deep-dive-analysis

name

deep-dive-analysis

description

AI-powered systematic codebase analysis. Combines structure extraction with semantic understanding to produce documentation capturing WHAT, WHY, HOW, and CONSEQUENCES. Multi-language: Python, Java, JavaScript, TypeScript, SQL, PL/SQL, Rust. Includes pattern recognition, red flag detection, flow tracing, and quality assessment. TRIGGER WHEN: encountering unfamiliar code, before major refactoring, or when documentation is stale or missing DO NOT TRIGGER WHEN: the task is outside the specific scope of this component.

Deep Dive Analysis Skill

Overview

This skill combines mechanical structure extraction with Claude's semantic understanding to produce comprehensive codebase documentation. Unlike simple AST parsing, this skill captures:

• WHAT the code does (structure, functions, classes)
• WHY it exists (business purpose, design decisions)
• HOW it integrates (dependencies, contracts, flows)
• CONSEQUENCES of changes (side effects, failure modes)

Language Support

Language	Extensions	Structural extraction	Comment rewriting
Python	.py, .pyi	stdlib ast (always available)	# line + docstrings
Java	.java	tree-sitter (preferred) or regex	//, /* */, Javadoc /** */
JavaScript	.js, .mjs, .cjs, .jsx	tree-sitter (preferred) or regex	//, /* */, JSDoc /** */
TypeScript	.ts, .tsx, .mts, .cts	tree-sitter (preferred) or regex; adds interfaces, enums, type aliases	//, /* */, JSDoc /** */
SQL	.sql, .ddl, .dml	regex DDL (tables, views, indexes, sequences, types, functions, procedures, triggers)	--, /* */
PL/SQL (Oracle)	.pks, .pkb, .plsql, .pls, .pck, .prc, .fnc, .trg	regex (packages, package bodies, type bodies, cursors, exceptions, %TYPE/%ROWTYPE references)	--, /* */
Rust	.rs	tree-sitter (preferred) or regex; structs, enums, traits, impls (with Trait for Type naming), mods, unions, type aliases	//, /* */, rustdoc /// / //! / /** */ / /*! */

.sql files are disambiguated against PL/SQL by inspecting content for Oracle-specific markers (CREATE OR REPLACE PACKAGE, DBMS_OUTPUT, %TYPE, %ROWTYPE, UTL_FILE, PRAGMA AUTONOMOUS, etc.). PostgreSQL plpgsql is correctly classified as SQL.

Prerequisites

The scripts are designed to work out of the box with just the Python stdlib. Tree-sitter is optional and improves accuracy for Java / JavaScript / TypeScript:

# Optional: install for higher-fidelity parsing
pip install -r scripts/requirements.txt
# or
uv pip install -r scripts/requirements.txt

What changes when tree-sitter is installed:

• Java: nested classes, generic type parameters, annotations, multi-line declarations parsed correctly. Without it, the regex fallback still finds top-level classes, methods, imports, and constants.
• JavaScript / TypeScript: arrow functions in object/class properties, decorators, template literals, JSX elements parsed correctly. Without it, the regex fallback handles top-level declarations, ES6 import/export, and CommonJS require.
• Rust: lifetimes, generic bounds (where clauses), impl blocks with trait bounds, attribute macros parsed correctly. Without it, the regex fallback still finds top-level fns, structs/enums/traits/impls/mods, use declarations, and UPPER_CASE constants.
• Python / SQL / PL-SQL: no change. Python always uses stdlib ast; SQL/PL-SQL always use the regex DDL extractor.

The active parser is reported in ParseResult.notes and in the CLI output: parser=stdlib-ast, parser=tree-sitter, or parser=regex-fallback.

Capabilities

Mechanical Analysis (Scripts):

• Extract code structure (classes, functions, imports)
• Map dependencies (internal/external)
• Find symbol usages across the codebase
• Track analysis progress
• Classify files by criticality

Semantic Analysis (Claude AI):

• Recognize architectural and design patterns
• Identify red flags and anti-patterns
• Trace data and control flows
• Document contracts and invariants
• Assess quality and maintainability

Documentation Maintenance:

• Review and maintain documentation (Phase 8)
• Fix broken links and update navigation indexes
• Analyze and rewrite code comments (antirez standards)

Use this skill when:

• Analyzing a codebase you're unfamiliar with
• Generating documentation that explains WHY, not just WHAT
• Identifying architectural patterns and anti-patterns
• Performing code review with semantic understanding
• Onboarding to a new project

Prerequisites

This skill is invoked by the /deep-dive-analysis command. The command creates and manages state automatically in .deep-dive/ under the target directory:

1. .deep-dive/state.json -- phase tracking (auto-created by the command)
2. .deep-dive/<phase-number>-<name>.md -- per-phase output documents

The legacy standalone flow using analysis_progress.json and DEEP_DIVE_PLAN.md at project root is no longer the primary path -- prefer invoking /deep-dive-analysis <target>.

