dmtools

name	dmtools
description	Comprehensive documentation and assistance for DMTools - an enterprise dark-factory orchestrator with 334+ MCP tools for Jira, Azure DevOps, GitHub, GitLab, Figma, Confluence, Teams, and test automation. Use when working with DMTools, configuring integrations, developing JavaScript agents, generating test cases, building reports (ReportGenerator/ReportVisualizer), creating CLI agent workflows (Teammate/CliAgent), or setting up CI/CD run tracing (ciRunUrl) for Teammate/Expert/TestCasesGenerator/CliAgent jobs.
license	Apache-2.0
compatibility	["Java 17+","macOS, Linux, Windows (WSL)"]
metadata	{"version":"skill-v1.0.31","author":"DMtools Team","repository":"https://github.com/epam/dm.ai","documentation":"https://github.com/epam/dm.ai/tree/main/dmtools-ai-docs"}

DMtools Development Assistant

DMTools is an enterprise dark-factory orchestrator that integrates with multiple platforms and provides 334+ MCP tools for reusable delivery automation.

🔧 FIRST-TIME SETUP (DO THIS PROACTIVELY)

When a user mentions DMtools or asks to use it, IMMEDIATELY perform these checks:

🚀 Quick Installation Bootstrap (Recommended)

Install or refresh DMtools from the latest release first, then continue with the configuration checks below:

# Install or update DMtools from the latest release
curl -fsSL https://github.com/epam/dm.ai/releases/latest/download/install.sh | bash

Then make sure to:

1. ✓ Check whether dmtools is available
2. ✓ Create dmtools.env if missing
3. ✓ Add DMtools files to .gitignore
4. ✓ Verify Java installation
5. ✓ Test DMtools functionality with dmtools list

OR follow manual steps below:

Focused skill packages: install only the integrations you need with DMTOOLS_SKILLS=jira,github and the skill installer described in references/installation/README.md#install-only-the-skills-you-need.

Child agent configs: define a shared base config and extend it with the existing parent inheritance pattern.

Step 1: Check if DMtools is installed

# Check if dmtools command is available
which dmtools || echo "DMtools not installed"

If NOT installed:

# Offer to install DMtools automatically
curl -fsSL https://github.com/epam/dm.ai/releases/latest/download/install.sh | bash

Step 2: Check for dmtools.env configuration

# Check if dmtools.env exists in current directory or home
ls dmtools.env ~/.dmtools.env 2>/dev/null || echo "No dmtools.env found"

If NOT found, help user create it:

1. Ask user which integrations they need (Jira, ADO, Figma, etc.)
2. Ask user which AI provider they want (Gemini free tier recommended)
3. Create dmtools.env with appropriate template (see Configuration Template below)
4. Add dmtools.env to .gitignore (contains secrets!)

Step 3: Verify .gitignore

# Check if dmtools files are in .gitignore
grep -q "dmtools.env\|dmtools-local.env" .gitignore 2>/dev/null || echo "Not in .gitignore"

If NOT in .gitignore, add these lines:

# DMtools configuration (contains secrets)
dmtools.env
dmtools-local.env

Configuration Template

When creating dmtools.env, use this template and fill with user's credentials:

# dmtools.env - NEVER commit this file
# Generated by DMtools skill assistant

# ================================
# INTEGRATIONS (choose what you need)
# ================================

# Jira (if user needs Jira)
JIRA_BASE_PATH=https://your-company.atlassian.net
JIRA_EMAIL=[e-mail]
JIRA_API_TOKEN=your-jira-api-token
JIRA_AUTH_TYPE=Basic

# Azure DevOps (if user needs ADO)
# ADO_BASE_PATH=https://dev.azure.com/your-org
# ADO_PAT_TOKEN=your-ado-pat-token

# ================================
# AI PROVIDER (required - choose one)
# ================================

# Gemini (RECOMMENDED - free tier available)
GEMINI_API_KEY=your-gemini-api-key
# Get free key: https://aistudio.google.com/app/apikey

# OR OpenAI
# OPENAI_API_KEY=your-openai-api-key

# OR AWS Bedrock
# BEDROCK_ACCESS_KEY_ID=your-aws-key
# BEDROCK_SECRET_ACCESS_KEY=your-aws-secret

# ================================
# DEFAULTS
# ================================
DEFAULT_LLM=gemini
DEFAULT_TRACKER=jira

Quick Links for API Tokens:

