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Create Technical Spike

  • 219 installs
  • 2 repo stars
  • Updated July 24, 2026
  • ilteoood/harness

This is a copy of create-technical-spike by github - installs and ranking accrue to the original listing.

Time-box research spikes so critical technical questions are answered before your agent or team commits to an implementation path.

About

Create Technical Spike is an agent skill that produces time-boxed technical spike documents for solo and indie builders who need to resolve a specific architecture or integration question before coding. It defines where spikes live on disk, how to name them, and a repeatable markdown skeleton with summary, research questions, deadlines, and ownership metadata so agents do not jump straight into implementation on unresolved bets. Use it when a feature path is blocked on unknowns—API feasibility, realtime performance, third-party coupling—or when you want a written record of what was investigated and what was decided. The skill is procedural knowledge packaged as SKILL.md: your agent fills template inputs (title, category, priority, timebox) and emits decision-ready artifacts for validate and early build planning. It matters because spikes keep small teams from paying full build cost to learn what a week of focused research could have answered.

  • Scaffolds individual spike markdown files with YAML frontmatter (status, priority, timebox, owner)
  • File naming pattern: category-short-description-spike.md under a configurable docs/spikes folder
  • Sections for primary/secondary research questions, decision deadline, and spike objective
  • Time-boxed format to prevent endless research before implementation
  • Pairs naturally with implementation planning once the spike resolves

Create Technical Spike by the numbers

  • 219 all-time installs (skills.sh)
  • +30 installs in the week ending Jul 25, 2026 (Skillselion tracking)
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Jul 25, 2026 (Skillselion catalog sync)
npx skills add https://github.com/ilteoood/harness --skill create-technical-spike

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Listed on Skillselion
Installs219
repo stars2
Security audit2 / 3 scanners passed
Last updatedJuly 24, 2026
Repositoryilteoood/harness

What it does

Time-box research spikes so critical technical questions are answered before your agent or team commits to an implementation path.

Files

SKILL.mdMarkdownGitHub ↗

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.

Related skills

FAQ

Is Create Technical Spike safe to install?

skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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