attune-ai 2.8.0

AI-powered developer workflows for Claude with cost optimization, multi-agent orchestration, and workflow automation.

Attune AI

AI-powered developer workflows with cost optimization and intelligent routing.

The easiest way to run code review, debugging, testing, and release workflows from your terminal or Claude Code. Just type /attune and let Socratic discovery guide you. Smart tier routing saves 34-86% on LLM costs.

pip install attune-ai[developer]

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What's New in v2.7.0

• Workflow Consolidation - Overlapping workflows consolidated into canonical groups with backward-compatible migration aliases
• Feature Availability API - Runtime checking of optional dependencies (Redis, etc.) with graceful degradation
• Modular Architecture - WorkflowContext composition, clean memory/telemetry splitting, streamlined workflow registry
• Deep Analysis Stages - Code review now LLM-validates performance and quality findings to filter false positives and add fix suggestions
• 433+ New Tests - Feature availability, workflow consolidation, and 6 workflow test suites
• attune features CLI - See what's available and what needs installing at a glance
• Easiest version to learn - Simplified command hubs, Socratic discovery, and natural language routing make Attune the most approachable release yet

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Why Attune?

	Attune AI	Agent Frameworks (LangGraph, AutoGen)	Coding CLIs (Aider, Codex)	Review Bots (CodeRabbit)
Ready-to-use workflows	15 built-in	Build from scratch	None	PR review only
Cost optimization	3-tier auto-routing	None	None	None
Cost in Claude Code	$0 (skill-based)	API costs	API costs	SaaS pricing
Multi-agent teams	4 strategies	Yes	No	No
MCP integration	18 native tools	No	No	No

Attune is a workflow operating system for Claude — it sits above coding agents and below general orchestration frameworks, providing production-ready developer workflows with intelligent cost routing. Full comparison

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Key Features

Claude-Native Architecture

Attune AI is built exclusively for Anthropic/Claude, unlocking features impossible with multi-provider abstraction:

• Prompt Caching - 90% cost reduction on repeated prompts
• Flexible Context - 200K via subscription, up to 1M via API for large codebases
• Extended Thinking - Access Claude's internal reasoning process
• Advanced Tool Use - Optimized for agentic workflows

Multi-Agent Orchestration

Full support for custom agents, dynamic teams, and Anthropic Agent SDK:

• Dynamic Team Composition - Build agent teams from templates, specs, or MetaOrchestrator plans with 4 execution strategies (parallel, sequential, two-phase, delegation)
• 13 Agent Templates - Pre-built archetypes (security auditor, code reviewer, test coverage, etc.) with custom template registration
• Agent State Persistence - AgentStateStore records execution history, saves checkpoints, and enables recovery from interruptions
• Workflow Composition - Compose entire workflows into DynamicTeam instances for orchestrated parallel/sequential execution
• Progressive Tier Escalation - Agents start cheap and escalate only when needed (CHEAP -> CAPABLE -> PREMIUM)
• Agent Coordination Dashboard - Real-time monitoring with 6 coordination patterns
• Inter-Agent Communication - Heartbeats, signals, events, and approval gates
• Quality Gates - Per-agent and cross-team quality thresholds with required/optional gate enforcement

Modular Architecture

Clean, maintainable codebase built for extensibility:

• Small, Focused Files - No file exceeds 1,000 lines; logic extracted into mixins and utilities
• Cross-Platform CI - Tested on Ubuntu, macOS, and Windows with Python 3.10-3.13
• 8,800+ Unit Tests - Security, unit, integration, and behavioral test coverage at 82% coverage

Intelligent Cost Optimization

• $0 in Claude Code - Workflows run as skills through Claude's Task tool
• Smart Tier Routing - Automatically selects the right model for each task
• Authentication Strategy - Routes between subscription and API based on codebase size

Socratic Workflows

Workflows guide you through discovery instead of requiring upfront configuration:

• Interactive Discovery - Asks targeted questions to understand your needs
• Context Gathering - Collects relevant code, errors, and constraints
• Dynamic Agent Creation - Assembles the right team based on your answers

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Claude Code Plugin

Install the attune-ai plugin in Claude Code for integrated workflow, memory, and orchestration access. The plugin provides the /attune command, 18 MCP tools, and 3 skills (memory-and-context, workflow-orchestration, refactor-plan). See the plugin/ directory.

For healthcare developers, the healthcare-cds plugin adds 9 clinical MCP tools and the /care command. See attune-healthcare-fork/attune-healthcare-plugin/.

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Quick Start

1. Install

pip install attune-ai

2. Setup Slash Commands

attune setup

This installs /attune to ~/.claude/commands/ for Claude Code.

3. Use in Claude Code

Just type:

/attune

Socratic discovery guides you to the right workflow.

Or use shortcuts:

/attune debug      # Debug an issue
/attune test       # Run tests
/attune security   # Security audit
/attune commit     # Create commit
/attune pr         # Create pull request

CLI Usage

Run workflows directly from terminal:

attune workflow run release-prep           # 4-agent release readiness check
attune workflow run security-audit --path ./src
attune workflow run test-gen --path ./src
attune telemetry show

Optional Features

Redis-enhanced memory (for multi-session coordination, real-time events):

pip install 'attune-ai[memory]'

All features (includes memory, dashboard, agents):

pip install 'attune-ai[all]'

Check what's available:

attune features

See Feature Availability Guide for detailed information about core vs optional features.

