diagnosis-loop
Skill4 starsChanged 2 months agoApache-2.0View on GitHub
Diagnose a difficult bug or performance regression through a symptom-specific reproduction and falsifiable hypotheses. Fix only when requested; not an automatic architecture rewrite.
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The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 32
Do not promote an untested theory to fact, erase a flaky result with retries, or turn a local defect into a modernization program.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Diagnosis Loop
Explain the cause using evidence. A diagnosis-only task authorizes inspection and safe checks, not an unrequested tracked code change or remote mutation. A request to fix the problem can include implementation after diagnosis without requiring a separate agent.
Build a useful feedback loop
State the expected behavior, actual symptom, affected environment, and observable failure signal. Inspect the relevant source and callers. Use an available index or memory service when helpful, with a focused file-search fallback.
Choose the narrowest existing test, request replay, browser scenario, CLI invocation, benchmark, or trace that exercises the symptom. Run it when safe and available. Preserve the first failure signal and protect credentials, personal data, device captures, and logs. Do not reproduce an issue against production or physical equipment without the necessary authority.
A useful loop distinguishes this bug from an unrelated setup failure. Minimize the input or sequence while preserving the symptom. If reproduction is unavailable, continue with bounded static reasoning and label the missing runtime evidence.
Test competing explanations
Keep as many hypotheses as the uncertainty needs; do not manufacture alternatives for an obvious proven defect. For each plausible cause, identify an observation that would falsify it. Try the cheapest high-information probe, change one variable at a time, and retire explanations contradicted by the evidence.
Prefer existing telemetry, debuggers, profilers, and focused checks over broad logging. Add temporary tracked instrumentation only when edits are in scope, and remove task-owned instrumentation before closing. For a performance regression, compare equivalent workloads and environments and separate CPU, I/O, contention, allocation, and tail latency.
Stop at the right boundary
For diagnosis, return the cause or bounded uncertainty, reproduction, supporting evidence, and a proposed regression seam. For an authorized fix, correct the root cause and verify the relevant failure path rather than patching only one symptom.
Do not promote an untested theory to fact, erase a flaky result with retries, or turn a local defect into a modernization program. Clean up task-owned runtime state and report remaining gaps plainly.
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