Créer des documents de spike technique

VérifiéSûr

Crée des documents de spike technique limités dans le temps pour rechercher et résoudre les décisions de développement critiques avant la mise en œuvre. Utile lorsque les équipes ont besoin d'une enquête structurée sur des questions techniques, avec des livrables et des délais clairs.

Spar Skills Guide Bot
DeveloppementIntermédiaire
4002/06/2026
CopilotCodex
#technical-spike#research#documentation#decision-making

Recommandé pour

Notre avis

Crée des documents de spike technique limités dans le temps pour rechercher et résoudre des décisions de développement critiques avant la mise en œuvre.

Points forts

  • Structure claire et reproductible
  • Promet une recherche ciblée avec des questions définies
  • Inclut un chronométrage et des critères de succès explicites
  • Facilite la documentation des décisions et des pistes de suivi

Limites

  • Nécessite une saisie manuelle des champs
  • Le modèle peut être trop rigide pour des explorations très ouvertes
  • Dépend d'un plugin spécifique (awesome-copilot-root)
Quand l'utiliser

Utilisez cette compétence lorsque vous devez formaliser une exploration technique avant une décision d'implémentation.

Quand l'éviter

Évitez-la si la décision peut être résolue rapidement par une conversation ou si un modèle plus spécifique existe déjà.

Analyse de sécurité

Sûr
Score qualité92/100

This skill only instructs the creation of markdown documents using a template. There are no commands for code execution, file deletion, network access, or handling of sensitive data. It poses no security risk.

Aucun point d'attention détecté

Exemples

API integration spike
Create a technical spike to research the best API integration approach for adding real-time collaboration features to our editor. Timebox: 2 days.
Performance investigation spike
Create a spike document to investigate the performance impact of using WebSockets vs Server-Sent Events for live updates. Priority: high.
Architecture decision spike
Create a technical spike to decide between microservices and a monolithic architecture for our new analytics module. Timebox: 1 week.

name: "awesome-copilot-root-create-technical-spike" description: "Create time-boxed technical spike documents for researching and resolving critical development decisions before implementation. Use when: the task directly matches create technical spike responsibilities within plugin awesome-copilot-root. Do not use when: a more specific framework or task-focused skill is clearly a better match."

Awesome Copilot Root Create Technical Spike

Scope

  • Use when: the task directly matches create technical spike responsibilities within plugin awesome-copilot-root.
  • Do not use when: a more specific framework or task-focused skill is clearly a better match.

Shared Plugin Context

See references/plugin-context.md.

Source

  • Converted from /tmp/codex-awesome-materialized-x3j3lxox/plugins/awesome-copilot-root/skills/create-technical-spike/SKILL.md

Instructions

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.

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