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
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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
LICENSE
MIT License Copyright GitHub, Inc. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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
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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