Deep Analysis

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 shell-powered investigation.

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

Accept the following inputs:

• analysis-context (optional): The focus area, feature, or question to analyze. Defaults to "general codebase understanding" if not provided.

Settings Check

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

1. Read settings file:

   • Check if .agents/agent-alchemy.local.md exists
   • If it exists, read it and look for a deep-analysis section with nested settings:

     - **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 it is running 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):

   - **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 .agents/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: Prompt the user to choose:
     • "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 .agents/sessions/__da_live__/checkpoint.md exists
2. If found, read the checkpoint to determine last_completed_phase
3. Prompt the user to choose:
   • "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 .agents/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 .agents/sessions/__da_live__/ directory
2. Write checkpoint.md:

   ## 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:

   ## 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 analysis-context input is provided, use it as the analysis context (feature area, question, or general exploration goal)
   • If no input and this skill was loaded by another skill, use the calling skill's context
   • If no input 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: Quickly map the codebase structure. This should take 1-2 minutes, not deep investigation.

   • Directory structure: Search for top-level directories (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: Search for files matching 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.

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: Search 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 analysis, focus areas should map to the codebase's actual structure:

   Example:
   Focus 1: "Next.js app layer in apps/web/src/" (pages, components, app router)
   Focus 2: "Shared library in packages/core/src/" (utilities, types, shared logic)
   Focus 3: "CLI and tooling in packages/cli/" (commands, configuration, build)
   

   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
   

4. Compose the team plan:

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

   ## 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 files:** [2-3 files]
   - **Search patterns:** [search patterns]
   - **Complexity:** [Low/Medium/High]
   - **Assigned to:** explorer-1
   
   #### Focus Area 2: [Label]
   - **Directories:** [list]
   - **Starting files:** [2-3 files]
   - **Search patterns:** [search patterns]
   - **Complexity:** [Low/Medium/High]
   - **Assigned to:** explorer-2
   
   [... repeated for each focus area]
   
   ### Agent Composition
   | Role | Count | Purpose |
   |------|-------|---------|
   | Explorer | [N] | Independent focus area exploration |
   | Synthesizer | 1 | Merge findings, deep investigation |
   
   ### Task Dependencies
   - Exploration Tasks 1-[N]: parallel (no dependencies)
   - Synthesis Task: blocked by all exploration tasks
   

5. Checkpoint (if ENABLE_CHECKPOINTING = true):

   • Update .agents/sessions/__da_live__/checkpoint.md: set current_phase: 1
   • Write .agents/sessions/__da_live__/team_plan.md with the full team plan from Step 4
   • Write .agents/sessions/__da_live__/recon_summary.md with reconnaissance findings from Step 2
   • Append to progress.md: [timestamp] Phase 1: Reconnaissance complete — [N] focus areas identified

Phase 2: Review & Approval

Goal: Present the team plan for user review and approval before allocating resources.

If ENABLE_PROGRESS = true: Display "[Phase 2/6] Review & Approval — Presenting team plan..."

If REQUIRE_APPROVAL = false

Skip to Phase 3 with a brief note: "Auto-approving team plan (skill-invoked mode). Proceeding with [N] explorers and 1 synthesizer."

If REQUIRE_APPROVAL = true

1. Present the team plan to the user (output the plan from Phase 1 Step 4), then prompt the user to choose:

   • "Approve" — Proceed to Phase 3 as-is
   • "Modify" — User describes changes (adjust focus areas, add/remove explorers, change scope)
   • "Regenerate" — Re-run reconnaissance with user feedback

2. If "Modify" (up to 3 cycles):

   • Ask what to change
   • Apply modifications to the team plan (adjust focus areas, agent count, scope)
   • Re-present the updated plan for approval
   • If 3 modification cycles are exhausted, offer "Approve current plan" or "Abort analysis"

