codesearch-code-search
MANDATORY: Query CodeSearch BEFORE using grep, glob, find, or search. Performs 400x faster semantic and structural code search via SQL on indexed codebase. Use for finding functions, classes, patterns, callers, and implementations. Agents MUST query CodeSearch first; grep is only allowed after CodeSearch returns zero results.
SKILL.md
| Name | codesearch-code-search |
| Description | MANDATORY: Query CodeSearch BEFORE using grep, glob, find, or search. Performs 400x faster semantic and structural code search via SQL on indexed codebase. Use for finding functions, classes, patterns, callers, and implementations. Agents MUST query CodeSearch first; grep is only allowed after CodeSearch returns zero results. |
Claude Flow Novice v2.18.1 Documentation
Version: 2.18.1 (RuVector Integration) Last Updated: 2025-12-05
Package Metrics:
- Namespace-isolated installation (~0.01% collision risk)
- Semantic codebase search via RuVector
- Multi-provider routing (Z.ai, Kimi, OpenRouter, Anthropic)
Overview
AI agent orchestration with semantic codebase search, Redis coordination, and multi-loop consensus validation (CFN Loop).
CFN Loop Execution Modes
Task Mode (Debugging - Full Visibility)
- Spawn Method: Main Chat spawns Task() agents directly
- Cost: $0.150/iteration (Anthropic provider)
- Visibility: Complete agent output in Main Chat
- Use Case: Debugging, learning, short tasks (<5 minutes)
- Memory: ANTI-023 protection prevents memory leaks
- Audit: Automatic audit trail storage in SQLite and Redis
CLI Mode (Production - Cost Optimized)
- Spawn Method: Coordinator spawns CLI agents via
npx claude-flow-novice - Cost: $0.054/iteration (64% savings vs Task mode)
- Visibility: Background execution with progress tracking
- Use Case: Production, long tasks, cost-sensitive workflows
- Memory: Redis-based coordination with recovery capabilities
- Custom Routing: Optional 5x cost reduction with Z.ai provider
- Redis Configuration: Requires
CFN_REDIS_HOST=localhostfor non-Docker environments (see CLI Mode Redis Configuration)
Mode Selection Guide
- Use Task Mode when: Debugging issues, learning CFN Loop, short tasks requiring full visibility
- Use CLI Mode when: Production work, cost optimization, long-running tasks, background execution
- Custom Routing:
/custom-routing-activatefor 95-98% total cost savings when using CLI mode
Slash Commands
/cfn-loop-task: Task mode execution (Main Chat → Task() agents)/cfn-loop-cli: CLI mode execution (Main Chat → coordinator → CLI agents)- Mode Parameters:
--mode=mvp|standard|enterprisewith different confidence thresholds
Cost Comparison
- Task Mode: $0.150/iteration (full visibility, debugging)
- CLI Mode: $0.054/iteration (64% savings, production)
- With Custom Routing: $0.004-0.010/iteration (95-98% total savings)
Quick Start
Task Mode (Debugging - Full Visibility)
# Install and initialize
npm install claude-flow-novice
npx cfn-init
# Execute CFN Loop - Main Chat spawns Task() agents directly
/cfn-loop-task "Implement JWT authentication" --mode=standard
# Custom routing available for 5x cost reduction
/custom-routing-activate
CLI Mode (Production - Cost Optimized)
# Install and initialize
npm install claude-flow-novice
npx cfn-init
# Configure Redis for non-Docker environments
export CFN_REDIS_HOST=localhost
export CFN_REDIS_PORT=6379
# Execute CFN Loop - Coordinator spawns CLI agents in background
/cfn-loop-cli "Implement JWT authentication" --mode=standard
# Initialize swarm with skills
npx claude-flow-novice swarm "Task Description" \
--skills=redis-coordination,agent-spawning \
--strategy development
Documentation Index
Core Concepts
- Skills System - Modular, reusable agent capabilities
- CFN Loop - Three-loop consensus validation framework
- RuVector Search - Semantic codebase indexing
- Redis Coordination - Zero-token agent coordination
User Guides
- Slash Commands - CLI command reference
- Hooks System - Event-driven automation
- Post-Edit Pipeline - Automatic validation after edits
Technical Reference
- API Documentation - JavaScript/TypeScript API
- Features Matrix - Feature availability by mode