CRITICAL PRINCIPLE: ABSOLUTE SOURCE OF TRUTH

THE DOCUMENTATION GENERATED BY THIS SKILL IS THE ABSOLUTE AND UNQUESTIONABLE SOURCE OF TRUTH FOR YOUR PROJECT.

ANY INFORMATION NOT VERIFIED WITH IRREFUTABLE EVIDENCE FROM SOURCE CODE IS FALSE, UNRELIABLE, AND UNACCEPTABLE.

Mandatory Rules (VIOLATION = FAILURE)

1. NEVER document anything without reading the actual source code first
2. NEVER assume any existing documentation, comment, or docstring is accurate
3. NEVER write documentation based on memory, inference, or "what should be"
4. ALWAYS derive truth EXCLUSIVELY from reading and tracing actual code
5. ALWAYS provide source file + qualified symbol name for every technical claim
6. ALWAYS verify state machines, enums, constants against actual definitions
7. TREAT all pre-existing docs as unverified claims requiring validation
8. MARK any unverifiable statement as [UNVERIFIED - REQUIRES CODE CHECK]
9. USE qualified symbol names in markers (file.py::Class.method), never line numbers -- line numbers break on any edit

See references/analysis-templates.md for the full verification trust model, temporal purity principle, and documentation status markers.

Output Usage Guide

After analysis completes, consult the right file for your task:

Your Task	Start With	Also Check
Onboarding / understanding the project	07-final-report, 01-structure	04-semantics
Writing new feature	01-structure (Where to Add), 02-interfaces	04-semantics
Fixing a bug	03-flows, 05-risks	01-structure
Refactoring	01-structure, 04-semantics, 05-risks	03-flows
Code review	02-interfaces, 05-risks	06-documentation
Updating documentation	06-documentation, 04-semantics	02-interfaces

Forbidden Files

The analysis NEVER reads or includes contents from sensitive files: .env, .env.*, credentials.*, secrets.*, *.pem, *.key, *.p12, *.pfx, id_rsa*, id_ed25519*, .npmrc, .pypirc, .netrc, or any file containing API keys, passwords, or tokens. If encountered, note file existence only - never quote contents.

Available Commands

1. Analyze Single File

# Python
python .claude/skills/deep-dive-analysis/scripts/analyze_file.py \
  --file src/utils/circuit_breaker.py \
  --output-format markdown

# Java
python .claude/skills/deep-dive-analysis/scripts/analyze_file.py \
  --file src/main/java/com/example/UserService.java

# TypeScript
python .claude/skills/deep-dive-analysis/scripts/analyze_file.py \
  --file src/services/auth.ts

# SQL / PL-SQL
python .claude/skills/deep-dive-analysis/scripts/analyze_file.py \
  --file migrations/0042_users.sql

python .claude/skills/deep-dive-analysis/scripts/analyze_file.py \
  --file packages/user_pkg.pkb

Parameters:

• --file / -f: Relative path to file - REQUIRED. Any supported extension (see Language Support table).
• --output-format / -o: Output format (json, markdown, summary) - default: summary
• --find-usages / -u: Find all usages of exported symbols - default: false
• --update-progress / -p: Update analysis_progress.json - default: false

2. Check Progress

python .claude/skills/deep-dive-analysis/scripts/check_progress.py \
  --phase 1 --status pending

3. Find Usages

python .claude/skills/deep-dive-analysis/scripts/analyze_file.py \
  --symbol CircuitBreaker --file src/utils/circuit_breaker.py

4. Generate Phase Report

python .claude/skills/deep-dive-analysis/scripts/analyze_file.py \
  --phase 1 --output-format markdown --output-file docs/01_domains/COMMON_LIBRARY.md

