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spike

Test an idea before committing to full development by building a small, disposable prototype. Compare approaches under equal conditions, try a failure case, and report feasibility with commands, results, or measurements supporting the verdict.

OriginalShow the original description

Run throwaway prototypes to validate feasibility, compare approaches, and report a verdict.

AI rating100/ 100See how to install

Good for

  • Testing whether an idea is technically feasible
  • Comparing two approaches under the same conditions
  • Checking an edge case before full development
  • Summarizing evidence for adopting or rejecting an approach

Overview

What it does

Build and run a small prototype to check whether an idea is feasible. First, define the question to investigate and review relevant documentation or code. Then create the smallest implementation needed to test it. Try one unexpected input or failure condition, and report a verdict of VALIDATED, PARTIAL, or INVALIDATED, with execution commands, output, or measurements as evidence and a recommendation for what to do next.

When it helps

Use it before full development to check whether a difficult part can work. It also helps compare two approaches using the same inputs and evaluation criteria, or record evidence for deciding against an approach.

Example requests

  • “Check whether this idea is feasible with the smallest possible prototype.”
  • “Compare approaches A and B under the same conditions, and summarize the results and your recommendation.”

Notes

Do not use it for questions that reading documentation or code can answer, or for production implementation. Prototypes normally go in .tmp/openclaw-spikes/<slug> and must be rewritten as normal implementations before entering production. When evaluating external dependencies, also check maintenance activity, documentation, licensing, and installation effort.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodIt clearly targets feasibility testing before full development and excludes questions answerable through documentation or code review.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodIt specifies question, research, build, stress, and verdict steps, plus an output format containing evidence.
SafetyAre sending data, deleting files, and running commands disclosed?
AGoodIt specifies prototype locations, prohibits direct production integration, and requires asking before building variants beyond a small prototype.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodNo fixed tools or keys are required, and it directs avoiding Docker, environment files, and similar setup.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 19, 2026. Treat it as a guide and read the original before installing.

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Files included (1)

  • SKILL.md1.8 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Spike

Use when the user wants to test an idea before committing to a real build: "spike this", "quick prototype", "is this possible", "compare A/B", "before we build".

Do not use when reading docs/code can answer the question, or when the user clearly asked for production implementation.

Loop

  1. Question: state the concrete feasibility question.
  2. Research: read enough docs/source to choose credible approach.
  3. Build: create the smallest runnable artifact that validates or invalidates the idea.
  4. Stress: try one edge case or failure mode.
  5. Verdict: VALIDATED, PARTIAL, or INVALIDATED.

Output shape

  • Default workspace: .tmp/openclaw-spikes/<slug> unless user asks for a tracked repo-local path.
  • Repo-local option: spikes/<NNN-slug>/ with README.md and minimal code.
  • Prefer runnable CLI, tiny HTML, one endpoint, or focused test.
  • Avoid package sprawl, Docker, env files, app frameworks, and production cleanup.

Multi-spike ideas

  • Split into 2-5 independent questions.
  • Run the riskiest question first.
  • For A/B comparisons, keep inputs equal and measure the same dimensions.
  • Ask before building all variants if the work is more than a small prototype.

Verdict format

## Verdict: VALIDATED | PARTIAL | INVALIDATED

Question: ...
Evidence: exact command/output/measurement.
What worked: ...
What failed or surprised us: ...
Recommendation: ship / adjust / avoid, with the next production step.

Rules

  • An invalidated spike is useful when it rules out a path with evidence.
  • Do not merge spike code into production without rewriting it normally.
  • If external dependencies are evaluated, check health: recent release/commit, docs, license, install friction.

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