Create Technical Spike
GitHubOfficialOriginally contributed by @PlagueHO as prompts/create-technical-spike.prompt.md; moved into a skill by pull request #761Distributed by GitHub
- Skill
- Content generator
- Software development
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a standardized template and research strategy for creating technical spikes. It helps development teams document research questions, investigation plans, and final recommendations for critical technical decisions. By enforcing a time-boxed approach and clear success criteria, it ensures that research efforts remain focused, evidence-based, and actionable, ultimately unblocking development progress.
What it does
- Generates a structured Markdown template for technical spike documentation.
- Defines a clear research strategy including information gathering, validation, and decision-making.
- Provides naming conventions for organizing spike files by category.
- Establishes best practices for AI agents to conduct focused, evidence-based technical research.
- Tracks spike status, priority, and ownership to ensure accountability.
- Facilitates the transition from research findings to concrete implementation tasks.
When to use it
- When a critical technical decision needs to be made before development can proceed.
- When exploring the feasibility of a new API integration or architectural pattern.
- When investigating performance bottlenecks or scalability requirements.
- When you need to document the rationale behind a specific technical choice for the team.
- When research tasks need to be time-boxed to prevent scope creep.
Advantages
- Reduces ambiguity in technical decision-making processes.
- Ensures research is grounded in evidence, prototypes, or testing.
- Standardizes documentation across the development lifecycle.
- Helps identify and manage dependencies between technical tasks.
- Provides a clear audit trail for architectural decisions.
Usage examples
- “Create a technical spike for investigating the latency of our real-time audio processing module.”
- Generates a file named performance-audio-processing-latency-spike.md with a pre-filled template focused on latency research, success criteria, and investigation tasks.
- “Start a new spike to evaluate the feasibility of integrating the XYZ third-party API.”
- Generates a file named api-xyz-integration-spike.md with sections for API capabilities, rate limits, and authentication research.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/github/create-technical-spike/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip create-technical-spike.zip -d .agents/skills
Documentation by PlagueHO
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.
Files
- ATTRIBUTION.mdAdded by AutoGineer1.1 KiB
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md6.4 KiB
Requirements and compatibility
Written for: GitHub Copilot
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Originally contributed by
@PlagueHOas prompts/create-technical-spike.prompt.mdmoved into a skill by pull request #761
- Publisher
- GitHub (Official)
- Distributed by
- GitHub
- Source
- github/awesome-copilot · skills/create-technical-spike · commit 797337f
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Contributors
- PlagueHO
AutoGineer is not affiliated with or endorsed by PlagueHO or GitHub.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download create-technical-spike.zip