Diagnosing Bugs

---
name: diagnosing-bugs
description: "Use when executing, coordinating, planning, or reviewing diagnosing bugs agent workflows, cognitive loops, and architecture standards."
version: 6.0.0
last-updated: 2026-09-29
skills:
  - systematic-debugging
  - test-result-analyzer
  - tdd-workflow
tools: Read, Grep, Glob, Bash, Edit, Write
scripts-binding:
  - .agent/scripts/test_runner.js
  - .agent/scripts/verify_all.js
  - .agent/scripts/lint_runner.js
---

# Diagnosing Bugs — A Discipline for Hard Bugs

## Mandatory Pre-Flight Context Inspection
Before reading, generating, or refactoring code in the `diagnosing-bugs` domain, inspect these 5 critical parameters:
1. **System Boundaries & Dependencies**: Verify that all required dependencies exist in target package manifests and environment paths.
2. **Runtime Context & Platform Invariants**: Confirm target platform constraints (Node.js, Browser, Mobile OS, Edge runtime) before applying APIs.
3. **Execution Guardrails**: Identify potential side-effects, state mutations, and unhandled asynchronous exceptions.
4. **Validation & Type Contracts**: Validate input data schemas and strict type constraints across all module interfaces.
5. **Observability & Proof of Execution**: Ensure execution produces tangible verification signals (terminal output, tests, metrics).


## Activation Boundaries
- **Activate when:** Use when executing, coordinating, planning, or reviewing diagnosing bugs agent workflows, cognitive loops, and architecture standards.
- **DO NOT activate when:** The task falls outside the `diagnosing-bugs` domain or is managed by a different dedicated specialist agent.


## 🔁 Multi-Pass Execution Protocol

| Pass | Phase | Core Action | Adaptive Depth |
|:---|:---|:---|:---|
| **Pass 1** | **Understand** | Deconstruct the user's explicit objective, implicit requirements, and platform constraints. | Fast / Standard / Deep |
| **Pass 2** | **Plan** | Decompose task into smallest logical steps; map dependencies, affected files, and tool calls. | Standard / Deep |
| **Pass 3** | **Execute** | Implement solution with production-grade craft, zero placeholders, and strict typing. | All Modes |
| **Pass 4** | **Verify** | Run linters, unit tests, or compiler checks to validate structural correctness. | All Modes |
| **Pass 5** | **Attack & Falsify** | Perform adversarial search for edge-case failures, counterexamples, race conditions, and traps. | Standard / Deep |
| **Pass 6** | **Harden** | Eliminate discovered friction, optimize performance, and harden error boundaries. | Standard / Deep |
| **Pass 7** | **Quality Gate** | Enforce Verification-Before-Completion (VBC) with concrete terminal proof before finalizing. | All Modes |


---

## 🛠️ Technical Architecture & Reference Recipes

---

## Protocol Overview

```
Phase 1: Build a Feedback Loop ──► Phase 2: Reproduce + Minimise ──► Phase 3: Hypothesise
                                                                               │
Phase 6: Cleanup + Post-Mortem ◄── Phase 5: Fix + Regression Test ◄── Phase 4: Instrument
```

---

## Phase 1 — Build a Feedback Loop

This is the core 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.

### 10 Strategies to Construct a Feedback Loop (in priority order)

1. **Failing Test at Whatever Seam Reaches the Bug**: Unit, integration, or E2E test.
2. **Curl / HTTP Script**: Send requests against a running dev server.
3. **CLI Invocation with Fixture Input**: Diffing stdout/stderr 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 run `git bisect`.
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 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.)

> ⚡ **Debugging Superpower**: A 30-second flaky loop is barely better than no loop; a 2-second deterministic one is 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:

1. Access to whatever environment reproduces it.
2. A captured artifact (HAR file, log dump, core dump, screen recording with timestamps).
3. Permission to add temporary production instrumentation.

_Do not proceed to hypothesise without a loop._

### Phase 1 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 (paste the invocation and its output), and that is:

- ✅ **Red-capable**: Drives the actual bug code path and asserts the user's exact symptom, going red on this bug and green once fixed. Not "runs without erroring" — it must catch this specific bug.
- ✅ **Deterministic**: Same verdict every run (or high, pinned reproduction rate).
- ✅ **Fast**: Seconds, not minutes.
- ✅ **Agent-runnable**: Runnable unattended (HITL only via `scripts/hitl-loop.template.sh`).

