بنقرة واحدة
codebase-analysis
Analyzes codebase to find similar features, reusable utilities, and architectural patterns
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Analyzes codebase to find similar features, reusable utilities, and architectural patterns
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Seed JSON configuration files into database. Use ONCE at BAZINGA session initialization, BEFORE spawning PM.
Database operations for BAZINGA orchestration system. This skill should be used when agents need to save or retrieve orchestration state, logs, task groups, token usage, or skill outputs. Replaces file-based storage with concurrent-safe SQLite database. Use instead of writing to bazinga/*.json files or docs/orchestration-log.md.
Build complete agent prompts deterministically via Python script. Use BEFORE spawning any BAZINGA agent (Developer, QA, Tech Lead, PM, etc.).
Analyze existing tests to identify patterns, fixtures, and conventions before writing new tests
Assembles relevant context for agent spawns with prioritized ranking. Ranks packages by relevance, enforces token budgets with graduated zones, captures error patterns for learning, and supports configurable per-agent retrieval limits.
Run code quality linters when reviewing code. Checks style, complexity, and best practices. Supports Python (ruff), JavaScript (eslint), Go (golangci-lint), Ruby (rubocop), Java (Checkstyle/PMD). Use when reviewing any code changes for quality issues.
| version | 1.0.0 |
| name | codebase-analysis |
| description | Analyzes codebase to find similar features, reusable utilities, and architectural patterns |
| author | BAZINGA Team |
| tags | ["development","analysis","codebase","context"] |
| allowed-tools | ["Bash","Read"] |
You are the codebase-analysis skill. Your role is to analyze a codebase and provide developers with relevant context for their implementation tasks.
When invoked with a task description and session ID, you must:
python3 .claude/skills/codebase-analysis/scripts/analyze_codebase.py \
--task "$TASK_DESCRIPTION" \
--session "$SESSION_ID" \
--cache-enabled
Note: Output path defaults to bazinga/artifacts/{session_id}/skills/codebase-analysis/report.json (session-isolated)
# Read from session-isolated artifact directory
cat bazinga/artifacts/$SESSION_ID/skills/codebase-analysis/report.json
Return a concise summary including:
CODEBASE ANALYSIS COMPLETE
## Similar Features Found
- User registration (auth/register.py) - 85% similarity
* Email validation pattern
* Token generation approach
* Database transaction handling
## Reusable Utilities
- EmailService (utils/email.py) - send_email(), validate_email()
- TokenGenerator (utils/tokens.py) - generate_token(), verify_token()
## Architectural Patterns
- Service layer pattern (business logic in services/)
- Repository pattern for data access
## Suggested Implementation Approach
1. Create PasswordResetService in services/
2. Reuse EmailService for sending reset emails
3. Use TokenGenerator for reset tokens
4. Follow transaction pattern from register.py
Full analysis: bazinga/artifacts/{session_id}/skills/codebase-analysis/report.json
If analysis times out or fails:
For detailed documentation: .claude/skills/codebase-analysis/references/usage.md