Use when a bug resists the obvious fix, behaviour makes no sense, a symptom keeps coming back, a test is flaky, something "worked last week", or the user asks why something happens and the answer is not on the surface — including mid-build when a second fix attempt fails. Do NOT use for bugs with a clear repro and an obvious cause (reproduce, fix, re-run directly), security incident triage (bulletproof), or reviewing a diff (code-review).
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---
name: root-cause
description: Use when a bug resists the obvious fix, behaviour makes no sense, a symptom keeps coming back, a test is flaky, something "worked last week", or the user asks why something happens and the answer is not on the surface — including mid-build when a second fix attempt fails. Do NOT use for bugs with a clear repro and an obvious cause (reproduce, fix, re-run directly), security incident triage (bulletproof), or reviewing a diff (code-review).
---
# Root-Cause
Build a feedback loop, then let evidence kill hypotheses. Each phase has a gate. Keep a hypothesis log in your replies: `H# | prediction | experiment | result | verdict`.
## Phase 1 — Build the loop
ONE command that reproduces the failure on demand. Cheapest first: failing test → curl/script → CLI run → headless browser script → trace replay → minimal harness.
Gate: **red-capable**, **deterministic**, **fast** (seconds), **agent-runnable**. Run it red. No red command, no Phase 2.
- **Flaky?** Run it N times (e.g. 20–50) and record the fail rate; that rate is the signal. Vary one thing at a time (order, seed, parallelism, timing) until it is deterministic or the rate moves.
- **Worked before?** With a known-good commit and the loop as a script: `git bisect start <bad> <good>`, then `git bisect run <script>` (exit 0 = good, 125 = skip untestable commit, any other 1–127 = bad). Always `git bisect reset` after. Ask first if the tree has uncommitted work.
## Phase 2 — Shrink it
Remove input, config, and code until removing anything more makes it pass (delta debugging: halve, test, keep the failing half). What survives is implicated. Already minimal? Say so.
## Phase 3 — Hypotheses
3–5 falsifiable one-liners, each naming the observation that would kill it. Rank by likelihood × cheapness. Show the list (non-blocking).
## Phase 4 — One variable
Test one hypothesis at a time, cheapest first. Never change two things between runs. Instrument boundaries (inputs, outputs, timing), not everything; prefer existing logging/tracing or the debugger. Tag new debug output `[DBG-xxxx]` (random suffix) so removal is one grep.
## Phase 5 — Regression test before fix
Write the failing regression test FIRST at a real seam. No honest seam? Record that as a finding and test at the nearest honest boundary. No suite and none requested? Keep the repro script as the check — never introduce a suite unasked.
## Phase 6 — Close out
If the ask was "why", stop at the answer and the fix it implies — change code only when the user asks for the fix. Otherwise fix, run the loop green (flaky: N runs, zero failures), run the regression test, grep-remove every `[DBG-xxxx]`, and state the cause in one sentence: cause → mechanism → symptom. Label claims `RUNTIME` / `CODE` / `DEDUCED`.
Hard rules: three failed fixes → the hypothesis list is wrong; return to Phase 3. Redact secrets from any quoted or committed log line.
## Scaling: one agent or several
- Reproduction, shrinking, and experiments: main thread only — one variable at a time.
- Wide codebase (several packages could own the bug): in Phase 3 you may send one read-only `owl` per hypothesis in a single `spawn_agent` call; brief = symptom, repro command, paths, "return file:line evidence for/against; do not run or edit". Treat replies as `CODE` leads to re-open, not verdicts.
Sources (accessed 3 October 2026): https://git-scm.com/docs/git-bisect; https://www.debuggingbook.org/html/DeltaDebugger.html