tdd-llm
AI-Powered TDD Workflows for Claude and Gemini
Deploy structured Test-Driven Development workflows to your AI coding assistants. Guide Claude and Gemini through the RED-GREEN-REFACTOR cycle with consistent, reproducible prompts.
Features
- Deploy
.claude/and.gemini/configuration directories - Automatic conversion from Claude (.md) to Gemini (.toml) format
- Language-specific placeholders (Python, C#, TypeScript)
- Backend support for local files or Jira (via REST API)
- Migrate existing projects from files to Jira
- Global and project-level configuration (project overrides global)
- Configurable coverage thresholds per project
- Cross-platform (Linux, macOS, Windows)
- Update templates from GitHub without reinstalling the package
Installation
pip install tdd-llm
Quick Start
# Initialize project config (creates .tdd-llm.yaml)
tdd-llm init --lang python --backend files
# Deploy TDD templates to current project
tdd-llm deploy
# Deploy to user-level directories
tdd-llm deploy --target user --lang csharp --backend jira
# Preview changes without writing
tdd-llm deploy --lang typescript --dry-run
# List available languages and backends
tdd-llm list
# Show configuration (merged global + project)
tdd-llm config --show
# Update templates from GitHub (without reinstalling)
tdd-llm update
Configuration
tdd-llm supports two configuration levels:
- Global (user-level): Applies to all projects
- Project (local): Overrides global settings for a specific project
Global Configuration
Location:
- Linux/macOS:
~/.config/tdd-llm/config.yaml - Windows:
%APPDATA%\tdd-llm\config.yaml
default_target: "project" # or "user"
default_language: "python"
default_backend: "files" # or "jira"
platforms:
- claude
- gemini
coverage:
line: 80 # Line coverage threshold (%)
branch: 70 # Branch coverage threshold (%)
Project Configuration
Create a .tdd-llm.yaml file in your project root to override global settings:
# Initialize project config with custom settings
tdd-llm init --lang typescript --coverage-line 90
# Or modify existing project config
tdd-llm config --project --set-lang csharp
Project config file: .tdd-llm.yaml
default_language: "typescript"
coverage:
line: 90 # Override only what you need
Configuration Commands
# Show effective configuration (merged global + project)
tdd-llm config --show
# Modify global config
tdd-llm config --set-coverage-line 80
# Modify project config
tdd-llm config --project --set-lang typescript
Coverage thresholds are applied to the generated TDD templates and enforced during the review phase.
Updating Templates
Templates can be updated from GitHub without reinstalling the package:
# Update to latest templates
tdd-llm update
# Force re-download all templates
tdd-llm update --force
# Update and deploy in one command
tdd-llm deploy --update
# Force re-download and overwrite existing files
tdd-llm deploy --update --force
# Deploy using package templates (ignore cached updates)
tdd-llm deploy --no-cache
Updated templates are cached in:
- Linux/macOS:
~/.config/tdd-llm/templates/ - Windows:
%APPDATA%\tdd-llm\templates\
Supported Languages
| Language | Placeholders |
|---|---|
| Python | pytest, coverage, architecture/integration/perf tests |
| C# | dotnet test, xUnit, architecture/integration/perf tests |
| TypeScript | Jest, Vitest, architecture/integration/perf tests |
Backends
Files (default)
Uses local markdown files for epic/story management:
docs/epics/*.md- Epic definitions with tasksdocs/state.json- Progress tracking.tdd-state.local.json- Session state (gitignored)
Jira
Uses Jira REST API for epic/story management. Supports OAuth 2.0 (recommended) or API token authentication.
OAuth 2.0 Authentication (Recommended)
OAuth provides secure, token-based authentication with automatic refresh. Credentials are stored encrypted locally.
