scientify-idea-generation
Generate research ideas from collected papers with gap analysis
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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/scientify-idea-generation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How scientify-idea-generation Compares
| Feature / Agent | scientify-idea-generation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/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.
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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 insteadRelated Skills
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