-generation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How scientify-idea-generation Compares

Feature / Agentscientify-idea-generationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Generate research ideas from collected papers with gap analysis

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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