_If you catch yourself reading code to build a theory before this command exists, stop. No red-capable command, no Phase 2._

---

## Phase 2 — Reproduce + Minimise

Run the loop. Watch it go red — the bug appears.

### Confirm

1. The loop produces the failure mode the user described — not a different failure nearby. (Wrong bug = wrong fix.)
2. The failure is reproducible across multiple runs (or at a high enough reproduction rate).
3. You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix 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 single one makes the loop go green.**

---

## 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 [X] is the cause, then [Y] 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. (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 environment supports it. One breakpoint beats ten logs.
2. **Targeted Logs**: Place logs at boundaries that distinguish hypotheses. Never "log everything and grep".
3. **Tag Every Debug Log**: Prefix every debug log with a unique tag, e.g. `[DEBUG-a4f2]`. Cleanup at the end becomes a single grep.
4. **Performance Profiling Branch**: For performance regressions, 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, note it. The codebase architecture is preventing the bug from being locked down. Flag this for Phase 6.

### 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 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 debug location)
- [ ] Correct hypothesis stated in commit / PR message

### Post-Mortem Handoff

Ask: **What would have prevented this bug?** If the answer involves architectural debt (no good test seam, tangled callers, hidden coupling), hand off to `/improve-codebase-architecture` with specific findings.

## 🚨 Edge-Case & Failure Mode Matrix

| Scenario | Risk | Production Mitigation |
|:---|:---|:---|
| **Empty or Null Inputs** | Unhandled exception or unexpected rendering collapse | Enforce fallback guards, optional chaining, and explicit empty state handlers |
| **Network Timeout / Latency** | Hanging operations or duplicate side-effects | Implement bounded abort controllers, exponential backoff, and idempotency keys |
| **Concurrency / Race Conditions** | Stale state overwrite or inconsistent data mutations | Use atomic transactions, mutex locking, or cancel-on-resubmit controls |
| **Invalid Schema / Malformed Payload** | Downstream runtime errors or security injection | Validate boundary payloads with Zod/Pydantic schemas prior to execution |
| **Resource / Memory Saturation** | OOM errors, frame drops, or memory leaks | Clean up listeners, cancel active timers, and enforce pagination/virtualization |


## 🤖 LLM-Specific Traps Table

| Anti-Pattern | What AI Commonly Does Wrong | What Is Actually Correct |
|:---|:---|:---|
| **Hallucinated Tool Capabilities** | Assuming an external library or CLI command exists without verification | Run a verification check or verify package.json before referencing tools |
| **Premature Completion Claim** | Declaring a task finished because code was generated without verification | Execute tests, linters, or terminal commands to provide concrete proof |
| **Context Bloat Dumping** | Pasting entire multi-thousand-line files into prompt context | Extract targeted excerpts, symbols, and signatures to preserve tokens |


## 🏛️ Tribunal Verification & Guardrails

**Active Reviewers:** `orchestrator` · `agent-organizer` · `logic-reviewer`
**Slash Command:** `/review` or `/tribunal-full`

### 🔬 Evidence Standard (Tri-State Verification)
Every finding, audit statement, or completion claim must classify its factual certainty:
- **`[OBSERVED]`**: Directly confirmed in the codebase or verified via executed terminal command.
- **`[INFERRED]`**: Logically deduced from code patterns, architectural data flow, or schema relations.
- **`[UNVERIFIED]`**: Speculative hypothesis or runtime possibility requiring active testing or measurement.

### ✅ Pre-Flight Self-Audit Checklist
```
✅ Did I deconstruct the root objective before proposing architecture?
✅ Did I identify dependencies, bottlenecks, and parallelizable sub-tasks?
✅ Did I avoid over-engineering and select the simplest effective pattern?
✅ Did I verify assumptions with concrete file reads instead of speculation?
✅ Did I establish measurable verification criteria before completion?
```

### 🛑 Verification-Before-Completion (VBC) Protocol
**CRITICAL:** You must follow a strict "evidence-based closeout" state machine.
- ❌ **Forbidden:** Declaring a task complete because the output "looks correct."
- ✅ **Required:** You are explicitly forbidden from finalizing any task without providing **concrete evidence** (terminal output, passing test suites, compiler success, or equivalent operational proof) that your output works as intended.