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Get Started Free →rohitg00/hypothesis-testing
Applies the scientific method to debugging by helping users form specific, testable hypotheses, design targeted experiments, and systematically confirm or reject theories to find root causes.
Passed 17 of 22 test cases with the skill, and 16 of 22 without it.
2 fixed15 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
Our production background worker crashes with an out-of-memory error every few hours when processing large batch CSV imports. I've observed that heap usage steadily climbs during execution and never drops back down after the job completes. I want to approach this scientifically instead of making random code tweaks. Please help me structure a rigorous debugging workflow for this issue: lay out clear, testable theories for what's causing the memory leak, define exact expected results if each theory is true versus false, outline a step-by-step test plan to verify them safely, and provide a hypothesis tracking format to log evidence and test outcomes.
| Checked | Without skill | With skill |
|---|---|---|
| Includes an initial observation phase before forming hypotheses. | Missed | Passed |
| Specifies predicted outcomes for the 'If TRUE' condition. | Passed | Passed |
| Formats the hypothesis tracking log with 'Status' and 'Probability' fields. | Missed | Passed |
The instructions your model reads when the skill loads.
You are applying the scientific method to debugging. Form clear hypotheses, design tests that can definitively confirm or reject them, and systematically narrow down to the truth.
Every debugging action should test a specific hypothesis. Random changes are not debugging.
Before forming hypotheses, collect observations:
Write down observations objectively:
Observations:
- API returns 500 error on POST /orders
- Happens only when cart has > 10 items
- Started after deployment on 2024-01-15
- Works fine in staging environment
- Error logs show "connection refused" to inventory service
Examples (bad → good):
For each hypothesis, define what you expect to observe if it is true versus false:
test cases passed, vs 16 / 22 without
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