# Login with OAuth (interactive setup on first run)
tdd-llm jira login
# Check authentication status
tdd-llm jira status
# Logout (remove stored tokens and credentials)
tdd-llm jira logout
First-time setup:
- Create an OAuth app at https://developer.atlassian.com/console/myapps/
- Configure your app:
- Callback URL:
http://localhost:8089/callback - Permissions: Jira API >
read:jira-work,write:jira-work,read:jira-user
- Callback URL:
- Run
tdd-llm jira loginand enter your Client ID and Client Secret when prompted - Complete authorization in your browser
Credentials and tokens are encrypted and stored in:
- Linux/macOS:
~/.config/tdd-llm/ - Windows:
%APPDATA%\tdd-llm\
API Token Authentication (Alternative)
For simpler setups or environments where OAuth isn't available:
# Set API token
export JIRA_API_TOKEN=your-api-token
Generate an API token at: https://id.atlassian.com/manage-profile/security/api-tokens
Configuration
# In config.yaml
default_backend: "jira"
jira:
base_url: "https://company.atlassian.net"
email: "user@company.com"
project_key: "PROJ"
# Optional: custom field mappings
fields:
acceptance_criteria: "customfield_10001"
# Optional: status mapping (adapt to your Jira language/workflow)
status_map:
"To Do": "not_started"
"In Progress": "in_progress"
"Done": "completed"
# French example:
# status_map:
# "À faire": "not_started"
# "En cours": "in_progress"
# "Terminé": "completed"
Environment variables (override config):
JIRA_API_TOKEN- API token for basic authJIRA_BASE_URL- Jira instance URLJIRA_EMAIL- User emailJIRA_PROJECT_KEY- Default project key
Backend Commands
Commands for AI assistants to interact with Jira:
# Get current workflow state
tdd-llm backend status
# Get epic with all tasks
tdd-llm backend get-epic PROJ-100
# Get task details
tdd-llm backend get-task PROJ-1234
# Get next incomplete task
tdd-llm backend next-task PROJ-100
# Update task status
tdd-llm backend update-status PROJ-1234 Done
# Set TDD phase (adds label tdd:test, tdd:dev, etc.)
tdd-llm backend set-phase PROJ-1234 test
# Set current task
tdd-llm backend set-current PROJ-100 PROJ-1234
# Add comment to task
tdd-llm backend add-comment PROJ-1234 "Task completed"
Migration: Files to Jira
Migrate existing epics and tasks from files backend to Jira:
# Preview what will be created (dry run)
tdd-llm migrate --dry-run
# Run migration
tdd-llm migrate
# Custom output path for mapping file
tdd-llm migrate --output my-mapping.json
The migration:
- Reads epics from
docs/epics/*.md - Creates epics in Jira with format
E1: Epic Name - Creates tasks linked to epics with format
T1: Task Title - Marks completed tasks as "Done" in Jira
- Generates
docs/jira-mapping.json:
{
"E1": "PROJ-100",
"E1/T1": "PROJ-101",
"E1/T2": "PROJ-102",
"E2": "PROJ-200"
}
TDD Workflow Commands
After deployment, use these commands with Claude or Gemini:
Flow Commands
| Command | Phase | Description |
|---|---|---|
/tdd:flow:1-analyze |
Plan | Analyze task, write specs |
/tdd:flow:2-test |
RED | Write failing tests |
/tdd:flow:3-dev |
GREEN+REFACTOR | Implement, then refactor |
/tdd:flow:4-docs |
Document | Update docs, CHANGELOG |
/tdd:flow:5-review |
Review | Code review, create PR |
/tdd:flow:6-done |
Done | Commit, update state |
/tdd:flow:status |
- | Show current progress |
Init Commands
| Command | Description |
|---|---|
/tdd:init:1-project |
Initialize project structure |
/tdd:init:2-architecture |
Define architecture |
/tdd:init:3-standards |
Define code standards |
/tdd:init:4-readme |
Generate README |
Development
# Clone and install in dev mode
git clone https://github.com/mxdumas/tdd-llm-workflow
cd tdd-llm-workflow
python -m venv .venv
source .venv/bin/activate # Linux/macOS
# .venv\Scripts\activate # Windows
pip install -e ".[dev]"
pre-commit install
# Run tests
pytest
# Run linter
ruff check src/
# Format code
ruff format src/
License
MIT
Metadata
Release files for tdd-llm 0.8.1
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