---

Phase 8: Documentation Review Commands

5. Scan Documentation Health

python .claude/skills/deep-dive-analysis/scripts/doc_review.py scan \
  --path docs/ --output doc_health_report.json

6. Validate Links

python .claude/skills/deep-dive-analysis/scripts/doc_review.py validate-links \
  --path docs/ --fix

7. Verify Against Source Code

python .claude/skills/deep-dive-analysis/scripts/doc_review.py verify \
  --doc docs/agents/lifecycle.md --source src/agents/lifecycle.py

8. Update Navigation Indexes

python .claude/skills/deep-dive-analysis/scripts/doc_review.py update-indexes \
  --search-index docs/00_navigation/SEARCH_INDEX.md \
  --by-domain docs/00_navigation/BY_DOMAIN.md

9. Full Documentation Maintenance

python .claude/skills/deep-dive-analysis/scripts/doc_review.py full-maintenance \
  --path docs/ --auto-fix --output doc_health_report.json

Executes: scan health, validate/fix links, identify obsolete files, update indexes, generate report.

---

Comment Quality Commands (Antirez Standards)

10. Analyze Comment Quality

python .claude/skills/deep-dive-analysis/scripts/rewrite_comments.py analyze \
  src/main.py --report

11. Scan Directory for Comment Issues

python .claude/skills/deep-dive-analysis/scripts/rewrite_comments.py scan \
  src/ --recursive --issues-only

12. Generate Comment Health Report

python .claude/skills/deep-dive-analysis/scripts/rewrite_comments.py report \
  src/ --output comment_health.md

13. Rewrite Comments

python .claude/skills/deep-dive-analysis/scripts/rewrite_comments.py rewrite \
  src/main.py --apply --backup

14. View Standards Reference

python .claude/skills/deep-dive-analysis/scripts/rewrite_comments.py standards

---

File Classification Criteria

Classification	Criteria	Verification
Critical	Handles authentication, security, encryption, sensitive data	Mandatory
High-Complexity	>300 LOC, >5 dependencies, state machines, async patterns	Mandatory
Standard	Normal business logic, data models, utilities	Recommended
Utility	Pure functions, helpers, constants	Optional

---

AI-Powered Semantic Analysis

Five Layers of Understanding

Layer	What	Who Does It
1. WHAT	Classes, functions, imports	Scripts (AST)
2. HOW	Algorithm details, data flow	Claude's first pass
3. WHY	Business purpose, design decisions	Claude's deep analysis
4. WHEN	Triggers, lifecycle, concurrency	Claude's behavioral analysis
5. CONSEQUENCES	Side effects, failure modes	Claude's systems thinking

Pattern Recognition

Pattern Type	Examples	Documentation Focus
Architectural	Repository, Service, CQRS, Event-Driven	Responsibilities, boundaries
Behavioral	State Machine, Strategy, Observer, Chain	Transitions, variations
Resilience	Circuit Breaker, Retry, Bulkhead, Timeout	Thresholds, fallbacks
Data	DTO, Value Object, Aggregate	Invariants, relationships
Concurrency	Producer-Consumer, Worker Pool	Thread safety, backpressure

Red Flags to Identify

ARCHITECTURE:
- GOD CLASS: >10 public methods or >500 LOC
- CIRCULAR DEPENDENCY: A -> B -> C -> A
- LEAKY ABSTRACTION: Implementation details in interface

RELIABILITY:
- SWALLOWED EXCEPTION: Empty catch blocks
- MISSING TIMEOUT: Network calls without timeout
- RACE CONDITION: Shared mutable state without sync

SECURITY:
- HARDCODED SECRET: Passwords, API keys in code
- SQL INJECTION: String concatenation in queries
- MISSING VALIDATION: Unsanitized user input

AI Analysis Workflow

1. SCRIPTS RUN FIRST -> classifier.py, ast_parser.py, usage_finder.py
2. CLAUDE ANALYZES -> Read source, apply semantic questions, recognize patterns, identify red flags
3. CLAUDE DOCUMENTS -> Use template, explain WHY not just WHAT, document contracts
4. VERIFY -> Check against runtime behavior, validate with code traces