3. If "Regenerate" (up to 2 cycles):

   • Ask for feedback/new direction
   • Return to Phase 1 Step 2 with the user's feedback incorporated
   • Re-compose and re-present the team plan
   • If 2 regeneration cycles are exhausted, offer "Approve current plan" or "Abort analysis"

4. Checkpoint (if ENABLE_CHECKPOINTING = true):

   • Update .agents/sessions/__da_live__/checkpoint.md: set current_phase: 2, record approval_mode (approved/auto-approved)
   • Append to progress.md: [timestamp] Phase 2: Plan approved (mode: [approval_mode])

Phase 3: Team Assembly

Goal: Assemble a team of agents, create tasks, and assign work using the approved plan.

If ENABLE_PROGRESS = true: Display "[Phase 3/6] Team Assembly — Creating team and assigning agents..."

1. Assemble the team:

   • Create a team named deep-analysis-{timestamp} (e.g., deep-analysis-1707300000)
   • Description: "Deep analysis of [analysis context]"

2. Delegate to teammates: Based on the approved plan, assign teammates:

   • N explorers (one per focus area) — using the code-explorer skill

     • Named: explorer-1, explorer-2, ... explorer-N
     • Prompt each with: "You are part of a deep analysis team. Wait for your task assignment. The codebase is at: [PATH]. Analysis context: [context]"

   • 1 synthesizer — using the code-synthesizer skill

     • Named: synthesizer
     • Prompt with: "You are the synthesizer for a deep analysis team. You have shell command access for git history, dependency analysis, and static analysis. Wait for your task assignment. The codebase is at: [PATH]. Analysis context: [context]"

3. Track sub-tasks: Create a task for each work item based on the approved plan's focus areas:

   • Exploration Task per focus area: Subject: "Explore: [Focus area label]", Description: detailed exploration instructions including directories, starting files, search terms, and complexity estimate
   • Synthesis Task: Subject: "Synthesize and evaluate exploration findings", Description: "Merge and synthesize findings from all exploration tasks into a unified analysis. Investigate gaps using shell commands (git history, dependency trees). Evaluate completeness before finalizing."
     • The synthesis task is blocked by all exploration tasks

4. Assign exploration tasks (with status guard):

   For each exploration task, apply the following status-guarded assignment:

   1. Check the task's current status and owner
   2. Only assign if status is pending AND owner is empty
   3. If already assigned or completed: log "Task [ID] already [status], skipping" and move on
   4. Set the owner to the corresponding explorer
   5. Communicate the task details to the explorer: "Your exploration task [ID] is assigned. Focus area: [label]. Directories: [list]. Starting files: [list]. Search patterns: [list]. Begin exploration now."

   Never re-assign a completed or in-progress task.

5. Checkpoint (if ENABLE_CHECKPOINTING = true):

   • Update .agents/sessions/__da_live__/checkpoint.md: set current_phase: 3, record team_name, explorer_names (list), task_ids (map of explorer to task ID), synthesis_task_id
   • Append to progress.md: [timestamp] Phase 3: Team assembled — [N] explorers, 1 synthesizer

Phase 4: Focused Exploration

Goal: Workers explore their assigned areas independently.

If ENABLE_PROGRESS = true: Display "[Phase 4/6] Focused Exploration — 0/[N] explorers complete"

Monitoring Loop

After assigning exploration tasks, monitor progress with status-aware tracking:

1. When an explorer goes idle or sends a message, check their task status
2. If task is completed: Record the explorer's findings. If ENABLE_CHECKPOINTING = true, write explorer-{N}-findings.md to .agents/sessions/__da_live__/ and update checkpoint.
3. If task is in_progress: The explorer is still working — do NOT re-send the assignment
4. If task is pending and owner is set: The explorer received the assignment but hasn't started yet — wait, do NOT re-send
5. If task is pending and owner is empty: Assignment may have been lost — re-assign using the status guard from Phase 3 step 4

Never re-assign a completed or in-progress task. This is the primary duplicate prevention mechanism.