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Command Hubs

Workflows are organized into hubs for easy discovery:

Hub	Command	Description
Developer	/dev	Debug, commit, PR, code review, quality
Testing	/testing	Run tests, coverage analysis, benchmarks
Documentation	/docs	Generate and manage documentation
Release	/release	Release prep, security scan, publishing
Workflows	/workflows	Automated analysis (security, bugs, perf)
Plan	/plan	Planning, TDD, code review, refactoring
Agent	/agent	Create and manage custom agents

Natural Language Routing:

/workflows "find security vulnerabilities"  # → security-audit
/workflows "check code performance"         # → perf-audit
/plan "review my code"                      # → code-review

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Cost Optimization

Skills = $0 (Claude Code)

When using Claude Code, workflows run as skills through the Task tool - no API costs:

/dev           # $0 - uses your Claude subscription
/testing       # $0
/release       # $0

API Mode (CI/CD, Automation)

For programmatic use, smart tier routing saves 34-86%:

Tier	Model	Use Case	Cost
CHEAP	Haiku	Formatting, simple tasks	~$0.005
CAPABLE	Sonnet	Bug fixes, code review	~$0.08
PREMIUM	Opus	Architecture, complex design	~$0.45

# Track API usage and savings
attune telemetry savings --days 30

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MCP Server Integration

Attune AI includes a Model Context Protocol (MCP) server that exposes all workflows as native Claude Code tools:

• 10 Tools Available - security_audit, bug_predict, code_review, test_generation, performance_audit, release_prep, and more
• Automatic Discovery - Claude Code finds tools via .claude/mcp.json
• Natural Language Access - Describe your need and Claude invokes the appropriate tool

# Verify MCP integration
echo '{"method":"tools/list","params":{}}' | PYTHONPATH=./src python -m attune.mcp.server

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Agent Coordination Dashboard

Real-time monitoring with 6 coordination patterns:

• Agent heartbeats and status tracking
• Inter-agent coordination signals
• Event streaming across agent workflows
• Approval gates for human-in-the-loop
• Quality feedback and performance metrics
• Demo mode with test data generation

# Launch dashboard (requires Redis 7.x or 8.x)
python examples/dashboard_demo.py
# Open http://localhost:8000

Redis 8.4 Support: Full compatibility with RediSearch, RedisJSON, RedisTimeSeries, RedisBloom, and VectorSet modules.

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Authentication Strategy

Intelligent routing between Claude subscription and Anthropic API:

# Interactive setup
python -m attune.models.auth_cli setup

# View current configuration
python -m attune.models.auth_cli status

# Get recommendation for a file
python -m attune.models.auth_cli recommend src/module.py

Automatic routing:

• Small/medium modules (<2000 LOC) → Claude subscription (free)
• Large modules (>2000 LOC) → Anthropic API (pay for what you need)

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Installation Options

# Base install (CLI + workflows)
pip install attune-ai

# Full developer experience (multi-LLM, agents, memory)
pip install attune-ai[developer]

# With semantic caching (70% cost reduction)
pip install attune-ai[cache]

# Enterprise (auth, rate limiting, telemetry)
pip install attune-ai[enterprise]

# Development
git clone https://github.com/Smart-AI-Memory/attune-ai.git
cd attune-ai && pip install -e .[dev]

What's in each option:

Option	What You Get
Base	CLI, workflows, Anthropic SDK
[developer]	+ OpenAI, Google AI, LangChain agents, memory
[cache]	+ Semantic similarity caching
[enterprise]	+ JWT auth, rate limiting, OpenTelemetry

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Environment Setup

In Claude Code: No setup needed - uses your Claude subscription.

For CLI/API usage:

export ANTHROPIC_API_KEY="sk-ant-..."  # Required for CLI workflows
export REDIS_URL="redis://localhost:6379"  # Optional: for memory features

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Security

• Path traversal protection on all file operations (_validate_file_path() on 22 write operations)
• JWT authentication with rate limiting
• PII scrubbing in telemetry
• HIPAA/GDPR compliance options
• Automated security scanning (517 findings remediated to 0 across codebase)

# Run security audit
attune workflow run security-audit --path ./src

See SECURITY.md for vulnerability reporting.

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Documentation

• Quick Start Guide
• CLI Reference
• Authentication Strategy Guide
• Orchestration API Reference
• Workflow Coordination Guide
• Architecture Overview
• Full Documentation

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Contributing

See CONTRIBUTING.md for guidelines.

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License

Apache License 2.0 - Free and open source. Use it, modify it, build commercial products with it. Details →

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Acknowledgements

Special thanks to:

• Anthropic - For Claude AI and the Model Context Protocol
• LangChain - Agent framework powering our orchestration
• FastAPI - Modern Python web framework

View Full Acknowledgements →

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