AI-assisted software lifecycle tools with multi-agent orchestration, state management, and work tracking integration
Project description
Trustable AI
An AI-assisted software lifecycle framework featuring multi-agent orchestration, state management, work tracking integration, and zero-trust tool integration. Build real software projects reliably with Claude Code.
Overview
Trustable AI provides a sophisticated system for managing AI-assisted software development workflows. It coordinates specialized AI agents to handle complex development tasks while maintaining context, state, and integration with your work tracking platform.
Key Capabilities:
- Multi-agent orchestration with 7 context-driven agents
- Re-entrant workflows with state persistence
- Re-entrant initialization (update settings without re-entering everything)
- Hierarchical context management with auto-generated CLAUDE.md files
- Integration with Azure DevOps, file-based tracking (Jira/GitHub planned)
- Skills system for reusable capabilities
- Learnings capture for institutional knowledge
Installation
pip install trustable-ai
With Azure DevOps support:
pip install trustable-ai[azure]
For development:
pip install -e ".[dev]"
Quick Start
Initialize in Your Project
cd your-project/
trustable-ai init
The interactive init wizard will:
- Prompt for project information (name, type, tech stack)
- Configure your work tracking platform
- Create
.claude/directory structure - Let you select which agents to enable (by number, 'all', or keep defaults)
- Optionally render agents and workflows to
.claude/ - Optionally generate hierarchical CLAUDE.md context files
Re-entrant: Running trustable-ai init again loads existing values as defaults, so you can update individual settings without re-entering everything.
Non-Interactive Mode
# Initialize with all defaults
trustable-ai init --no-interactive
Agent and Workflow Management
# List available agents
trustable-ai agent list
# Enable agents (individually or all at once)
trustable-ai agent enable senior-engineer
trustable-ai agent enable all
# Render all enabled agents to .claude/agents/
trustable-ai agent render-all
# Also render agent slash commands to .claude/commands/
trustable-ai agent render-all --with-commands
# Or render commands separately
trustable-ai agent render-commands
# Render workflows to .claude/commands/
trustable-ai workflow render-all
# Validate your setup
trustable-ai validate
Use with Claude Code
After rendering, use the slash commands in Claude Code:
/sprint-planning- Plan your sprint with multi-agent orchestration/daily-standup- Generate daily standup reports/backlog-grooming- Review and prioritize backlog items/senior-engineer- Invoke the senior engineer agent with fresh context/software-developer- Invoke the developer agent with fresh context
Features
Multi-Agent System (7 Context-Driven Agents)
Trustable AI uses context-driven agents that adapt their behavior based on the task context, rather than having a separate agent for each specialized role.
| Agent | Core Responsibilities | Context-Driven Behaviors | Model |
|---|---|---|---|
| business-analyst | Requirements analysis, business value scoring, prioritization | Sprint planning, roadmap analysis, feature assessment | sonnet |
| architect | Technical architecture, system design, technology decisions | Component design, risk assessment, ADR creation | opus |
| senior-engineer | Task breakdown, estimation, code review, epic decomposition | Feature decomposition, sprint planning, backlog grooming | sonnet |
| engineer | Feature implementation, DevOps, performance optimization | → DevOps tasks (CI/CD, infrastructure) → Performance tasks (optimization, profiling) |
sonnet |
| tester | Test planning, test execution, adversarial testing | → Adversarial testing (find bugs) → Spec-driven testing (independent verification) → Falsifiability proving (test validation) → Test arbitration (fault attribution) |
sonnet |
| security-specialist | Security review, vulnerability analysis, threat modeling | Code review, architecture review, deployment security | sonnet |
| scrum-master | Sprint coordination, workflow management, retrospectives | Sprint planning, daily standups, closure decisions | sonnet |
Context-Driven Behavior: Agents adapt based on task keywords. For example:
/engineeranalyzing a deployment task → Acts as DevOps engineer (CI/CD focus)/engineeranalyzing a performance issue → Acts as Performance engineer (profiling focus)/testerin sprint planning → Test planning and strategy/testerwith failing tests → Fault attribution and bug creation
Deprecated Agents: The framework maintains backward compatibility for old agent names (project-architect, software-developer, qa-engineer, etc.) by aliasing them to the new consolidated agents.