If ENABLE_PROGRESS = true: Update the progress display as explorers complete: "[Phase 4/6] Focused Exploration — [completed]/[N] explorers complete"

• Workers explore their assigned focus areas independently — no cross-worker messaging
• Workers can respond to follow-up questions from the synthesizer
• Each worker marks its task as completed when done
• The lead receives idle notifications as workers finish
• Wait for all exploration tasks to be marked complete before proceeding to Phase 5

Phase 5: Evaluation and Synthesis

Goal: Verify exploration completeness, launch synthesis with deep investigation.

If ENABLE_PROGRESS = true: Display "[Phase 5/6] Synthesis — Merging findings and investigating gaps..."

Step 1: Structural Completeness Check

This is a structural check, not a quality assessment:

1. Verify all exploration tasks are completed
2. Check that each worker produced a report with content (review the messages/reports received)
3. If a worker failed completely (empty or error output):
   • Create a follow-up exploration task targeting the gap
   • Assign it to an idle worker
   • Add the new task to the synthesis task's blocked-by list
   • Wait for the follow-up task to complete
4. If all produced content: proceed immediately to Step 2

Step 2: Launch Synthesis

1. Assign the synthesis task to the synthesizer

2. Communicate the exploration context and recon findings to the synthesizer: "All exploration tasks are complete. Your synthesis task is now assigned.

   Analysis context: [analysis context] Codebase path: [PATH]

   Recon findings from planning phase:

   • Project structure: [brief summary of directory layout]
   • Primary language/framework: [what was detected]
   • Key areas identified: [the focus areas and why they were chosen]

   The workers are: [list of explorer names from the approved plan]. You can message them with follow-up questions if you find conflicts or gaps in their findings.

   You have shell command access for deep investigation — use it for git history analysis, dependency trees, static analysis, or any investigation that file reading and searching can't handle.

   Read the completed exploration tasks to access their reports, then synthesize into a unified analysis. Evaluate completeness before finalizing."

3. Wait for the synthesizer to mark the synthesis task as completed

4. Checkpoint (if ENABLE_CHECKPOINTING = true):

   • Update .agents/sessions/__da_live__/checkpoint.md: set current_phase: 5
   • Write .agents/sessions/__da_live__/synthesis.md with the synthesis results
   • Append to progress.md: [timestamp] Phase 5: Synthesis complete

Phase 6: Completion + Cleanup

Goal: Collect results, present to user, and disband the team.

If ENABLE_PROGRESS = true: Display "[Phase 6/6] Completion — Collecting results and cleaning up..."

1. Collect synthesis output:

   • The synthesizer's findings are in the messages it sent and/or the task completion output
   • Read the synthesis results

2. Write exploration cache (if CACHE_TTL > 0):

   • Create .agents/sessions/exploration-cache/ directory (overwrite if exists)
   • Write manifest.md:

     ## Exploration Cache Manifest
     - **analysis_context**: [the analysis context used]
     - **codebase_path**: [current working directory]
     - **timestamp**: [ISO timestamp]
     - **config_checksum**: [comma-separated list of config files and their mod-times]
     - **ttl_hours**: [CACHE_TTL value]
     - **explorer_count**: [N]
     

   • Write synthesis.md with the full synthesis output
   • Write recon_summary.md with the Phase 1 reconnaissance findings
   • Write explorer-{N}-findings.md for each explorer's findings (if not already persisted from Phase 4 checkpoints)

3. Present or return results:

   • Standalone invocation: Present the synthesized analysis to the user. The results remain in conversation memory for follow-up questions.
   • Loaded by another skill: The synthesis is complete. Control returns to the calling workflow — do not present a standalone summary.

4. Archive session and disband the team:

   • If ENABLE_CHECKPOINTING = true: Move .agents/sessions/__da_live__/ to .agents/sessions/da-{timestamp}/
   • Disband the team and its task list

Error Handling

Settings Check Failure

• If .agents/agent-alchemy.local.md exists but is malformed or the deep-analysis section is unparseable: warn the user ("Settings file found but could not parse deep-analysis settings — using defaults") and proceed with default approval values.

