felipecustodio Overview & Purpose
The Scientific Method is a step-by-step method for empirical investigation. It transforms speculative problem solving into structured hypothesis testing, ensuring that conclusions are grounded in verifiable evidence and reproducible reasoning.
When to Use
- Root Cause Analysis: Investigating unexplained bugs, performance regressions, or test failures.
- Empirical Validation: Testing technical assumptions against experimental data or logs.
- Scientific & Research Tasks: Systematic exploration of unknown phenomena or complex data sets.
Execution Workflow
- Observation: Record objective facts, error logs, or anomalous behavior without bias.
- Hypothesis: create testable, falsifiable hypotheses explaining the observation.
- Experiment Setup: Design a controlled test to prove or disprove the primary hypothesis.
- Data Collection & Analysis: Execute the experiment, measure results, and compare against expectations.
- Conclusion: Accept, modify, or reject the hypothesis based strictly on evidence.
Expected Output Contract
### Scientific Investigation
- **Observation**: [Factual anomaly / error]
- **Hypothesis**: [Falsifiable explanation]
- **Experiment**: [Validation step]
- **Results**: [Measured data]
- **Conclusion**: [Confirmed / Rejected]
Scripts
scripts/scientific_method.py- Deterministic evaluation, state validation, and CLI tool for scientific-method.