awesome-copilot/prompts/create-technical-spike.prompt.md

agent, description, tools

agent	description	tools
agent	Create time-boxed technical spike documents for researching and resolving critical development decisions before implementation.	runCommands runTasks edit search extensions usages vscodeAPI think problems changes testFailure openSimpleBrowser web/fetch githubRepo todos Microsoft Docs search

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).

---
title: "${input:SpikeTitle}"
category: "${input:Category|Technical}"
status: "🔴 Not Started"
priority: "${input:Priority|High}"
timebox: "${input:Timebox|1 week}"
created: [YYYY-MM-DD]
updated: [YYYY-MM-DD]
owner: "${input:Owner}"
tags: ["technical-spike", "${input:Category|technical}", "research"]
---

# ${input:SpikeTitle}

## Summary

**Spike Objective:** [Clear, specific question or decision that needs resolution]

**Why This Matters:** [Impact on development/architecture decisions]

**Timebox:** [How much time allocated to this spike]

**Decision Deadline:** [When this must be resolved to avoid blocking development]

## Research Question(s)

**Primary Question:** [Main technical question that needs answering]

**Secondary Questions:**

- [Related question 1]
- [Related question 2]
- [Related question 3]

## Investigation Plan

### Research Tasks

- [ ] [Specific research task 1]
- [ ] [Specific research task 2]
- [ ] [Specific research task 3]
- [ ] [Create proof of concept/prototype]
- [ ] [Document findings and recommendations]

### Success Criteria

**This spike is complete when:**

- [ ] [Specific criteria 1]
- [ ] [Specific criteria 2]
- [ ] [Clear recommendation documented]
- [ ] [Proof of concept completed (if applicable)]

## Technical Context

**Related Components:** [List system components affected by this decision]

**Dependencies:** [What other spikes or decisions depend on resolving this]

**Constraints:** [Known limitations or requirements that affect the solution]

## Research Findings

### Investigation Results

[Document research findings, test results, and evidence gathered]

### Prototype/Testing Notes

[Results from any prototypes, spikes, or technical experiments]

### External Resources

- [Link to relevant documentation]
- [Link to API references]
- [Link to community discussions]
- [Link to examples/tutorials]

## Decision

### Recommendation

[Clear recommendation based on research findings]

### Rationale

[Why this approach was chosen over alternatives]

### Implementation Notes

[Key considerations for implementation]

### Follow-up Actions

- [ ] [Action item 1]
- [ ] [Action item 2]
- [ ] [Update architecture documents]
- [ ] [Create implementation tasks]

## Status History

| Date   | Status         | Notes                      |
| ------ | -------------- | -------------------------- |
| [Date] | 🔴 Not Started | Spike created and scoped   |
| [Date] | 🟡 In Progress | Research commenced         |
| [Date] | 🟢 Complete    | [Resolution summary]       |

---

_Last updated: [Date] by [Name]_

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.