attune-ai 5.0.3

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

Attune AI

Production-ready AI workflows for Claude Code, aligned with Anthropic best practices.

15 multi-agent workflows for code review, security, testing, and release — each backed by specialized Claude subagents with intelligent model routing, budget controls, and structured output. Just type /attune and go.

pip install 'attune-ai[developer]'

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What's New in v5.0.1 — Security Hardening

v5.0.1 hardens memory isolation, hook execution, and MCP rate limiting across the plugin surface. Built on top of v5.0.0's Anthropic best practices alignment.

Feature	What It Does
Memory ownership	Retrieve/delete checks created_by before allowing access
Workspace isolation	INTERNAL classification enforces cross-project boundaries
MCP rate limiter	60 calls/min per tool prevents abuse
Hook import guard	Only attune.* modules can be loaded via hooks
Path validation	State manager and morning workflow now validate all file paths

Previous releases

v5.0.0 — Anthropic Best Practices Release

v5.0.0 aligns all 15 SDK-native workflows with Anthropic's recommended patterns for the Claude Agent SDK. Every workflow now uses proper system prompts, per-agent model routing, budget safety nets, cost/usage tracking, and structured output.

5 features across all 15 workflows:

Feature	What It Does	Why It Matters
System Prompt Separation	Persona in system_prompt, task in user message	How Anthropic designed the API — better agent behavior
Cost & Usage Tracking	Surfaces total_cost_usd, tokens, turns, session ID	Full visibility into what each workflow costs
Budget Safety Nets	max_budget_usd caps per depth (quick/standard/deep)	Prevents runaway costs; override with ATTUNE_MAX_BUDGET_USD
Per-Agent Model Routing	Opus for security/architecture, Haiku for scanning	Right model for each task; override with env vars
Structured Output	JSON schema output with text-parsing fallback	Reliable extraction instead of regex; piloting on 2 workflows

v4.1.0

• Smart test selection — /smart-test runs only tests affected by your changes using git-diff file mapping.
• Auto-fix failing tests — /fix-test diagnoses failures, applies fixes, and re-runs with up to 3 retries.
• Testing hub upgrade — /testing smart and /testing fix routes with natural language routing.

v4.0.0

• Full Agent SDK integration — 15 workflows now have Agent SDK adapters for parallel, contextual code analysis.
• Smart workflow routing — get_workflow() resolves to SDK variant when available, with transparent fallback.

v3.9.x

• 33 MCP tools — All workflows exposed as MCP tools.
• attune doctor — Health check for your install.
• TestAuditWorkflow and DocAuditWorkflow added.
• Exception handling hardened across 16 files.

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Workflows

Every workflow runs as a multi-agent team. Each agent is a specialist — it reads your code with Read, Glob, and Grep tools and reports findings to an orchestrator that synthesizes a unified result.

