deep-analysis

Deep Analysis Workflow

Execute a structured exploration + synthesis workflow using 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 deep investigation.

This skill can be invoked standalone or loaded by other skills as a reusable building block. Approval behavior is configurable.

Settings Check

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

1. Read settings:
2. Check configuration for deep-analysis settings
3. Look for a deep-analysis section with nested settings:
4. direct-invocation-approval: Whether to require plan approval when invoked directly (default: true)
5. invocation-by-skill-approval: Whether to require approval when loaded by another skill (default: false)

1. Determine invocation mode:
2. Direct invocation: The user invoked this skill directly, or it is running standalone
3. Skill-invoked: Another skill (e.g., codebase-analysis, feature-dev, docs-manager) loaded and is executing this workflow

1. Resolve settings:
2. If settings were found, use them as-is
3. If the settings are missing, use defaults
4. If the settings are malformed (unparseable), warn the user and use defaults

1. Set REQUIRE_APPROVAL:
2. If direct invocation: use direct-invocation-approval value (default: true)
3. If skill-invoked: use invocation-by-skill-approval value (default: false)

1. Parse session settings (also under the deep-analysis section):
2. cache-ttl-hours: Number of hours before exploration cache expires. Default: 24. Set to 0 to disable caching entirely.
3. enable-checkpointing: Whether to write session checkpoints at phase boundaries. Default: true.
4. enable-progress-indicators: Whether to display phase progress messages. Default: true.

1. Set behavioral flags:
2. CACHE_TTL = value of cache-ttl-hours (default: 24)
3. ENABLE_CHECKPOINTING = value of enable-checkpointing (default: true)
4. 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 .agents/sessions/exploration-cache/manifest.md exists
2. If found, read the manifest and verify:
3. analysis_context matches the current analysis context (or is a superset)
4. codebase_path matches the current working directory
5. timestamp is within CACHE_TTL hours of now
6. 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.)
7. If cache is valid:
8. 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).
9. Direct invocation: Prompt the user to choose:
10. Use cached results -- Set CACHE_HIT = true, skip to Phase 6 step 2
11. Refresh analysis -- Set CACHE_HIT = false, proceed normally
12. If cache is invalid or absent: Set CACHE_HIT = false

Step 2: Interrupted Session Check

If ENABLE_CHECKPOINTING = true:

1. Check if .agents/sessions/__da_live__/checkpoint.md exists
2. If found, read the checkpoint to determine last_completed_phase
3. Prompt the user to choose:
4. Resume from Phase [N+1] -- Load checkpoint state, proceed from the interrupted phase (see Session Recovery in Error Handling)
5. Start fresh -- Archive the interrupted session to .agents/sessions/da-interrupted-{timestamp}/ and proceed normally
6. If not found: proceed normally

Step 3: Initialize Session Directory

If ENABLE_CHECKPOINTING = true AND CACHE_HIT = false:

1. Create .agents/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

```

1. 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.

1. Determine analysis context:
2. Accept the following inputs: an analysis context or focus area
3. If no inputs and this skill was loaded by another skill, use the calling skill's context
4. If no inputs and standalone invocation, set context to "general codebase understanding"
5. Set PATH = current working directory
6. Inform the user: "Exploring codebase at: PATH" with the analysis context

1. Rapid codebase reconnaissance:

Quickly map the codebase structure. This should take 1-2 minutes, not deep investigation.

• Directory structure: Search for top-level directories 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: Search 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: Search file contents 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.

1. 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: Patterns to find related code
• Complexity estimate: Low/Medium/High based on file count and apparent structure

b) Static fallback focus areas (only if recon failed):

For feature-focused analysis: `` Focus 1: Explore entry points and user-facing code related to the context Focus 2: Explore data models, schemas, and storage related to the context Focus 3: Explore utilities, helpers, and shared infrastructure ``

For general codebase understanding: `` Focus 1: Explore application structure, entry points, and core logic Focus 2: Explore configuration, infrastructure, and shared utilities Focus 3: Explore shared utilities, patterns, and cross-cutting concerns ``

1. Compose the team plan:

Assemble a structured plan document from the reconnaissance and focus area findings:

```markdown ## Team Plan: Deep Analysis

### Analysis Context [context from Step 1]

### Reconnaissance Summary

• Project: [name/type]
• Primary language/framework: [detected]
• Codebase size: [file counts, key directories]
• Key observations: [2-3 bullets]

### Focus Areas

#### Focus Area 1: [Label]

• Directories: [list]
• **Starting fil