rseng-debugging
SolidCovers systematic debugging of research software: hypothesis-driven diagnosis instead of guess-and-change, building minimal reproducers, bisecting across commits, data and parameters, debugging scientific failure modes (wrong numbers rather than crashes, nondeterminism, scale-dependent bugs), debugger and print-discipline mechanics, and turning every fix into a regression test. Use when the user reports a bug, a crash, wrong or changed results, a heisenbug or an it-works-on-my-machine discrepancy, when a pipeline fails at scale but not in tests, or when the user is stuck guessing instead of diagnosing. For preventing silent wrong-result bugs see rseng-defensive-coding; for judging whether numerical differences matter see rseng-numerical-accuracy.
Install
Quality Score: 83/100
Skill Content
Details
- Author
- fdiblen
- Repository
- fdiblen/rseng-agent-skills
- Created
- 4 days ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
systematic-debugging
Find a bug by narrowing a hypothesis against evidence instead of guessing at fixes — reproduce, isolate, prove the cause, fix, then prove the fix. Binds to the decisions ledger as a defect pin so the root cause is recorded, not just the patch. Use when something is broken, a test fails mysteriously, or behavior differs between environments.
code-debug
Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.
systematic-debugging
A disciplined procedure for finding root causes -- reproduce, isolate, hypothesize, bisect, fix, verify. Consult when a bug is non-obvious, a fix didn't hold, or you've tried the same thing twice without progress.