create-technical-spike▌
github/awesome-copilot · updated Jun 2, 2026
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Time-boxed technical spike documents for researching critical development decisions before implementation.
- ›Generates structured markdown spike files with clear objectives, research questions, investigation plans, and decision frameworks
- ›Supports six spike categories: API Integration, Architecture & Design, Performance & Scalability, Platform & Infrastructure, Security & Compliance, and User Experience
- ›Includes built-in checklists for research tasks, success criter
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.mdapi-azure-speech-realtime-spike.mdapi-vscode-extension-capabilities-spike.md
Performance Examples:
performance-audio-processing-latency-spike.mdperformance-extension-host-limitations-spike.mdperformance-webrtc-reliability-spike.md
Architecture Examples:
architecture-voice-pipeline-design-spike.mdarchitecture-state-management-spike.mdarchitecture-error-handling-strategy-spike.md
Best Practices for AI Agents
-
One Question Per Spike: Each document focuses on a single technical decision or research question
-
Time-Boxed Research: Define specific time limits and deliverables for each spike
-
Evidence-Based Decisions: Require concrete evidence (tests, prototypes, documentation) before marking as complete
-
Clear Recommendations: Document specific recommendations and rationale for implementation
-
Dependency Tracking: Identify how spikes relate to each other and impact project decisions
-
Outcome-Focused: Every spike must result in an actionable decision or recommendation
Research Strategy
Phase 1: Information Gathering
- Search existing documentation using search/fetch tools
- Analyze codebase for existing patterns and constraints
- Research external resources (APIs, libraries, examples)
Phase 2: Validation & Testing
- Create focused prototypes to test specific hypotheses
- Run targeted experiments to validate assumptions
- Document test results with supporting evidence
Phase 3: Decision & Documentation
- Synthesize findings into clear recommendations
- Document implementation guidance for development team
- 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.
How to use create-technical-spike on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add create-technical-spike
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches create-technical-spike from GitHub repository github/awesome-copilot and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate create-technical-spike. Access the skill through slash commands (e.g., /create-technical-spike) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★46 reviews- ★★★★★Chinedu Rahman· Dec 24, 2024
Useful defaults in create-technical-spike — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Chinedu Nasser· Dec 20, 2024
I recommend create-technical-spike for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Shikha Mishra· Dec 4, 2024
We added create-technical-spike from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Yash Thakker· Nov 23, 2024
create-technical-spike fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Li Tandon· Nov 15, 2024
I recommend create-technical-spike for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Chinedu Okafor· Nov 11, 2024
Useful defaults in create-technical-spike — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Dhruvi Jain· Oct 14, 2024
create-technical-spike is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Li Jackson· Oct 6, 2024
create-technical-spike reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ama Okafor· Oct 2, 2024
create-technical-spike has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Oshnikdeep· Sep 21, 2024
Keeps context tight: create-technical-spike is the kind of skill you can hand to a new teammate without a long onboarding doc.
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