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audriusstataudriusstat/execution-discipline/skills/two-strike-debug/SKILL.md

two-strike-debug

Skill0 starsChanged 4 months agoMITView on GitHub

Use when anything fails — a test, build, deploy, script, or unexpected runtime behavior — BEFORE proposing a fix, and again whenever a fix attempt has just failed. Triggers: "fails", "broken", "error", "still not working", "neveikia", "lūžta", "klaida", "vis dar neveikia", "vėl ta pati klaida". Not for: code that hasn't been run yet, or mechanical lint/type complaints with obvious fixes.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    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
  1. Distinctive:

    After the fix, verification-before-completion gates the "done" claim.

    line 63
  2. Distinctive:

    When even re-diagnosis has failed and the user reports failure again, escalate per compounding-engineering §5: fresh context, carrying …

    line 64

≈ “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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Two-Strike Debug

Triggers automatically when relevant; invoke directly with /two-strike-debug or ask, e.g. "diagnose this failure".

A fix without a confirmed diagnosis is a guess. Two failed guesses of the same kind mean the diagnosis is wrong — not the implementation.

Protocol — in order, no skipping

1. REPRODUCE   deterministically. Can't reproduce → THAT is the task now,
               not fixing blind.
2. READ        the actual, full error output. Not your memory of a similar
               error — most of the time the answer is already in the output.
3. LOCALIZE    to the smallest failing unit: bisect commits, halve inputs,
               instrument boundaries. Instrument BEFORE speculating.
4. HYPOTHESIZE in one sentence: "It fails because X."
               Can't write that sentence → return to 3.
5. EXPERIMENT  with the smallest change that tests ONLY the hypothesis.
               One variable at a time.
6. FIX         — and first capture the failing case as a test where
               possible: red→green proves the test tests the right thing.
7. RE-VERIFY   with the exact check that originally failed, then the full
               gate (build + tests), not just the local one.

The two-strike rule

Two fixes of the same class have failed → STOP. The bug is in your diagnosis, not your implementation. Return to step 3 assuming "my hypothesis was wrong." A third attempt at the same idea is forbidden — looping on a wrong theory is the most expensive failure mode there is.

Anti-patterns

  • ✗ Pattern-match fixes — "I've seen this, it's probably X" — without reading the real output. A similar symptom is not the same cause.
  • ✗ Shotgun fixes: changing several things at once. Even if it passes, you won't know why.
  • ✗ Suppressing the error to get green: catch-and-ignore, loosening an assertion. Allowed only with an explicit statement of why the CHECK was wrong, not the code.
  • ✗ Labeling a failure "flaky" without running it 5 times. Instability is data, not an excuse.
  • ✗ Restarting / clearing / reinstalling as step 1. A state reset can mask the bug and destroy the evidence.

Relationship to other skills

  • Runs inside universal-loop Step 5 (Loop): the loop counts iterations; this protocol makes each iteration count.
  • After the fix, verification-before-completion gates the "done" claim.
  • When even re-diagnosis has failed and the user reports failure again, escalate per compounding-engineering §5: fresh context, carrying evidence, not hypotheses.

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