idea-generation

Idea Generation Generate and refine novel research ideas with literature-backed novelty assessment. Input $0 — Research area, task description, or existing codebase context $1 — Optional: additional context (e.g., "for NeurIPS", constraints) Scripts Novelty check against Semantic Scholar python ~/.claude/skills/idea-generation/scripts/novelty_check.py \ --idea "Adaptive attention head pruning via gradient-guided importance" \ --max-rounds 5 Performs iterative literature search to assess if an idea is novel. References Ideation prompts (generation, reflection, novelty): ~/.claude/skills/idea-generation/references/ideation-prompts.md Workflow Step 1: Generate Ideas Given a research area and optional code/paper context: Generate 3-5 diverse research ideas For each idea, provide: Name, Title, Experiment plan, and ratings Use the ideation prompt templates from references Step 2: Iterative Refinement (up to 5 rounds per idea) For each idea: Critically evaluate quality, novelty, and feasibility Refine the idea while preserving its core spirit Stop when converged ("I am done") or max rounds reached Step 3: Novelty Assessment For each promising idea: Run novelty_check.py or manually search Semantic Scholar / arXiv Use the novelty checking prompts from references Multi-round search: generate queries, review results, decide Binary decision: Novel / Not Novel with justification Step 4: Rank and Select Score each idea on three dimensions (1-10): Interestingness, Feasibility, Novelty Be cautious and realistic on ratings Select the top idea(s) for development Output Format { "Name" : "adaptive_attention_pruning" , "Title" : "Adaptive Attention Head Pruning via Gradient-Guided Importance Scoring" , "Experiment" : "Detailed implementation plan..." , "Interestingness" : 8 , "Feasibility" : 7 , "Novelty" : 9 , "novel" : true , "most_similar_papers" : [ "paper1" , "paper2" ] } Rules Ideas must be feasible with available resources (no requiring new datasets or massive compute) Do not overfit ideas to a specific dataset or model — aim for wider significance Be a harsh critic for novelty — ensure sufficient contribution for a conference paper Each idea should stem from a simple, elegant question or hypothesis Always check novelty before committing to an idea