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Deep analysis

Skill sequenzia/agent-alchemy/ported/20260304-102613/core-tools/skills/deep-analysis

Agent Alchemy is a curated collection of plugins, apps, and extensions designed to elevate your agentic engineering workflows. Built for Claude Code and other AI coding agents, these tools help developers work smarter and ship faster.

Install
npx -y skills add sequenzia/agent-alchemy --skill deep-analysis

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Deep exploration and synthesis workflow with dynamic planning and hub-and-spoke coordination. Use for deep analysis, deep understanding, or codebase investigation.

SKILL.md

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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:

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

    • Direct invocation: The user invoked this skill 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 settings are missing, use defaults
    • If the settings are 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):

    • 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 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.

  1. Determine analysis context:

    • Accept the following inputs: an analysis context or focus area
    • If no inputs and this skill was loaded by another skill, use the calling skill's context
    • If no inputs 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 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.

  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: 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
    
  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:** [patterns]
    - **Complexity:** [Low/Medium/High]
    - **Assigned to:** explorer-1
    
    #### Focus Area 2: [Label]
    - **Directories:** [list]
    - **Starting files:** [2-3 files]
    - **Search patterns:** [patterns]
    - **Complexity:** [Low/Medium/High]
    - **Assigned to:** explorer-2
    
    [... repeated for each focus area]
    
    ### Worker 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 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, worker 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: Set up workers, create tasks, and assign work using the approved plan.

  1. Prepare workers: Based on the approved plan, prepare the following workers:

    • N explorers (one per focus area): Refer to the code-explorer skill for exploration behavior. Each explorer investigates their assigned focus area independently.
    • 1 synthesizer: Refer to the code-synthesizer skill for synthesis behavior. The synthesizer has shell access for git history, dependency analysis, and static analysis.
  2. Create tasks: For each focus area, create an exploration task with: subject ("Explore: [Focus area label]"), detailed exploration instructions including directories, starting files, search terms, and complexity estimate.

    Create a synthesis task: "Synthesize and evaluate exploration findings" -- blocked by all exploration tasks.

  3. Assign exploration tasks: For each exploration task, delegate to the corresponding explorer worker with the task details: focus area label, directories, starting files, and search patterns.

  4. Checkpoint (if ENABLE_CHECKPOINTING = true):

    • Update .agents/sessions/__da_live__/checkpoint.md: set current_phase: 3, record worker names, task assignments
    • Append to progress.md: [timestamp] Phase 3: Team assembled -- [N] explorers, 1 synthesizer

Phase 4: Focused Exploration

Goal: Workers explore their assigned areas independently.

Monitoring

After assigning exploration tasks, monitor progress:

  1. When an explorer completes, record their findings. If ENABLE_CHECKPOINTING = true, write explorer-{N}-findings.md to .agents/sessions/__da_live__/ and update checkpoint.
  2. Workers explore independently -- no cross-worker communication (hub-and-spoke topology)
  3. Workers can respond to follow-up questions from the synthesizer
  4. Each worker marks its task as completed when done
  5. Wait for all exploration tasks to complete before proceeding to Phase 5

Phase 5: Evaluation and Synthesis

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

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
  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
    • Wait for the follow-up to complete
  4. If all produced content: proceed immediately to Step 2

Step 2: Launch Synthesis

  1. Assign the synthesis task to the synthesizer worker

  2. Provide the synthesizer with:

    • Analysis context and codebase path
    • Reconnaissance findings from Phase 1
    • The list of explorer workers (for follow-up questions if needed)
    • Instructions to read exploration task results, synthesize into a unified analysis, and evaluate completeness before finalizing
  3. The synthesizer has shell access for deep investigation -- git history analysis, dependency trees, static analysis, or any investigation that basic file reading cannot handle

  4. Wait for the synthesizer to complete

  5. 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 clean up.

  1. Collect synthesis output:

    • Read the synthesis results from the synthesizer
  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. Shut down workers: Signal all workers that analysis is complete and they can stop.

  5. Archive session and cleanup:

    • If ENABLE_CHECKPOINTING = true: Move .agents/sessions/__da_live__/ to .agents/sessions/da-{timestamp}/
    • Clean up any temporary team/task resources

Error Handling

Settings Check Failure

  • If settings exist but are malformed or unparseable: warn the user ("Settings 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
  • 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:

Interrupted AtRecovery Strategy
Phase 1Restart from Phase 1 (reconnaissance is fast, ~1-2 min)
Phase 2Load saved team_plan.md from session dir, re-present for approval
Phase 3Load approved plan from checkpoint, restart team assembly
Phase 4Read completed explorer-{N}-findings.md files from session dir. Only assign explorers whose findings files are missing. Add existing findings to synthesizer context.
Phase 5Load all explorer findings from session dir. Launch a fresh synthesizer with the persisted findings.
Phase 6Load synthesis.md from session dir. Proceed directly to present/return results and cleanup.

Recovery procedure:

  1. Read checkpoint.md to determine last_completed_phase and session state (worker names, task assignments)
  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

Coordination

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

Integration Notes

What this component does: Orchestrates a multi-phase deep analysis workflow: reconnaissance, dynamic planning, user approval, parallel exploration via independent workers, synthesis with deep investigation, caching, and session checkpointing/recovery.

Origin: Skill (orchestrator, keystone)

Capabilities needed:

  • File reading, writing, and search (for reconnaissance, caching, checkpointing)
  • Shell command execution (for the synthesizer's deep investigation: git history, dependency trees, static analysis)
  • User interaction/prompting (for approval flow, cache decisions, session recovery)
  • Task/worker delegation (for spawning explorer and synthesizer workers)
  • Background task monitoring (for tracking explorer completion)

Adaptation guidance:

  • The hub-and-spoke coordination pattern originally used platform-specific TeamCreate/TaskCreate/SendMessage/TaskUpdate APIs. Adapt to whatever task delegation and messaging mechanism the target harness provides.
  • Explorer workers were originally spawned as Sonnet-tier agents; the synthesizer as Opus-tier. If the target harness supports model selection, preserve this tiering for cost efficiency.
  • Session checkpointing writes to .agents/sessions/__da_live__/. If the target harness has its own session/state management, adapt accordingly.
  • The approval flow uses interactive prompts. If the target harness is non-interactive, default to auto-approval.

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