Workflow Templates
- sprint-planning - Complete sprint planning automation
- sprint-execution - Sprint progress monitoring
- sprint-completion - Sprint closure and retrospectives
- sprint-retrospective - Retrospective analysis
- backlog-grooming - Backlog refinement
- daily-standup - Daily standup reports
- dependency-management - Dependency analysis and tracking
- workflow-resume - Resume incomplete workflows from within Claude Code
- context-generation - Guided CLAUDE.md hierarchy creation
Hierarchical Context Generation
Trustable AI can automatically generate hierarchical CLAUDE.md files for your codebase:
# Preview what would be generated
trustable-ai context generate --dry-run
# Generate CLAUDE.md files (skips existing)
trustable-ai context generate
# Force overwrite existing files
trustable-ai context generate --force
# Limit depth of directory traversal
trustable-ai context generate --depth 2
# Build searchable context index
trustable-ai context index
# Look up relevant context for a task
trustable-ai context lookup "implement user authentication"
Context generation creates:
- Root
CLAUDE.mdwith project overview and structure - Directory-level
CLAUDE.mdforsrc/,tests/,docs/, etc. - Module-level
CLAUDE.mdfor significant subdirectories .claude/context-index.yamlfor fast keyword-based lookups
State Management
Workflows maintain state for re-entrancy:
- Resume from last checkpoint on failure
- Prevent duplicate work on retry
- Track created work items
- Persist errors with context
Resume from within Claude Code:
/workflow-resume
This will:
- Scan for incomplete workflows
- Show status, progress, and age of each
- Let you select which to resume
- Automatically continue from the last checkpoint
Or use the CLI:
# View workflow states
trustable-ai state list
# Resume interrupted workflow (outputs instructions)
trustable-ai state resume sprint-planning-sprint-10
Skills System
Reusable capabilities for common tasks:
- Azure DevOps operations (enhanced CLI, bulk operations)
- Context loading and optimization
- Learnings capture
- Cross-repo coordination
Learnings Capture
Capture institutional knowledge from development sessions:
trustable-ai learnings capture
trustable-ai learnings list
trustable-ai learnings archive
Configuration
The trustable-ai init command creates .claude/config.yaml in your project. You can also create it manually:
project:
name: "your-project"
type: "web-application"
tech_stack:
languages: ["Python", "TypeScript"]
frameworks: ["FastAPI", "React"]
platforms: ["Azure", "Docker"]
databases: ["PostgreSQL"]
work_tracking:
platform: "azure-devops" # or "file-based"
organization: "https://dev.azure.com/yourorg"
project: "Your Project"
credentials_source: "cli" # uses 'az login'
work_item_types:
epic: "Epic"
feature: "Feature"
story: "User Story"
task: "Task"
bug: "Bug"
quality_standards:
test_coverage_min: 80
critical_vulnerabilities_max: 0
high_vulnerabilities_max: 0
code_complexity_max: 10
agent_config:
models:
architect: "claude-opus-4"
engineer: "claude-sonnet-4.5"
analyst: "claude-sonnet-4.5"
enabled_agents:
- senior-engineer
- project-architect
- software-developer
# Implementation tier affects quality expectations
# tier-0: Exploration/prototype
# tier-1: Intentful development (CI, tests)
# tier-2: Production ready
implementation_tier: "tier-0"
CLI Reference
# Initialization (re-entrant)
trustable-ai init # Initialize or update Trustable AI configuration
trustable-ai init --no-interactive # Use defaults without prompts
trustable-ai validate # Validate configuration
trustable-ai doctor # Health check and diagnostics
trustable-ai status # Overall status
# Agent Management
trustable-ai agent list # List available agents
trustable-ai agent enable <name> # Enable an agent
trustable-ai agent enable all # Enable all agents
trustable-ai agent disable <name> # Disable an agent
trustable-ai agent render <name> # Render specific agent
trustable-ai agent render all # Render all enabled agents
trustable-ai agent render-all # Render all enabled agents to .claude/agents/
trustable-ai agent render-all --with-commands # Also render agent slash commands
trustable-ai agent render-commands # Render agent slash commands to .claude/commands/
# Workflow Management
trustable-ai workflow list # List available workflows
trustable-ai workflow render <name> # Render specific workflow
trustable-ai workflow render-all # Render all workflows to .claude/commands/
# State Management
trustable-ai state list # List workflow states
trustable-ai state show <id> # Show specific state
trustable-ai state resume <id> # Resume interrupted workflow
trustable-ai state cleanup # Clean up old state files
# Context Management
trustable-ai context generate # Generate hierarchical CLAUDE.md files
trustable-ai context generate --dry-run # Preview without creating files
trustable-ai context generate --force # Overwrite existing files
trustable-ai context generate -d 2 # Limit depth
trustable-ai context index # Build context index
trustable-ai context show # Show loaded contexts
trustable-ai context lookup <task> # Find relevant context for a task
# Configuration
trustable-ai configure azure-devops # Configure Azure DevOps
trustable-ai configure file-based # Configure file-based tracking
trustable-ai configure quality # Configure quality standards
Work Tracking Platforms
Azure DevOps
# Configure Azure DevOps
trustable-ai configure azure-devops
# Ensure you've logged in
az login
File-Based (Zero Dependency)
For projects without external work tracking:
trustable-ai configure file-based
Tasks are stored in .claude/tasks/ as YAML files.
Architecture
.claude/
config.yaml # Main configuration
agents/ # Rendered agent definitions (.md files)
commands/ # Workflow and agent slash commands
workflow-state/ # Execution state (re-entrancy)
profiling/ # Performance profiles
learnings/ # Session learnings
context-index.yaml # Searchable context index
tasks/ # File-based task tracking
project-root/
CLAUDE.md # Root context file
src/
CLAUDE.md # Source code context
tests/
CLAUDE.md # Test suite context
Hierarchical Context
Trustable AI uses hierarchical CLAUDE.md files to provide maximal context with minimal tokens:
- Root CLAUDE.md for project overview
- Module-level CLAUDE.md for specific areas
- Auto-generated context index for smart loading
- Use
trustable-ai context generateto create the hierarchy automatically
Development
# Clone repository
git clone https://github.com/keychain-io/trustable-ai
cd trustable-ai
# Install for development
pip install -e ".[dev]"
# Run tests
pytest
# Run specific test categories
pytest -m unit # Unit tests only
pytest -m integration # Integration tests
# Code quality
black . && ruff . && mypy .
Requirements
- Python 3.9+
- Claude Code account
- Azure CLI (for Azure DevOps integration)
License
MIT License - see LICENSE file for details.
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