Idea Generation

SkillDev tools

Generate research ideas from collected papers with gap analysis

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Idea Generation skill

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/43-wentorai-research-plugins/skills/research/methodology/scientify-idea-generation/SKILL.md and read by ahel’s review.

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:

# 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

ResourceLocationStatus
Papers$WORKSPACE/papers/Count: ?
Survey clusters$WORKSPACE/survey/clusters.jsonExists: 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
  1. Clone 3-5 reference repos:
mkdir -p $WORKSPACE/repos
git clone --depth 1 {repo_url} $WORKSPACE/repos/{name}
  1. Download paper sources:
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:

# 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:
IdeaStrategy
1Combination - merge 2+ techniques
2Simplification - reduce complexity
3Generalization - extend to new domain
4Constraint relaxation - remove assumption
5Architecture 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

IdeaNoveltyFeasibilityImpactTotal
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 SaysAction
"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

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
Advanced
Item type
skill
Key
scientify-idea-generation
Source
github.com/brycewang-stanford/auto-empirical-research-skills