Formulate testable hypotheses and grade evidence to diagnose uncertain system failures.
npx skills add https://github.com/augustscl/awesome-xiawang-skills --skill hdd-augustscl
Please help me install this Agent Skill. Skill: hdd Source: https://github.com/augustscl/awesome-xiawang-skills/tree/main/hdd Command: npx skills add https://github.com/augustscl/awesome-xiawang-skills --skill hdd-augustscl
HDD (Hypothesis-Driven Development) helps teams and individuals diagnose ambiguous failures, choose between competing solutions, and avoid costly, incorrect changes by forcing testable hypotheses and evidence-based decisions. It prevents wasted effort caused by unchecked assumptions and guess-and-fix cycles by turning uncertainty into verifiable experiments.
Apply HDD to diagnose a failing service by listing 3 testable hypotheses, specifying observable falsification criteria for each, designing a minimal verification test, and running the highest-impact test first.
High-intent search queries and answers about installing and using this skill.
To find the root cause of a flaky service, formulate 3 testable hypotheses with explicit falsification criteria, then run the highest-impact verification test first to isolate the failure.
Hypothesis-driven debugging is a method that diagnoses uncertain software failures by assigning prior probabilities to hypotheses and requiring verifiable, reproducible tests before making code changes.
Convert vague bug reports into verifiable test cases by applying a test-first workflow: define observable falsification criteria, design a minimal acceptance test, and execute it before development.
Yes, you can use hypothesis testing for architecture and vendor selection by running controlled spikes as verifiable experiments to evaluate competing solutions and avoid incorrect changes.
The V1-V5 evidence grading model categorizes reproducibility levels, requiring V1 or V2 reproducible tests to be passed before proceeding to development or end-to-end testing.
Avoid guess-and-fix cycles for regression analysis when outcomes are uncertain, and instead use acceptance-test-driven progression rules with clear rollback criteria to prevent wasted effort.
leynosFormulate falsifiable debugging hypotheses and plan falsification tests for software issues.
recca0120Guide TDD-driven feature workflows with layered tests and incremental commits.
remiconnessonDiagnose software bugs through reproduction, hypothesis testing, and root-cause analysis.
rp4riEnforce falsifiable hypotheses and data audits in bug resolution workflows.