Workflow	Agents	What It Does	When to Use
code-review	security-reviewer, quality-reviewer, perf-reviewer, architect-reviewer	4-perspective code review covering security, quality, performance, and architecture	Before merging a PR or after significant changes
security-audit	vuln-scanner, secret-detector, auth-reviewer, remediation-planner	Finds vulnerabilities, leaked secrets, auth issues, and generates fix plans	Pre-release security gate, compliance checks
deep-review	security-reviewer, quality-reviewer, test-gap-reviewer	Multi-pass deep analysis with configurable focus areas	Complex modules needing thorough inspection
perf-audit	complexity-analyzer, bottleneck-finder, optimization-advisor	Identifies O(n^2) patterns, bottlenecks, and optimization opportunities	Slow endpoints, large data processing
bug-predict	pattern-scanner, risk-correlator, prevention-advisor	Scans for bug-prone patterns and predicts likely failure points	Proactive quality — find bugs before users do
health-check	test-checker, dep-checker, lint-checker, ci-checker, doc-checker, security-checker	Dynamic agent team (2-6 agents based on mode) for project health	Daily health monitoring, onboarding to a new repo
test-gen	function-identifier, test-designer, test-writer	Identifies untested functions, designs test cases, writes pytest code	Boosting coverage on undertested modules
test-audit	coverage-auditor, gap-analyzer, test-planner	Audits test coverage, finds gaps, and prioritizes what to test next	Coverage-driven test improvement
doc-gen	outline-planner, content-writer, polish-reviewer	Generates documentation from source code with structured outlines	Creating docs for undocumented modules
doc-audit	staleness-checker, accuracy-reviewer, gap-finder	Checks for stale docs, broken links, and documentation drift	Keeping docs accurate after refactors
dependency-check	inventory-assessor, update-advisor	Audits dependencies for outdated packages and security advisories	Pre-release dependency review
refactor-plan	debt-scanner, impact-analyzer, plan-generator	Scans tech debt, analyzes refactoring impact, generates migration plans	Planning large-scale refactors
simplify-code	complexity-scanner, simplification-designer, safety-reviewer	Finds over-engineered code and proposes simplifications with safety review	Reducing complexity after feature sprints
release-prep	health-checker, security-scanner, changelog-generator, release-assessor	4-agent readiness check: health, security, changelog, and go/no-go	Before cutting a release
research-synthesis	source-summarizer, pattern-analyst, synthesis-writer	Multi-source research synthesis with pattern extraction	Technical research, RFC preparation

Model Routing

Each agent is assigned a model based on task complexity:

Model	Agents	Rationale
Opus	security, vuln, architect	Deep reasoning for security and architecture
Sonnet	quality, plan, research	Balanced analysis for synthesis and planning
Haiku	complexity, lint, coverage, dep	Fast scanning for detection tasks
Inherited	All others	Uses the parent orchestrator's model

Override any assignment with environment variables:

# Override security agents to use sonnet (save cost)
export ATTUNE_AGENT_MODEL_SECURITY=sonnet

# Override all agents to use opus (max quality)
export ATTUNE_AGENT_MODEL_DEFAULT=opus

# Let lint agents inherit parent model
export ATTUNE_AGENT_MODEL_LINT=inherit

Budget Controls

Every workflow enforces a budget cap based on depth:

Depth	Budget	Use Case
quick	$0.50	Fast checks, smoke tests
standard	$2.00	Normal analysis (default)
deep	$5.00	Thorough multi-pass review

# Override budget for all workflows
export ATTUNE_MAX_BUDGET_USD=10.0

# Disable budget caps entirely
export ATTUNE_MAX_BUDGET_USD=0

For subscription users, budget caps act as complexity bounds (the SDK limits resource usage even without per-token billing). For API-key users, they're hard dollar caps.

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Quick Start

1. Install

pip install 'attune-ai[developer]'

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
/testing smart     # Run only tests affected by changes
/attune security   # Security audit
/attune commit     # Create commit
/attune pr         # Create pull request

CLI Usage

Run workflows directly from terminal:

attune workflow run code-review --path ./src
attune workflow run security-audit --path ./src
attune workflow run release-prep
attune workflow run test-audit
attune telemetry show

What Does It Look Like?

$ attune workflow run security-audit --path src/

[security-audit] vuln-scanner (opus) ........... done
[security-audit] secret-detector (opus) ........ done
[security-audit] auth-reviewer (opus) .......... done
[security-audit] remediation-planner (opus) .... done

Security Audit Results
Score: 95/100 | Cost: $0.03 | Turns: 12

| Severity | Count | Example                       |
|----------|-------|-------------------------------|
| High     | 1     | Broad except in cli.py:42     |
| Medium   | 3     | Missing type hints            |
| Low      | 2     | TODO comments                 |

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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
Per-agent model routing	Opus/Sonnet/Haiku per role	Manual	None	None
Budget controls	Depth-based caps	None	None	SaaS pricing
Cost in Claude Code	$0 for most tasks	API costs	API costs	SaaS pricing
Multi-agent teams	2-6 agents per workflow	Yes	No	No
MCP integration	17 native tools	No	No	No
Structured output	JSON schema with fallback	Manual	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.

