diff --git a/skills/diagnosing-bugs/SKILL.md b/skills/diagnosing-bugs/SKILL.md new file mode 100644 index 0000000..2a5ad33 --- /dev/null +++ b/skills/diagnosing-bugs/SKILL.md @@ -0,0 +1,142 @@ +--- +name: diagnosing-bugs +description: Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow. +license: MIT +source: https://github.com/mattpocock/skills +--- + +# Diagnosing Bugs + +A discipline for hard bugs. Skip phases only when explicitly justified. + +When exploring the codebase, read `CONTEXT.md` (if it exists) to get a clear mental model of the relevant modules, and check ADRs in the area you're touching. + +## Redact + +This skill has you show commands, outputs and captured artifacts. **Redact every secret first** — write `` in its place. Build loops against env vars, so the credential stays in the environment rather than in what you show. Captured artifacts carry auth headers: quote only the lines that carry the signal. + +If the redacted output is not enough to diagnose the bug, say so and ask the user. + +## 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 order + +1. **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 a small structured bash wizard 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 loop + +Treat 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 bugs + +The 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 loop + +Stop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a redacted 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 red + +Phase 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** (show the invocation and its output, redacted), 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 a structured bash wizard. + +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 + minimise + +Run 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. + +### Minimise + +Once 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 — 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: + +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 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: + +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-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 (`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 + +**Then ask: what would have prevented this bug?** If the answer involves architectural change (no good test seam, tangled callers, hidden coupling) capture that as a separate follow-up task. Make the recommendation **after** the fix is in, not before — you have more information now than when you started.