| name | research-templates |
| description | Three academic research templates (Heilmeier, scientific discovery, system optimization) with schemas and use cases. Use when RefineIdea to align output structure with research type. |
Research Templates
Three academic templates for structuring refined research ideas. Use when RefineIdea to choose the output structure that best fits the research type.
Template Selection
| Template ID | Use When | Core Fields |
|---|
| heilmeier_catechism | Engineering/applied research, system building, DARPA-style proposals | problem_statement, state_of_the_art, key_insight, impact, technical_plan, risks_and_mitigations |
| scientific_discovery | Theoretical AI, algorithms, experiments (NeurIPS/ICLR style) | research_question, hypothesis, related_work_gap, proposed_method, experimental_design, expected_results |
| system_optimization | Performance tuning, resource efficiency, benchmarking | target_system, bottleneck_analysis, optimization_strategy, implementation_steps, evaluation_metrics |
Heilmeier Catechism
For engineering and applied research. You may use these fields to organize your output (not required):
- problem_statement: What is the problem? Why does it matter?
- state_of_the_art: Current solutions and limitations
- key_insight: Novel angle or approach
- impact: Expected benefit (e.g. efficiency, scalability)
- technical_plan: High-level implementation steps
- risks_and_mitigations: Main risks and how to address them
Scientific Discovery
For theory and experiments. You may use these fields (not required):
- research_question: Central RQ (RQ1:, RQ2:)
- hypothesis: Testable claim
- related_work_gap: Limitations of prior work
- proposed_method: Method outline
- experimental_design: Setup, metrics, baselines
- expected_results: Anticipated findings
System Optimization
For performance and efficiency. You may use these fields (not required):
- target_system: System or component to optimize
- bottleneck_analysis: Current limitations
- optimization_strategy: Approach (e.g. caching, parallelism)
- implementation_steps: Concrete steps
- evaluation_metrics: How to measure success
Use whichever structure best fits the research type. Quality matters; schema is flexible.
