Agent Skill
2/7/2026

cfn-deployment

Automated skill deployment pipeline for CFN Loop integration

M
masharratt
14GitHub Stars
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npx skills add masharratt/claude-flow-novice

SKILL.md

Namecfn-deployment
DescriptionAutomated skill deployment pipeline for CFN Loop integration

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=localhost for 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-activate for 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|enterprise with 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

User Guides

Technical Reference

Workflows

Maintenance

Legacy

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.json tracks 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

  1. Skills-Based Coordination: All agent communication via explicit Redis dependencies
  2. Multi-Layer Enforcement: Coordination primitives at technical, skill, agent, and system layers
  3. Centralized Orchestration: Keep orchestration in dedicated skills, not distributed across components
  4. Mode-Aware Architecture: Task Mode (direct Task() spawning) vs CLI Mode (coordinator-driven)
  5. Post-Edit Validation: All Edit/Write operations trigger validation hooks
  6. 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

SchemaPurposeQuery TypeUse Case
V1 (embeddings, files)Semantic similarityVector distance"Find code similar to X"
V2 (entities, refs, modules)Structured relationshipsSQL 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

License

See LICENSE file in repository root.

Skills Info
Original Name:cfn-deploymentAuthor:masharratt