prove-me-wrong
Your agents have a theory. This skill makes them ask, “What would prove me wrong?”
A skill for Claude Code that makes the agent state a prediction about the result before changing code to fix behavior from an uncertain cause, so the next action tests the hypothesis.
Claude Code
$ npx -y skills add Lum1104/bet-on-it --agent claude-code
Codex
$ npx skills add Lum1104/bet-on-it -a codex
Cursor
$ npx skills add Lum1104/bet-on-it -a cursor
Gemini CLI
$ npx skills add Lum1104/bet-on-it -a gemini-cli
GitHub Copilot
$ npx skills add Lum1104/bet-on-it -a github-copilot
OpenCode
$ npx skills add Lum1104/bet-on-it -a opencode
Windsurf
$ npx skills add Lum1104/bet-on-it -a windsurf
Your agents change the code, then explain why.
This skill makes them bet on the result first.
Install · Before / After · How it works · Read the skill
Agents can explain almost any result after seeing it.
bet-on-it records the hypothesis, expected result, and losing condition before an action that depends on an uncertain causal explanation. After the experiment, it compares the observation with the prediction and drops unsupported changes.
Use bet-on-it before an action to commit to a prediction. Use prove-me-wrong once a claim or fix is favored to design an attack that could defeat it.
Install with the Skills CLI:
npx skills add Lum1104/bet-on-it
Install globally for all projects:
npx skills add Lum1104/bet-on-it -g
Then invoke it when the next diagnostic or behavior-changing step depends on an uncertain cause:
Use $bet-on-it to debug these duplicate checkout requests.
The duplicate requests were probably caused by a React effect. I changed its dependencies. Tests pass, so that was likely the issue.
The explanation appeared after the edit. There is no record of what the agent expected to observe, and the change can remain even if the duplicate originated on the server.
Bet 1
Hypothesis: A React effect binds the submit handler twice after rerender.
Expected observation: Instrumentation records two handler calls per click.
Expected change: none; this step only observes the current path.
Disproof: One client call still produces two server writes.
Instrumentation records one client call and two server writes. Bet 1 failed, so the agent does not make the effect edit. It forms a retry/idempotency hypothesis next. Only a matched Bet 1 would justify Bet 2 predicting the result of correcting the binding.
When the next action depends on an uncertain causal explanation, write four short fields:
Hypothesis: <current causal explanation>
Expected observation: <specific result expected next>
Expected change: <files, state, metric, or behavior; none for observation-only steps>
Disproof: <result that would make the hypothesis untenable>
A useful prediction names a value, error, event, diff, or behavior. “This should help” is not a bet.
Choose the cheapest safe action that separates the current hypothesis from a plausible alternative. Prefer read-only observation or temporary instrumentation before a persistent edit. Avoid bundling unrelated changes.
Preserve the original prediction and append:
Observed: <what actually happened>
Verdict: matched | partially matched | failed | inconclusive
Next action: <continue, refine, abandon, revert, or gather a better signal>
| Verdict | Required response |
|---|---|
| Matched | Continue, without claiming more than the observation supports |
| Partially matched | Narrow or revise the hypothesis |
| Failed | Abandon or replace it; revert unjustified speculative edits |
| Inconclusive | Treat it as no support and design a better discriminator |
Hypothesis: Repeated JSON parsing dominates request latency.
Expected observation: A profile attributes more than half of the slow path to JSON.parse.
Expected change: none; this step only profiles the baseline.
Disproof: Parsing is a minor sample in the slow path.
If the profile instead shows database wait time, the parsing optimization has no justification. Only a matched profile bet should lead to a second bet predicting how caching changes p95 latency.
Explicit prompts:
Use $bet-on-it before changing this cache invalidation logic.
Use $bet-on-it to make the next debugging step discriminate between two causes.
Use $bet-on-it and revert the edit if its prediction fails.
The complete agent-facing protocol lives in SKILL.md. The repository is intentionally instruction-only: no framework, service, or runtime dependency.
| Skill | Use it when |
|---|---|
prove-me-wrong | An established claim needs the cheapest useful counterexample |
no-vibes | Completion must be tied to the real end-to-end outcome |
archaeologist | Repository history may contain evidence about the suspected cause |
red-button | The experiment or change has high-impact consequences |
Each repository is standalone. Combine them only when their failure modes overlap.
MIT © 2026 Lum1104
Your agents have a theory. This skill makes them ask, “What would prove me wrong?”
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A skill for Claude Code that makes the agent state a prediction about the result before changing code to fix behavior from an uncertain cause, so the next action tests the hypothesis. Install it with the command on its page. It includes bet-on-it. Its skills do not fire on their own yet. Free and open source.
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