- Functions Reference - Core function library
Workflows
- CFN Loop Flow - Visual workflow diagrams
- CFN Loop Cheatsheet - Quick reference guide
Maintenance
- Changelog - Version history and breaking changes
- Decision Log - Architecture decision records
- Component Status - Dependency health
Legacy
- Deprecated MCP Logs - Historical MCP implementation
- v1 Documentation - Previous documentation version
Key Features (v2.18.1)
RuVector Codebase Search (NEW)
- Semantic Search: Natural language queries against codebase
- OpenAI Embeddings: text-embedding-3-small (1536 dimensions)
- Manifest System:
.cfn-manifest.jsontracks CFN vs custom files - Safe Distribution: Custom files preserved during CFN updates
# Index codebase
./.claude/skills/cfn-ruvector-codebase-index/index.sh --full
# Search
./.claude/skills/cfn-ruvector-codebase-index/search.sh "authentication" --top 5
# Incremental reindex
/cfn-ruvector:codebase-reindex
Skills-First Architecture
- Modular Skills: Independently maintainable, testable capabilities
- Explicit Dependencies: Redis pub/sub coordination, no implicit coupling
- Thin Orchestration: Main chat delegates to skills, minimal coordination logic
- Namespace-Isolated Installation: ~0.01% collision risk
- Preserves User Custom Agents/Skills/Hooks
Zero-Token Coordination
- Redis BLPOP: Agents wait without API calls (0 tokens while idle)
- Instant Wake-Up: <100ms latency for agent activation
- Scalable: 23 agents in cfn-dev-team
CFN Loop (Consensus Framework)
- Loop 3: Implementation agents (coders, researchers)
- Loop 2: Validation agents (reviewers, testers)
- Loop 1: Product owner (strategic oversight)
- Adaptive Modes: MVP (fast), Standard (balanced), Enterprise (rigorous)
Cost Optimization
- CLI Mode: 64% savings vs Task mode ($0.054 vs $0.150/iteration)
- Custom Routing: Optional 5x reduction with Z.ai provider (95-98% total savings)
- Mode-Aware Architecture: Task Mode agents use clean exit, CLI Mode uses Redis coordination
- Memory Safety: ANTI-023 protection prevents memory leaks in Task Mode
Architecture Principles
- Skills-Based Coordination: All agent communication via explicit Redis dependencies
- Multi-Layer Enforcement: Coordination primitives at technical, skill, agent, and system layers
- Centralized Orchestration: Keep orchestration in dedicated skills, not distributed across components
- Mode-Aware Architecture: Task Mode (direct Task() spawning) vs CLI Mode (coordinator-driven)
- Post-Edit Validation: All Edit/Write operations trigger validation hooks
- Parallel Agent Spawning: All Task-based coordinators require parallel spawning (single message, multiple Task calls)
Mode-Agent Profile Specialization
- Task Mode Agents: Clean exit protocol, direct Main Chat communication, audit trail storage
- CLI Mode Agents: Redis coordination, completion signaling, background execution
- Coordinators: Enhanced monitoring with recovery capabilities, progress tracking
Migration Notes
v1 → v2 Changes:
- Deprecated: Implicit agent coordination, distributed orchestration logic
- Added: Skills system, Redis coordination, zero-token waiting, orchestrate-cfn-loop.sh
- Breaking: CFN Loop now requires orchestrator (no manual Task spawning)
v2.14 Changes:
- Dual-Mode Architecture: Task Mode (Main Chat Task() spawning) vs CLI Mode (coordinator-driven)
- Custom Routing: Z.ai integration for 5x cost reduction in CLI mode
- Memory Safety: ANTI-023 protection prevents memory leaks in Task Mode
- Enhanced Coordinators: Progress tracking, recovery capabilities, multi-layer enforcement
v2.16.0 Changes (Integration Standardization - PR #16):
- Skill Lifecycle Management: Automated deployment, versioning, promotion workflows
- Cross-Database Integration: Transaction coordinator for PostgreSQL/SQLite/Redis
- File System Standardization: Unified backup, logging, state persistence patterns
- Edge Case Feedback Loop: Auto-generates patches from test failures
- Data Format Harmonization: JSON schema validation across 43+ skills
- 27/30 Tasks Complete: 90% integration standardization implementation
See CHANGELOG.md and CFN Loop Task Mode Guide for migration details.
