deep-analysis

What this skill does

# Deep Analysis Workflow

Execute a structured exploration + synthesis workflow using Agent Teams with hub-and-spoke coordination. The lead performs rapid reconnaissance to generate dynamic focus areas, composes a team plan for review, workers explore independently, and a synthesizer merges findings with Bash-powered investigation.

This skill can be invoked standalone or loaded by other skills as a reusable building block. Approval behavior is configurable via `.claude/agent-alchemy.local.md`.

## Settings Check

**Goal:** Determine whether the team plan requires user approval before execution.

1. **Read settings file:**
   - Check if `.claude/agent-alchemy.local.md` exists
   - If it exists, read it and look for a `deep-analysis` section with nested settings:
     ```markdown
     - **deep-analysis**:
       - **direct-invocation-approval**: true
       - **invocation-by-skill-approval**: false
     ```
   - If the file does not exist or is malformed, use defaults (see step 4)

2. **Determine invocation mode:**
   - **Direct invocation:** The user invoked `/deep-analysis` directly, or you are running this skill standalone
   - **Skill-invoked:** Another skill (e.g., codebase-analysis, feature-dev, docs-manager) loaded and is executing this workflow

3. **Resolve settings:**
   - If settings were found, use them as-is
   - If the file is missing or the `deep-analysis` section is absent, use defaults:
     - `direct-invocation-approval`: `true`
     - `invocation-by-skill-approval`: `false`
   - If the file exists but is malformed (unparseable), warn the user and use defaults

4. **Set `REQUIRE_APPROVAL`:**
   - If direct invocation → use `direct-invocation-approval` value (default: `true`)
   - If skill-invoked → use `invocation-by-skill-approval` value (default: `false`)

5. **Parse session settings** (also under the `deep-analysis` section):
   ```markdown
   - **deep-analysis**:
     - **cache-ttl-hours**: 24
     - **enable-checkpointing**: true
     - **enable-progress-indicators**: true
   ```
   - `cache-ttl-hours`: Number of hours before exploration cache expires. Default: `24`. Set to `0` to disable caching entirely.
   - `enable-checkpointing`: Whether to write session checkpoints at phase boundaries. Default: `true`.
   - `enable-progress-indicators`: Whether to display `[Phase N/6]` progress messages. Default: `true`.

6. **Set behavioral flags:**
   - `CACHE_TTL` = value of `cache-ttl-hours` (default: `24`)
   - `ENABLE_CHECKPOINTING` = value of `enable-checkpointing` (default: `true`)
   - `ENABLE_PROGRESS` = value of `enable-progress-indicators` (default: `true`)

---

## Phase 0: Session Setup

**Goal:** Check for cached exploration results, detect interrupted sessions, and initialize the session directory.

> Skip this phase entirely if `CACHE_TTL = 0` AND `ENABLE_CHECKPOINTING = false`.

### Step 1: Exploration Cache Check

If `CACHE_TTL > 0`:

1. Check if `.claude/sessions/exploration-cache/manifest.md` exists
2. If found, read the manifest and verify:
   - `analysis_context` matches the current analysis context (or is a superset)
   - `codebase_path` matches the current working directory
   - `timestamp` is within `CACHE_TTL` hours of now
   - Config files referenced in `config_checksum` haven't been modified since the cache was written (check mod-times of `package.json`, `tsconfig.json`, `pyproject.toml`, etc.)
3. **If cache is valid:**
   - **Skill-invoked mode:** Auto-accept the cache. Set `CACHE_HIT = true`. Read cached `synthesis.md` and `recon_summary.md`. Skip to Phase 6 step 2 (present/return results).
   - **Direct invocation:** Use `AskUserQuestion` to offer:
     - **"Use cached results"** — Set `CACHE_HIT = true`, skip to Phase 6 step 2
     - **"Refresh analysis"** — Set `CACHE_HIT = false`, proceed normally
4. **If cache is invalid or absent:** Set `CACHE_HIT = false`

