---
name: Investigate
slug: investigate-4
category: Quality
description: Investigate traces software issues from symptoms back to root cause using evidence from code, logs, and tests. Use it when debugging bugs, failed integrations, or API behavior that needs a deep dive rather than a code review.
github: "https://github.com/testdouble/han/tree/main/han-coding/skills/investigate"
language: Shell
stars: 253
forks: 22
install: "npx degit https://github.com/testdouble/han/tree/main/han-coding/skills/investigate ~/.claude/skills/investigate"
installs_to: ~/.claude/skills/investigate
source_path: han-coding/skills/investigate/SKILL.md
collection_size: 25
category_size: 1418
collection_url: "https://dirskills.com/collections/testdouble/han"
added: 2026-09-02T05:20:51.251Z
last_synced: 2026-09-02T05:20:51.251Z
canonical_url: "https://dirskills.com/skills/investigate-4"
---

# Investigate

Investigate traces software issues from symptoms back to root cause using evidence from code, logs, and tests. Use it when debugging bugs, failed integrations, or API behavior that needs a deep dive rather than a code review.

**Install:**

```bash
npx degit https://github.com/testdouble/han/tree/main/han-coding/skills/investigate ~/.claude/skills/investigate
```

## README

## Project Context

- CLAUDE.md: !`find . -maxdepth 1 -name "CLAUDE.md" -type f`
- project-discovery.md: !`find . -maxdepth 3 -name "project-discovery.md" -type f`
- personal config directory: !`bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh" 2>/dev/null || echo "$HOME/.claude"`
- project .han/config.md: !`cat .han/config.md 2>/dev/null || echo ""`

As your first action, use the Read tool on `.han/config.md` inside the `personal config directory` path above. A read
that returns no file is no personal configuration: continue silently. When that file or the `project .han/config.md`
probe supplies content, apply it per [config-rule.md](../../references/config-rule.md), which governs precedence
between the two files, relative-path resolution, and what to do with a file that reads but cannot be used.

## Investigation Approach

- Trace backward from symptoms — don't guess, follow the code.
- Launch parallel `han-core:evidence-based-investigator` agents for different angles simultaneously — one for the error
  path, one for the data flow, one for recent changes.
- Add one or more specialist analysts **in parallel with** the investigators when the bug type calls for it
  (concurrency, data flow across boundaries, database or query behavior). Specialist analysts find root causes
  generalists miss.
- The `han-core:adversarial-validator` agent handles all three validation strategies (challenge evidence, challenge fix,
  challenge assumptions) internally.
- Apply the evidence rule from [../../references/evidence-rule.md](../../references/evidence-rule.md) to every finding.
  Codebase findings (file path, line number, log line, test output) carry the trust-class label "codebase" and stand on
  their citation. Web-source context (RFCs, vendor docs, Stack Overflow, blog posts) carries the trust-class label "web"
  and is subject to the corroboration gate when it drives the proposed fix. When the investigation hits a point where no
  evidence at any tier resolves a question, label the no-evidence state rather than guessing.
- Lazy-create the output sections. Include a section in the plan file only when the investigation produced meaningful
  content for it; omit any section that would be empty, and keep the sections that remain in the template's order. Never
  emit a heading with placeholder or "N/A" content.
- Invoke `han-communication:readability-guidance` to source the shared readability standard into your context, then
  apply it as you write the findings, holding the named audience: the engineer who will implement the fix and may be
  paged on the bug. Scope that frame per section so the technical specifics the engineer needs (function names, exact
  failing conditions, file:line citations) are preserved, never simplified away.

# Investigate

## Step 1: Research and Investigation

### Always dispatch

Launch at least 2 `han-core:evidence-based-investigator` agents in parallel, each investigating from a different angle —
for example, one tracing the error path and another following the data flow.

### Conditional specialist dispatch

Classify the bug from the user's symptom description before launching. Skip any specialist that does not apply. Dispatch
every applicable specialist in parallel with the `han-core:evidence-based-investigator` agents in the same message.

1. **Launch han-core:concurrency-analyst** — when the symptom involves intermittent failures, race conditions,
   deadlocks, ordering issues, stale reads after writes, timeouts, dropped messages, or anything that only reproduces
   under load or concurrent users. Prompt: "Investigate the concurrency and async behavior of the code paths implicated
   by this symptom: {symptom}. Focus on race conditions, lock ordering, shared-resource contention, async error
   handling, and missing cancellation/timeout handling. Return numbered findings keyed to file paths and line numbers."

2. **Launch han-core:behavioral-analyst** — when the symptom involves data transformed wrong, values lost between
   modules, errors swallowed, state mutated unexpectedly, or integration boundaries passing bad data. Prompt: "Trace the
   data flow for the code paths implicated by this symptom: {symptom}. Focus on data transformation across module
   boundaries, error propagation and loss, state mutation, and integration-boundary assumptions. Return numbered
   findings keyed to file paths and line numbers."

3. **Launch han-core:data-engineer** — when the symptom involves wrong data in the database, slow queries, N+1, lock
   contention, migration failures, unbounded scans, lost data, broken referential integrity, or isolation-level
   surprises. Prompt: "Investigate the schema, queries, migrations, and data-access code implicated by this symptom:
   {symptom}. Focus on the specific data-engineering principles violated and the concrete data-level impact. Return
   numbered findings keyed to file paths, line numbers, and schema or migration references."

