
Thinking Scientific Method
When a symptom has several plausible causes, rank falsifiable hypotheses and run the...
Install
npx skills add tjboudreaux/cc-thinking-skills --skill thinking-scientific-method -g -a claude-code -y- Repository
- tjboudreaux/cc-thinking-skills1.7k
- Category
- Engineering
- Updated
- 3mo ago
- License
- MIT
- Context cost
- Lightabout 1,003 tokens
- Runs scripts
- No, instructions only
What it does
When a symptom has several plausible causes, rank falsifiable hypotheses and run the cheapest discriminating observation first; prefer least-assumptive survivors only after evidence fit.
Scientific Method (Hypothesis Differential)
When a symptom could come from several places, enumerate competing falsifiable hypotheses and spend the cheapest observation on the one that best discriminates among them. After each observation, keep only hypotheses that still fit, then prefer the survivor with the fewest unsupported assumptions as the working explanation.
When to Use
- A bug, incident, or anomaly has more than one plausible cause.
- You can observe code, logs, diffs, traces, tests, configs, or data now.
- You must localize the faulty file, function, branch, config, or invariant before fixing.
- Competing explanations fit the same surface facts and you need a discriminating check.
When NOT to Use
- Cause is already obvious from a single stack, failing test, or recent diff, fix directly.
- Only one plausible hypothesis exists, test it; do not invent rivals for ritual.
- No observation is possible yet, obtain access first; do not speculate a localization.
- Multi-week experiments, product A/B tests, or policy trials, this skill is for agent-now checks.
- Fault is already localized and you need systemic root/prevention depth, use five-whys-plus.
- Selective "only these objects/times" defects better suited to IS/IS-NOT comparison, use Kepner-Tregoe.
- Representation (doc/dashboard) may be stale versus reality, verify territory with map-territory first, then resume hypotheses.
