Create time-boxed technical spike documents for researching and resolving critical development decisions before implementation.

Create Technical Spike Document Create time boxed technical spike documents for researching critical questions that must be answered before development can proceed. Each spike focuses on a specific technical decision with clear deliverables and timelines. Document Structure Create individual files in ${input:FolderPath docs/spikes} directory. Name each file using the pattern: [category] [short description] spike.md (e.g., api copilot integration spike.md , performance realtime audio spike.md ). Categories for Technical Spikes API Integration Third party API capabilities and limitations Integration patterns and authentication Rate limits and performance characteristics Architecture & Design System architecture decisions Design pattern applicability Component interaction models Performance & Scalability Performance requirements and constraints Scalability bottlenecks and solutions Resource utilization patterns Platform & Infrastructure Platform capabilities and limitations Infrastructure requirements Deployment and hosting considerations Security & Compliance Security requirements and implementations Compliance constraints Authentication and authorization approaches User Experience User interaction patterns Accessibility requirements Interface design decisions File Naming Conventions Use descriptive, kebab case names that indicate the category and specific unknown: API/Integration Examples: api copilot chat integration spike.md api azure speech realtime spike.md api vscode extension capabilities spike.md Performance Examples: performance audio processing latency spike.md performance extension host limitations spike.md performance webrtc reliability spike.md Architecture Examples: architecture voice pipeline design spike.md architecture state management spike.md architecture error handling strategy spike.md Best Practices for AI Agents 1. One Question Per Spike: Each document focuses on a single technical decision or research question 2. Time Boxed Research: Define specific time limits and deliverables for each spike 3. Evidence Based Decisions: Require concrete evidence (tests, prototypes, documentation) before marking as complete 4. Clear Recommendations: Document specific recommendations and rationale for implementation 5. Dependency Tracking: Identify how spikes relate to each other and impact project decisions 6. Outcome Focused: Every spike must result in an actionable decision or recommendation Research Strategy Phase 1: Information Gathering 1. Search existing documentation using search/fetch tools 2. Analyze codebase for existing patterns and constraints 3. Research external resources (APIs, libraries, examples) Phase 2: Validation & Testing 1. Create focused prototypes to test specific hypotheses 2. Run targeted experiments to validate assumptions 3. Document test results with supporting evidence Phase 3: Decision & Documentation 1. Synthesize findings into clear recommendations 2. Document implementation guidance for development team 3. Create follow up tasks for implementation Tools Usage search/searchResults: Research existing solutions and documentation fetch/githubRepo: Analyze external APIs, libraries, and examples codebase: Understand existing system constraints and patterns runTasks: Execute prototypes and validation tests editFiles: Update research progress and findings vscodeAPI: Test VS Code extension capabilities and limitations Focus on time boxed research that resolves critical technical decisions and unblocks development progress.

create-technical-spike