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github avatar

Create Technical Spike

github/awesome-copilotOfficial

When you're stuck on a technical decision that's blocking development, this generates structured spike documents to research your way out. It creates markdown files with research questions, investigation checklists, and decision frameworks for things like API integrations, architecture choices, or performance constraints. The templates force you to define success criteria upfront and timebox your research, which prevents endless rabbit holes. I've seen too many teams debate implementation approaches for weeks when a two-day focused spike would have given them concrete answers. The structured format also makes it easy to hand off research between team members.

installs
9K
GitHub stars
40.5K
last updated
Aug 21, 2026
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Install

$ npx -y skills add github/awesome-copilot --skill create-technical-spike --agent claude-code

Installs into .claude/skills of the current project.

Files

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.

Sponsors

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Details

Repository
github.com/github/awesome-copilot
Categories
Git & Pull Requests, AI & Agent Building

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