Defame1297
00c1e6b305
Body 1126 -> 808 words, clearing the FAIL tier, and description 290 -> 220 chars. Phase 1's depth moves to references/feedback-loops.md; the six-phase spine stays in the body, since a linear procedure is not a dispatch case. The description rewrite was not originally in scope, which was an error: adding a mandatory boundary clause to a 290-char description cannot land under 400. The dropped capability chain was also inaccurate -- it named 'minimise' as a phase that does not exist while omitting the one phase the body calls 'This is the skill'. A clean-context audit found no text lost but three reachability defects, all fixed: content stranded behind an inverted trigger, Phase 2's reproduction-rate threshold defined only in a file that path never loaded, and a script path that did not resolve from the file carrying it. The two reference files are merged into one, since the split is what created the first two. Refs #99
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name, description
| name | description |
|---|---|
| diagnose | Use when the user says "diagnose this" or "debug this", reports something broken, throwing, or failing, or says something got slow. Not filing or triaging a reported bug -> `triage`. Not test-first feature work -> `tdd`. |
Diagnose
A discipline for hard bugs. Skip phases only when explicitly justified.
When exploring the codebase, use the project's domain glossary to get a clear mental model of the relevant modules, and check ADRs in the area you're touching.
Phase 1 — Build a feedback loop
This is the skill. Everything else is mechanical. If you have a fast, deterministic, agent-runnable pass/fail signal for the bug, you will find the cause — bisection, hypothesis-testing, and instrumentation all just consume that signal. If you don't have one, no amount of staring at code will save you.
Spend disproportionate effort here. Be aggressive. Be creative. Refuse to give up.
Read references/feedback-loops.md — even if you already have a signal. Ten ways to build a loop ordered by cost, how to sharpen the one you have, and what to do when the bug resists reproduction. An unsharpened loop is usually not good enough yet.
Do not proceed to Phase 2 until you have a loop you believe in. If you cannot build one, stop and say so explicitly, listing what you tried — never hypothesise without a signal.
Phase 2 — Reproduce
Run the loop. Watch the bug appear.
Confirm:
- The loop produces the failure mode the user described — not a different failure that happens to be nearby. Wrong bug = wrong fix.
- The failure is reproducible across multiple runs. If it is intermittent,
references/feedback-loops.mddefines the rate high enough to debug against — go back to Phase 1 and raise it. - You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix actually addresses it.
Do not proceed until you reproduce the bug.
Phase 3 — Hypothesise
Generate 3–5 ranked hypotheses before testing any of them. Single-hypothesis generation anchors on the first plausible idea.
Each hypothesis must be falsifiable: state the prediction it makes.
Format: "If is the cause, then will make the bug disappear / will make it worse."
If you cannot state the prediction, the hypothesis is a vibe — discard or sharpen it.
Show the ranked list to the user before testing. They often have domain knowledge that re-ranks instantly ("we just deployed a change to #3"), or know hypotheses they've already ruled out. Cheap checkpoint, big time saver. Don't block on it — proceed with your ranking if the user is AFK.
Phase 4 — Instrument
Each probe must map to a specific prediction from Phase 3. Change one variable at a time.
Tool preference:
- Debugger / REPL inspection if the env supports it. One breakpoint beats ten logs.
- Targeted logs at the boundaries that distinguish hypotheses.
- Never "log everything and grep".
Tag every debug log with a unique prefix, e.g. [DEBUG-a4f2]. Cleanup at the end becomes a single grep. Untagged logs survive; tagged logs die.
Perf branch. For performance regressions, logs are usually wrong. Instead: establish a baseline measurement (timing harness, performance.now(), profiler, query plan), then bisect. Measure first, fix second.
Phase 5 — Fix + regression test
Write the regression test before the fix — but only if there is a correct seam for it.
A correct seam is one where the test exercises the real bug pattern as it occurs at the call site. If the only available seam is too shallow (single-caller test when the bug needs multiple callers, unit test that can't replicate the chain that triggered the bug), a regression test there gives false confidence.
If no correct seam exists, that itself is the finding. Note it. The codebase architecture is preventing the bug from being locked down. Flag this for the next phase.
If a correct seam exists:
- Turn the Phase 1 loop into a failing test at that seam, narrowed to the symptom captured in Phase 2.
- Watch it fail.
- Apply the fix.
- Watch it pass.
- Re-run the Phase 1 feedback loop against the original, un-narrowed scenario.
Phase 6 — Cleanup + post-mortem
Required before declaring done:
- Original repro no longer reproduces (re-run the Phase 1 loop)
- Regression test passes (or absence of seam is documented)
- All
[DEBUG-...]instrumentation removed (grepthe prefix) - Throwaway prototypes deleted (or moved to a clearly-marked debug location)
- The hypothesis that turned out correct is stated in the commit / PR message — so the next debugger learns
Then ask: what would have prevented this bug? If the answer involves architectural change (no good test seam, tangled callers, hidden coupling) hand off to the /improve-codebase-architecture skill with the specifics. Make the recommendation after the fix is in, not before — you have more information now than when you started.