Planning Phase Failure

• If reconnaissance fails (errors, empty results, unusual structure): fall back to static focus area templates (Step 3b)
• If the codebase appears empty: inform the user and ask how to proceed

Approval Phase Failure

• If maximum modification cycles (3) or regeneration cycles (2) are reached without approval, prompt the user to choose:
  • "Approve current plan" — Proceed with the latest version of the plan
  • "Abort analysis" — Cancel the analysis entirely

Partial Worker Failure

• If one worker fails: create a follow-up task targeting the missed focus area, assign to an idle worker, add to synthesis blocked-by list
• If two workers fail: attempt follow-ups, but if they also fail, instruct the synthesizer to work with partial results
• If all workers fail: inform the user and offer to retry or abort

Synthesizer Failure

• If the synthesizer fails: present the raw exploration results to the user directly
• Offer to retry synthesis or let the user work with partial results

General Failures

If any phase fails:

1. Explain what went wrong
2. Ask the user how to proceed:
   • Retry the phase
   • Continue with partial results
   • Abort the analysis

Session Recovery

When resuming from an interrupted session (detected in Phase 0 Step 2), use the following per-phase strategy:

Recovery procedure:

1. Read checkpoint.md to determine last_completed_phase and session state (team_name, explorer_names, task_ids)
2. Load any persisted artifacts from the session directory (team_plan, explorer findings, synthesis)
3. Resume from Phase last_completed_phase + 1 using the loaded state
4. For Phase 4 recovery: compare persisted explorer-{N}-findings.md files against expected explorer list to determine which explorers still need to run

Agent Coordination

• The lead (you) acts as the planner: performs recon, composes the team plan, handles approval, assigns work
• Workers explore independently — no cross-worker messaging (hub-and-spoke topology)
• The synthesizer can ask workers follow-up questions to resolve conflicts and fill gaps
• The synthesizer has shell command access for deep investigation (git history, dependency trees, static analysis)
• Wait for task dependencies to resolve before proceeding
• Handle agent failures gracefully — continue with partial results
• Agent count and focus area details come from the approved plan, not hardcoded values

Integration Notes

What this component does: Orchestrates a multi-agent codebase exploration and synthesis workflow using hub-and-spoke coordination with dynamic planning, caching, and session recovery.

Capabilities needed:

• File reading, file search, and content search (for reconnaissance)
• Shell command execution (for the synthesizer's deep investigation)
• Agent/sub-task spawning (to create explorer and synthesizer workers)
• Inter-agent messaging (hub-and-spoke communication)
• Task tracking (to manage exploration and synthesis tasks)
• File writing (for session checkpoints and cache)

Adaptation guidance:

• This skill originally spawned code-explorer (sonnet-tier) and code-synthesizer (opus-tier) as sub-agents via a team/task system. In the target harness, adapt to whatever agent spawning or background task mechanism is available.
• The hub-and-spoke pattern means the lead coordinates all workers; workers never communicate with each other directly.
• If the target harness doesn't support agent teams, this workflow can be serialized: run each exploration focus area sequentially, then run synthesis on the collected findings.
• Session checkpointing writes to .agents/sessions/ — adapt the path to the target harness's session storage.

Configurable parameters:

• deep-analysis.direct-invocation-approval — Whether to require plan approval when invoked directly (default: true)
• deep-analysis.invocation-by-skill-approval — Whether to require approval when loaded by another skill (default: false)
• deep-analysis.cache-ttl-hours — Hours before exploration cache expires; 0 disables caching (default: 24)
• deep-analysis.enable-checkpointing — Write session checkpoints at phase boundaries for recovery (default: true)
• deep-analysis.enable-progress-indicators — Display progress messages during execution (default: true)