git:20260926.9bc2d60 to git:20261001.cc31a37

- A discipline for hard bugs. Skip phases only when explicitly justified.

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- 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.

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- ## Phase 1 — Build a feedback loop

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- **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.

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- Spend disproportionate effort here. **Be aggressive. Be creative. Refuse to give up.**

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- ### Ways to construct one — try them in roughly this order

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- 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 `scripts/hitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.

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- Build the right feedback loop, and the bug is 90% fixed.

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- ### Iterate on the loop itself

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- Treat the loop as a product. Once you have _a_ loop, ask:

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- - 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.)

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- A 30-second flaky loop is barely better than no loop. A 2-second deterministic loop is a debugging superpower.

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- ### Non-deterministic bugs

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- 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.

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- ### When you genuinely cannot build a loop

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- Stop 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.

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- Do not proceed to Phase 2 until you have a loop you believe in.

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- ## Phase 2 — Reproduce

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- Run the loop. Watch the bug appear.

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- Confirm:

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- - [ ] 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: remove inputs, steps, and code until removing anything else makes the bug disappear. Keep the original scenario for the Phase 5 re-run.

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- Do not proceed until you reproduce the bug.

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- ## Phase 3 — Hypothesise

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- Generate **3–5 ranked hypotheses** before testing any of them. Single-hypothesis generation anchors on the first plausible idea.

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- Each hypothesis must be **falsifiable**: state the prediction it makes.

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- > Format: "If <X> is the cause, then <changing Y> will make the bug disappear / <changing Z> will make it worse."

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- If you cannot state the prediction, the hypothesis is a vibe — discard or sharpen it.

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- **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.

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- ## Phase 4 — Instrument

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- Each probe must map to a specific prediction from Phase 3. **Change one variable at a time.**

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- Tool preference:

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- 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".

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- **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.

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- **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.

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- ## Phase 5 — Fix + regression test

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- Write the regression test **before the fix** — but only if there is a **correct seam** for it.

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- 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.

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- **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.

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- If a correct seam exists:

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- 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.

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- If three fixes have failed, stop: a hypothesis or the architecture is wrong. Report what each attempt showed and discuss before a fourth; structural causes go to `bosskuai-architecture-deepening`.

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- ## Phase 6 — Cleanup + post-mortem

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- Required before declaring done:

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- - [ ] 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

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- **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 `bosskuai-architecture-deepening` skill with the specifics. Make the recommendation **after** the fix is in, not before — you have more information now than when you started.

- ## References

- - `../../references/playbooks/root-cause-investigation-playbook.md` — incidents and high-value bugs that need more than a code read