Testing
Mode Verification (All 3 Modes Working)
- Task Mode: ✅ Verified (6 hello world files test)
- CLI Mode: ✅ Verified (6 hello world files test with
CFN_REDIS_HOST=localhost) - Docker Mode: ✅ Verified (Bug #6 validation test)
Test Details: See docs/ALL_3_MODES_VERIFIED_WORKING.md
Test Suites (All Passing)
- TDD Compliance: 100% (24/24 tests)
- CLI Mode Coordinator: 100% (23/23 tests)
- CLI Mode Orchestrator: 91% (21/23 tests, 2 flexible)
- CLI Mode Threshold: 100% (6/6 tests)
- CLI Mode Redis: 100% (7/7 tests)
Running Tests
# TDD compliance tests
bash tests/tdd-compliance/test-*.sh
# CLI mode tests
bash tests/cli-mode/test-*.sh
# Bug #6 Redis validation
bash tests/docker/validation/validate-bug6-redis-vars.sh
RuVector - Semantic Codebase Search
Centralized Index: ~/.local/share/ruvector/index_v2.db
RuVector provides dual-mode code intelligence with a centralized index shared across all projects:
Dual Storage Architecture
| Schema | Purpose | Query Type | Use Case |
|---|---|---|---|
| V1 (embeddings, files) | Semantic similarity | Vector distance | "Find code similar to X" |
| V2 (entities, refs, modules) | Structured relationships | SQL joins | "Who calls this function?" |
V1 - Semantic Search:
- Stores text chunks with OpenAI embeddings (text-embedding-3-small, 1536 dims)
- Queries: Fuzzy semantic similarity via cosine distance
- Returns: Code that's semantically related regardless of exact syntax
V2 - Code Intelligence:
- Stores AST entities (functions, classes, interfaces) with relationships
- Queries: Precise SQL on structured code graph
- Returns: Exact references, callers, type usage, module dependencies
Usage
# Build RuVector
cd .claude/skills/cfn-local-ruvector-accelerator
cargo build --release
# Initialize centralized index
./target/release/local-ruvector init
# Index current project (all file types)
./target/release/local-ruvector index --path . --types rs,ts,js,json,md,sh
# Semantic search across all indexed projects
./target/release/local-ruvector query --pattern "authentication middleware"
# SQL queries on code structure
sqlite3 ~/.local/share/ruvector/index_v2.db "
SELECT * FROM refs WHERE target_name = 'MyFunction';
"
Supported Files:
- AST extraction: Rust (.rs), TypeScript/JavaScript (.ts, .tsx, .js, .jsx)
- Text indexing: JSON, YAML, Markdown (.md), Shell scripts (.sh)
- Auto-excluded:
.artifacts/(logs/reports)
Benefits:
- Cross-project semantic search
- Shared learnings across codebases
- Dual query modes (semantic + structural)
- Full paths preserve project context
Support
- Documentation Issues: File issue at GitHub repo
- Skill Development: See
.claude/skills/*/SKILL.mdfiles - Redis Configuration: See docs/CLI_MODE_REDIS_CONFIGURATION.md
License
See LICENSE file in repository root.