Analysis Loop Workflow

1. CLASSIFY -> LOC, dependencies, critical patterns, assign classification
2. READ & MAP -> AST structure, classes, functions, constants, state mutations
3. DEPENDENCY CHECK -> Internal imports, external imports, external calls
4. CONTEXT ANALYSIS -> Symbol usages, importing modules, message flows
5. RUNTIME VERIFICATION (Critical/High-Complexity) -> Log analysis, flow verification
6. DOCUMENTATION -> Update progress, generate report, cross-reference

Best Practices

Source Code Analysis (Phases 1-7)

1. Start with Phase 1 - foundation modules inform everything else
2. Track progress with --update-progress
3. Never skip runtime verification for critical/high-complexity files
4. Cross-reference with CONTEXT.md after analysis

Documentation Maintenance (Phase 8)

1. Run scan first to understand current state
2. Fix links before content - broken links indicate structural issues
3. Verify against code before updating documentation
4. Update indexes last to reflect final state

Team Mode Integration

The classic /deep-dive-analysis command runs three subagents in two waves on a single target. For monorepos, multi-language repos, or large codebases where a single deep-dive's context window grows uncomfortable, switch to the team variant:

/deep-dive-analysis:team-deep-dive <target>

The team command:

1. Auto-detects partitions (workspaces, top-level dirs, or language clusters) and asks you to confirm at a checkpoint.
2. Spawns three deep-dive workers per partition in two waves (Wave 1 = Structure; Wave 2 = Behavior + Quality). Wave 2 workers read every partition's Wave 1 output, so cross-partition contracts and flows can be cited directly.
3. Synthesizes a backward-compatible .deep-dive/01..07.md set that any downstream consumer (/senior-review:team-review, /codebase-mapper:map-codebase, /project-setup:create-claude-md) can pick up without changes.
4. Adds .deep-dive/08-interconnect-map.md produced by senior-review:semantic-interconnect-mapper on top of the consolidated set, giving a global Call Graph, Contracts, Invariants, and Integration Hot-Spots view.

Choosing between classic and team

Repo profile	Use classic	Use team
Single package, < 200 files, one language	✓
Monorepo (pnpm/npm/yarn/lerna/nx/turbo workspaces)		✓
Multi-language (Python + TS, etc.) at top level		✓
You want a global interconnection map produced in the same run		✓
You want --phase N or --docs-only control	✓

Output layout (team mode)

.deep-dive/
├── state.json
├── partitions/
│   └── <name>/{01..06}.md          ← per-partition reports
├── 01-structure.md .. 07-final-report.md   ← consolidated (compat with classic)
└── 08-interconnect-map.md          ← new, global cross-partition map

See docs/plans/2026-05-20-deep-dive-team-mode-design.md for the full architecture.

References

• references/analysis-templates.md - Verification trust model, temporal purity principle, documentation status markers, comment classification, maintenance workflows
• references/AI_ANALYSIS_METHODOLOGY.md - Complete analysis methodology
• references/SEMANTIC_PATTERNS.md - Pattern recognition guide
• references/ANTIREZ_COMMENTING_STANDARDS.md - Comment taxonomy
• references/DEEP_DIVE_PLAN.md - Master analysis plan with all phase definitions
• templates/semantic_analysis.md - AI-powered per-file analysis template
• templates/analysis_report.md - Module-level report template

Resources

• Scripts: scripts/ - analysis tools (Python runtime, multi-language targets)
  • ast_parser.py - structural extraction dispatcher (Phases 1-7)
  • analyze_file.py - per-file CLI (classification + structure + usages)
  • classifier.py - language-aware criticality classifier
  • usage_finder.py - cross-file symbol usage finder (multi-language extensions)
  • comment_rewriter.py - multi-language comment analysis engine
  • rewrite_comments.py - comment quality CLI (scan / analyze / rewrite / report)
  • doc_review.py - documentation maintenance (Phase 8)
  • check_progress.py / progress_tracker.py - phase progress tracking
  • languages/ - per-language adapters (Python ast, Java/JS/TS/Rust via tree-sitter or regex, SQL/PL-SQL regex)
    • base.py - shared dataclasses + LanguageAdapter Protocol
    • __init__.py - extension dispatch (detect_language, get_adapter)
    • comments.py - per-language comment lexer (includes rustdoc post-processor)
    • _treesitter.py - optional tree-sitter loader with fallbacks
    • python.py, java.py, javascript.py, typescript.py, sql.py, plsql.py, rust.py
  • requirements.txt - optional dependencies (tree-sitter + language-pack, click)