Extra agents named in the project config's `## Extra Agents` list join this conditional-specialist pool under the same
symptom-driven selection, per [../../references/config-rule.md](../../references/config-rule.md): dispatch one only
when the classified bug type matches its stated specialty, and skip an entry that does not resolve to a dispatchable
agent with a one-line note.

After all agents complete (investigators and specialists), compile an **evidence summary** — a numbered list of concrete
findings (E1, E2, E3, ...) that will feed into the root cause analysis. Specialist findings go into the same E-series
list, tagged with the specialist's domain (e.g., `E3 (concurrency)`).

## Step 2: Document Root Cause

Write to the plan file using the template at [template.md](./references/template.md). Fill the sections in the workflow
order below; this is deliberately not the template's on-page order, which leads with the Summary and places the
supporting Evidence Summary, Validation Results, and Coding Standards Reference near the end for the reader. Fill in
these sections:

1. **Problem Statement** — document the symptoms, expected behavior, conditions under which it occurs, and impact.
2. **Evidence Summary** — consolidate evidence from all agents into a unified numbered list (E1, E2, E3, ...); merge
   duplicates and resolve conflicting findings while preserving each item's output structure.
3. **Root Cause Analysis** — write a one-to-three sentence summary of the root cause, then a detailed analysis
   referencing evidence items by number (e.g., "The handler passes an unvalidated ID (E1) to the service layer, which
   assumes non-nil (E3)").

## Step 3: Plan the Fix

Resolve project config: read CLAUDE.md's `## Project Discovery` section for docs, ADR, and coding-standards directories;
fall back to project-discovery.md; fall back to Glob defaults (`docs/`, `docs/adr/`, `docs/coding-standards/`). Search
found directories for relevant standards, ADRs, and docs. Also check `CLAUDE.md`, `AGENTS.md`, and linter/formatter
configs for coding standards. If none found, infer conventions from surrounding code.

Design a fix that **directly addresses the root cause** from Step 2 — fix the underlying problem, not symptoms. Then
fill in the remaining sections of [template.md](./references/template.md) in the plan file:

1. **Coding Standards Reference** — for each standard, convention, ADR, or pattern inferred from surrounding code that
   governs the fix, document what it is, where it was found (file path, ADR number, or "inferred from surrounding
   code"), and which files or changes it governs. If nothing governs the fix, omit the section per the lazy-create rule.
2. **Planned Fix** — write a one-sentence summary, then for each file that needs to change: full path from repo root,
   what will be modified/added/removed, which evidence items (E1, E2, ...) justify the change, which coding standards
   apply, and implementation specifics (new function signatures, changed logic, updated tests).

## Step 4: Validation (CRITICAL)

Launch `han-core:adversarial-validator` agents and pass them the complete evidence summary (all E1-EN items with full
code snippets), the root cause analysis, and the planned fix with all file changes. Do not summarize — the validator
needs verbatim detail to challenge effectively. Their job is adversarial — they must actively try to disprove the
findings and break the fix.

When counter-evidence is found, document it as a validation finding (V1, V2, ...), investigate whether it changes the
root cause analysis, adjust the plan (evidence, root cause, and fix sections) as needed, and fill in the **Adjustments
Made** section listing what changed and which validation finding triggered each change. When counter-evidence is not
found, document what was checked and why it supports the original findings, recording it as a validation finding
confirming the analysis.

After all validation is complete, incorporate the `han-core:adversarial-validator` agents' Confidence Assessment and
Remaining Risks into the plan.

## Step 5: Summary and User Review

Add the **Summary** section at the top of the plan file with one sentence each for: root cause (what caused the
problem), fix (what the planned changes will do), why correct (reference the strongest evidence), validation outcome
(what validation confirmed or changed), and remaining risks (reference the Confidence Assessment).

Once the write-up draft is complete, dispatch `han-communication:readability-editor` (one Agent call) to audit and
rewrite the findings against the readability standard. This is separate from the Step 4 adversarial-validator pass: that
pass checks the fix is correct (accuracy); this pass checks how the write-up reads. Keep both. Pass the editor the plan
file path and the named audience: the engineer who will implement the fix and may be paged on the bug; the editor reads
han-communication's own canonical rule, so pass no rule path. It must preserve every fact and operate on prose regions
only — never inside code fences, function signatures in code blocks, diagram bodies, or file:line citation identifiers.
Apply its rewrite to the plan file.

Then run the standardized readability self-check (the shared standard is in your context from
`han-communication:readability-guidance`) over the write-up's prose regions only — never inside code fences, function
signatures, diagram bodies, or file:line citation identifiers. Confirm each criterion and fix any failure before
presenting:

Run the readability rule's standardized self-check, which is already in your context from the `readability-guidance`
invocation above. Correct every failure before presenting. Its fidelity criterion is not optional: the standard governs
how the content is said, and drops a required fact only when the reader asked for less and losing it would not change
what they do next.

Present the plan file to the user for approval. The user can approve the plan (triggering implementation) or provide
feedback for revisions.