spike

SKILL.md

Spike

Structured technical investigation to reduce uncertainty. Answer specific questions, not "explore X."

Key Principles

  • Every spike answers a specific, measurable question
  • Strict time-box (default 4h) — produce a decision at the end, even if incomplete
  • Output is a decision (GO/NO-GO/PIVOT/MORE-INFO), not a general exploration
  • Create follow-up tasks from findings, not just a report

When NOT to Use

  • Multi-day evaluations — Use deep-research for comprehensive technology evaluations with stakeholder reports
  • Already know what to build — Skip straight to implementation; spikes are for reducing uncertainty, not planning known work
  • Bug investigation — Use error-handling or /fix; bugs have reproduction steps, spikes have open questions

Quick Start Checklist

  1. Define the question clearly (what are we trying to learn?)
  2. Set a time-box (hours, not days — use deep-research for multi-day)
  3. Identify evaluation criteria upfront
  4. Investigate with focused experiments or prototypes
  5. Checkpoint at 50% — assess progress, decide if pivoting
  6. Produce mandatory conclusion: GO / NO-GO / PIVOT / MORE-INFO

Mandatory Outputs

  • Decision: GO, NO-GO, PIVOT, or MORE-INFO
  • Evidence: What was tested, results observed
  • Follow-up tasks: Created in ohno if GO
  • Report: Saved to .claude/spikes/[name]-[date].md

References

Reference Description
spike-types.md Feasibility, architecture, integration, performance spikes
question-patterns.md How to frame good spike questions
output-templates.md Spike report templates and examples
Weekly Installs
18
GitHub Stars
2
First Seen
Jan 24, 2026
Installed on
gemini-cli15
codex15
opencode15
github-copilot15
cursor13
kimi-cli12