debugging — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited debugging (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
What it is: Debugging is the discipline of turning a broken behavior into a reproduced failure, isolating the cause, verifying the fix on the same evidence path, and preserving the case as a regression test.
Mental model: A debugging pass has six gates: reproduce the failure, reduce the scope, capture evidence at the failure point, form a hypothesis that explains all evidence, verify the fix with the same path, and add a regression test that fails without the fix.
Why it exists: Plausible explanations are cheap and often wrong. Debugging keeps the agent from patching the visible symptom before proving where the state first becomes wrong.
What it is NOT: It is not feature planning, architecture design, green-test refactoring, documentation, or test-strategy planning for a future change.
Common misconception: The newest change is not automatically the cause. It is only a hypothesis until it explains the failing path and the unaffected control paths.
The fastest way to fix a bug is usually the wrong fix. A working reproduction is worth more than a plausible hypothesis; a plausible hypothesis is worth more than a clever fix; a clever fix that skips the reproduction step ships the same bug again under a different name. When pressure is high the temptation to jump from symptom to patch is also high — resist it, because the cost of a wrong fix is paid again by the next person who hits the same failure with less context than you had.
Each step asks a question. The answer decides the next step. Do not skip steps to save time; the steps exist because skipping them is how bugs return.
| Step | Ask | If yes | If no |
|---|---|---|---|
| 1. Reproduce | Do you have a deterministic failing case? | Go to step 2 | Add logging, narrow inputs, or run the failing path in a loop until the failure is reliable |
| 2. Scope | Can you reproduce it in a surface smaller than the full system? | Go to step 3 | Bisect — halve the code path, data, or config and retry |
| 3. Evidence | Do you have the state at the moment of failure, not just the symptom after? | Go to step 4 | Add instrumentation at the boundary where state flips wrong |
| 4. Cause | Does your hypothesis explain ALL of the evidence, not just the visible symptom? | Go to step 5 | Form a better hypothesis — partial explanations hide shared root causes |
| 5. Verify | Does the same evidence path pass with the fix applied, and fail with it reverted? | Go to step 6 | The fix did not land or the cause was wrong — return to step 4 |
| 6. Regression test | Does the test you just wrote fail without the fix and pass with it? | Done | Your test is not isolating the cause — rewrite it |
This skill ships a comprehension-eval artifact at examples/evals/debugging.json. The Verification checklist below is the authoring gate for a completed debugging pass; the eval file is how this skill is graded by scripts/skill-audit.js --graded. Do not conflate them — the checklist is for the debugger, the eval is for the grader.
| Use instead | When |
|---|---|
refactor | The task is structural cleanup, not failure-driven diagnosis |
testing-strategy | The task is planning what to test, not chasing a known failure |
documentation | The task is explaining behavior, not fixing broken behavior |
<!-- skill-graph-context:start (generated — do not edit by hand) -->
Classification
software-engineering-methodtrueWhen to use
debugging-skillNot for
Related skills
testing-strategy, observability-modelinggenerative-ui, test-driven-development, testing-strategy, tool-call-strategyKeywords
debugging, tests fail in CI, used to work, reproduce failure, failing test, root cause, symptom vs cause, minimum reproduction, regression, what changed<!-- skill-graph-context:end -->
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.