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Key Features

Anthropic Best Practices (v5.0.0)

All 15 workflows follow Anthropic's recommended patterns:

• System Prompt Separation — Persona/behavior preamble in system_prompt, task instructions in user message
• Per-Agent Model Selection — Each subagent gets the right model for its role via AgentDefinition.model
• Budget Safety Nets — max_budget_usd on every ClaudeAgentOptions call, configurable per depth
• Cost/Usage Extraction — AgentRunResult captures total_cost_usd, usage, num_turns, session_id
• Structured Output — JSON schema via output_format with text-parsing fallback (piloting on code-review and security-audit)

Claude-Native Architecture

Built exclusively for Anthropic/Claude:

• Automatic Prompt Caching — Cached tokens cost 10% of standard price, delivering up to 90% savings
• Flexible Context — 200K via subscription, up to 1M via API for large codebases
• Extended Thinking — Access Claude's internal reasoning
• Advanced Tool Use — Optimized for agentic workflows

Multi-Agent Orchestration

• Dynamic Team Composition — 4 execution strategies (parallel, sequential, two-phase, delegation)
• 14 Agent Templates — Pre-built archetypes with custom template registration
• Agent State Persistence — Execution history, checkpoints, and recovery from interruptions
• Progressive Tier Escalation — Start cheap, escalate only when needed

Socratic Workflows

Workflows guide you through discovery instead of requiring upfront configuration:

• Interactive Discovery — Asks targeted questions
• Context Gathering — Collects relevant code and errors
• Dynamic Agent Creation — Assembles the right team

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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, smart test, coverage, test gen
Documentation	/docs	Generate docs, changelog, doc audit
Release	/release	Release prep, security scan, publishing
Workflows	/workflows	Automated analysis (security, bugs, perf)
Plan	/plan	Feature planning, brainstorm, 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 in Claude Code

Most workflows run as skills through the Task tool using your Claude subscription — no additional API costs:

/dev           # Uses your Claude subscription
/testing       # Uses your Claude subscription
/release       # Uses your Claude subscription

When API costs apply: Tasks that exceed your subscription's context window or programmatic/CI usage route through the Anthropic API.

API Mode (CI/CD, Automation)

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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Claude Code Plugin

Install the attune-ai plugin in Claude Code for integrated workflow, memory, and orchestration access. The plugin provides the /attune command, 17 MCP tools, and 17 skills. See the plugin/ directory.

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Installation Options

# Recommended (agents, memory, semantic caching)
pip install 'attune-ai[developer]'

# Minimal (CLI + workflows only)
pip install attune-ai

# All features
pip install 'attune-ai[all]'

# Development (contributing)
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
[developer]	CLI, workflows, agents, memory, semantic caching
Base	CLI, workflows, Anthropic SDK
[all]	Everything including enterprise features

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Environment Setup

In Claude Code: No API key needed — workflows run as skills using your Claude subscription. Just type /attune.

For CLI usage (attune workflow run ...):

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

Optional features:

pip install 'attune-ai[memory]'   # Redis-enhanced memory
attune features                   # Check what's available

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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:

• 17 Tools Available — Workflow, utility, memory, and context tools
• Automatic Discovery — Claude Code finds tools via .claude/mcp.json
• Natural Language Access — Describe your need and Claude invokes the appropriate tool

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Security

• Path traversal protection on all file operations
• JWT authentication with rate limiting
• PII scrubbing in telemetry
• GDPR compliance options
• Automated security scanning

See SECURITY.md for vulnerability reporting.

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Documentation

• Quick Start Guide
• CLI Reference
• Authentication Strategy Guide
• Orchestration API Reference
• 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, the Model Context Protocol, and the Agent SDK patterns that shaped v5.0.0
• Boris Cherny — Creator of Claude Code, whose workflow posts validated Attune's approach to plan-first execution and multi-agent orchestration
• Affaan Mustafa — For battle-tested Claude Code configurations that inspired our hook system

View Full Acknowledgements

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