create-technical-spike
Create time-boxed technical spike documents for researching and resolving critical development decisions before implementation.
Best use case
create-technical-spike is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Create time-boxed technical spike documents for researching and resolving critical development decisions before implementation.
Teams using create-technical-spike should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/create-technical-spike/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How create-technical-spike Compares
| Feature / Agent | create-technical-spike | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Create time-boxed technical spike documents for researching and resolving critical development decisions before implementation.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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 `${input:FolderPath|docs/spikes}` directory. Name each file using the pattern: `[category]-[short-description]-spike.md` (e.g., `api-copilot-integration-spike.md`, `performance-realtime-audio-spike.md`).
```md
---
title: "${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
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