diagnosing-bugs

---title: diagnosing-bugsname: diagnosing-bugsdescription: Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.---# Diagnosing BugsA discipline for hard bugs. Skip phases only when explicitly justified.When exploring the codebase, read `AGENTS.md` to get a clear mental model of the project, and check `PAPERCUTS.md` — a past session may have already hit the detour you're about to take.## Phase 1 — Build a feedback loop**This is the skill.** Everything else is mechanical. If you have a **tight** pass/fail signal for the bug — one that goes red on _this_ bug — you will find the cause; bisection, hypothesis-testing, and instrumentation all just consume it. 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.**### Ways to construct one — try them in roughly this order1. **Failing test** at whatever seam reaches the bug — unit, integration, e2e.2. **Curl / HTTP script** against a running dev server.3. **CLI invocation** with a fixture input, diffing stdout against a known-good snapshot.4. **Headless browser script** (Playwright / Puppeteer) — drives the UI, asserts on DOM/console/network.5. **Replay a captured trace.** Save a real network request / payload / event log to disk; replay it through the code path in isolation.6. **Throwaway harness.** Spin up a minimal subset of the system (one service, mocked deps) that exercises the bug code path with a single function call.7. **Property / fuzz loop.** If the bug is "sometimes wrong output", run 1000 random inputs and look for the failure mode.8. **Bisection harness.** If the bug appeared between two known states (commit, dataset, version), automate "boot at state X, check, repeat" so you can `git bisect run` it.9. **Differential loop.** Run the same input through old-version vs new-version (or two configs) and diff outputs.10. **HITL bash script.** Last resort. If a human must click, drive _them_ with `scripts/hitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.Build the right feedback loop, and the bug is 90% fixed.### Tighten the loopTreat the loop as a product. Once you have _a_ loop, **tighten** it:- Can I make it faster? (Cache setup, skip unrelated init, narrow the test scope.)- Can I make the signal sharper? (Assert on the specific symptom, not "didn't crash".)- Can I make it more deterministic? (Pin time, seed RNG, isolate filesystem, freeze network.)A 30-second flaky loop is barely better than no loop; a 2-second deterministic one is tight — a debugging superpower.### Non-deterministic bugsThe goal is not a clean repro but a **higher reproduction rate**. Loop the trigger 100×, parallelise, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not — keep raising the rate until it's debuggable.### When you genuinely cannot build a loopStop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a captured artifact (HAR file, log dump, core dump, screen recording with timestamps), or (c) permission to add temporary production instrumentation. Do **not** proceed to hypothesise without a loop.### Completion criterion — a tight loop that goes redPhase 1 is done when the loop is **tight** and **red-capable**: you can name **one command** — a script path, a test invocation, a curl — that you have **already run at least once** (paste the invocation and its output), and that is:- [ ] **Red-capable** — it drives the actual bug code path and asserts the **user's exact symptom**, so it can go red on this bug and green once fixed. Not "runs without erroring" — it must be able to _catch this specific bug_.- [ ] **Deterministic** — same verdict every run (flaky bugs: a pinned, high reproduction rate, per above).- [ ] **Fast** — seconds, not minutes.- [ ] **Agent-runnable** — you can run it unattended; a human in the loop only via `scripts/hitl-loop.template.sh`.If you catch yourself reading code to build a theory before this command exists, **stop — jumping straight to a hypothesis is the exact failure this skill prevents.** No red-capable command, no Phase 2.## Phase 2 — Reproduce + minimiseRun the loop. Watch it go red — the bug appears.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 (or, for non-deterministic bugs, reproducible at a high enough rate to debug against).- [ ] You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix actually addresses it.### MinimiseOnce it's red, shrink the repro to the **smallest scenario that still goes red**. Cut inputs, callers, config, data, and steps **one at a time**, re-running the loop after each cut — keep only what's load-bearing for the failure.Why bother: a minimal repro shrinks the hypothesis space in Phase 3 (fewer moving parts left to suspect) and becomes the clean regression test in Phase 5.Done when **every remaining element is load-bearing** — removing any one of them makes the loop go green.Do not proceed until you have reproduced **and** minimised.## Phase 3 — HypothesiseGenerate **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 <X> is the cause, then <changing Y> will make the bug disappear / <changing Z> 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 — InstrumentEach probe must map to a specific prediction from Phase 3. **Change one variable at a time.**Tool preference:1. **Debugger / REPL inspection** if the env supports it. One breakpoint beats ten logs.2. **Targeted logs** at the boundaries that distinguish hypotheses.3. 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 testWrite 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:1. Turn the minimised repro into a failing test at that seam.2. Watch it fail.3. Apply the fix.4. Watch it pass.5. Re-run the Phase 1 feedback loop against the original (un-minimised) scenario.## Phase 6 — Cleanup + post-mortemRequired 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 (`grep` the 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- [ ] Detours worth remembering (a tool that failed repeatedly before a workaround, a misleading name, a surprise) appended to `PAPERCUTS.md`**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.