### Step 2: Interrupted Session Check

If `ENABLE_CHECKPOINTING = true`:

1. Check if `.claude/sessions/__da_live__/checkpoint.md` exists
2. If found, read the checkpoint to determine `last_completed_phase`
3. Use `AskUserQuestion` to offer:
   - **"Resume from Phase [N+1]"** — Load checkpoint state, proceed from the interrupted phase (see Session Recovery in Error Handling)
   - **"Start fresh"** — Archive the interrupted session to `.claude/sessions/da-interrupted-{timestamp}/` and proceed normally
4. If not found: proceed normally

### Step 3: Initialize Session Directory

If `ENABLE_CHECKPOINTING = true` AND `CACHE_HIT = false`:

1. Create `.claude/sessions/__da_live__/` directory
2. Write `checkpoint.md`:
   ```markdown
   ## Deep Analysis Session
   - **analysis_context**: [context from arguments or caller]
   - **codebase_path**: [current working directory]
   - **started**: [ISO timestamp]
   - **current_phase**: 0
   - **status**: initialized
   ```
3. Write `progress.md`:
   ```markdown
   ## Deep Analysis Progress
   - **Phase**: 0 of 6
   - **Status**: Session initialized

   ### Phase Log
   - [timestamp] Phase 0: Session initialized
   ```

---

## Phase 1: Reconnaissance & Planning

**Goal:** Perform codebase reconnaissance, generate dynamic focus areas, and compose a team plan.

> If `ENABLE_PROGRESS = true`: Display "**[Phase 1/6] Reconnaissance & Planning** — Mapping codebase structure..."

1. **Determine analysis context:**
   - If `$ARGUMENTS` is provided, use it as the analysis context (feature area, question, or general exploration goal)
   - If no arguments and this skill was loaded by another skill, use the calling skill's context
   - If no arguments and standalone invocation, set context to "general codebase understanding"
   - Set `PATH = current working directory`
   - Inform the user: "Exploring codebase at: `PATH`" with the analysis context

2. **Rapid codebase reconnaissance:**
   Use Glob, Grep, and Read to quickly map the codebase structure. This should take 1-2 minutes, not deep investigation.

   - **Directory structure:** List top-level directories with `Glob` (e.g., `*/` pattern) to understand the project layout
   - **Language and framework detection:** Read config files (`package.json`, `tsconfig.json`, `pyproject.toml`, `Cargo.toml`, `go.mod`, etc.) to identify primary language(s) and framework(s)
   - **File distribution:** Use `Glob` with patterns like `src/**/*.ts`, `**/*.py` to gauge the size and shape of different areas
   - **Key documentation:** Read `README.md`, `CLAUDE.md`, or similar docs if they exist for project context
   - **For feature-focused analysis:** Use `Grep` to search for feature-related terms (function names, component names, route paths) to find hotspot directories
   - **For general analysis:** Identify the 3-5 largest or most architecturally significant directories

   **Fallback:** If reconnaissance fails (empty project, unusual structure, errors), use the static focus area templates from Step 3b.

3. **Generate dynamic focus areas:**

   Based on reconnaissance findings, create focus areas tailored to the actual codebase. Default to 3 focus areas, but adjust based on codebase size and complexity (2 for small projects, up to 4 for large ones).

   **a) Dynamic focus areas (default):**

   Each focus area should include:
   - **Label:** Short description (e.g., "API layer in src/api/")
   - **Directories:** Specific directories to explore
   - **Starting files:** 2-3 key files to read first
   - **Search terms:** Grep patterns to find related code
   - **Complexity estimate:** Low/Medium/High based on file count and apparent structure

   For feature-focused analysis, focus areas should track the feature's actual footprint:
   ```
   Example:
   Focus 1: "API routes and middleware in src/api/ and src/middleware/" (auth-related endpoints, request handling)
   Focus 2: "React components in src/pages/profile/ and src/components/user/" (UI layer for user profiles)
   Focus 3: "Data models and services in src/db/ and src/services/" (persistence and business logic)
   ```

   For general