• Jira: https://id.atlassian.com/manage-profile/security/api-tokens
• Gemini: https://aistudio.google.com/app/apikey (FREE - 15 req/min)
• OpenAI: https://platform.openai.com/api-keys
• ADO: https://dev.azure.com → User Settings → Personal Access Tokens

Step 4: Test Installation

# Verify installation works
dmtools list | head -5

When to Use

Use this skill when:

• Installing or configuring DMtools (do setup steps above first!)
• Setting up integrations (Jira, Azure DevOps, Figma, Confluence, Teams)
• Configuring AI providers (Gemini, OpenAI, Claude, DIAL, Ollama)
• Developing JavaScript agents with MCP tools
• Generating test cases (Jira, Xray, Cucumber)
• Generating analytics reports (ReportGenerator, ReportVisualizer)
• Troubleshooting DMtools issues
• Working with dmtools.env configuration
• Creating AI teammate configurations (Teammate/CliAgent)
• Setting up CI/CD run tracing (ciRunUrl) for ticket traceability

Quick Reference

⚠️ IMPORTANT: If this is first time using DMtools, see FIRST-TIME SETUP section above.

Manual Installation Steps

If automated setup didn't work, follow these manual steps:

1. Install DMtools CLI

curl -fsSL https://github.com/epam/dm.ai/releases/latest/download/install.sh | bash

2. Create dmtools.env

Create dmtools.env in project root (see template in FIRST-TIME SETUP section)

3. Add to .gitignore

echo -e "\n# DMtools configuration\ndmtools.env\ndmtools-local.env" >> .gitignore

4. Get API Tokens

• Jira: https://id.atlassian.com/manage-profile/security/api-tokens
• Gemini (FREE): https://aistudio.google.com/app/apikey
• OpenAI: https://platform.openai.com/api-keys

See Installation Guide for detailed setup.

Common Commands

dmtools list                          # List all 334+ MCP tools
dmtools jira_get_ticket PROJ-123      # Get Jira ticket
dmtools run agents/config.json        # Run configuration
dmtools run agents/config.json --ciRunUrl "https://ci.example.com/runs/42"  # With CI tracing
dmtools run agents/config.json "${ENCODED_CONFIG}" --inputJql "key=PROJ-1"  # With overrides

Core Capabilities

334+ MCP Tools Available

Complete Reference: references/mcp-tools/README.md - Auto-generated from actual DMtools build

Current breakdown (20 integrations):

• Jira (58 tools): Ticket management, search, comments, fields
• Jira Xray (11 tools): Xray test management
• Teams (28 tools): Messages, chats, files, transcripts, meetings
• Teams Auth (3 tools): Teams authentication flows
• Confluence (24 tools): Page management, search, content access, attachments, inline comments
• ADO (38 tools): Azure DevOps work items, queries, comments, attachments, pull requests, code review threads
• GitHub (38 tools): Pull requests, issues, comments, workflows
• GitLab (30 tools): Merge requests, issues, CI/CD pipelines
• Bitbucket (1 tool): Pull request operations
• Figma (22 tools): Design extraction, icons, layers, styles, components
• AI Providers (15 tools): Chat, vision, and file inputs across Gemini, OpenAI, Anthropic, Bedrock, DIAL, Ollama, and Vertex
• Knowledge Base (5 tools): Document search, indexing, RAG
• File (4 tools): File operations, read/write
• Mermaid (3 tools): Diagram generation
• SharePoint (2 tools): Document management
• Bitrise (24 tools): Mobile CI/CD builds and artifacts
• Jenkins (7 tools): CI/CD job and build information
• TestRail (16 tools): Test case and test run management
• Rally (1 tool): Work item lookups
• CLI (1 tool): Command execution

Example tools:

• jira_get_ticket, jira_search_by_jql, jira_xray_create_test
• ado_get_work_item, ado_move_to_state, ado_add_comment
• ado_list_prs, ado_get_pr, ado_add_pr_comment, ado_resolve_pr_thread, ado_merge_pr
• figma_get_layers, figma_get_icons, figma_download_node_image
• teams_send_message, teams_messages_since, teams_download_file
• gemini_ai_chat, openai_ai_chat, openai_ai_chat_with_files, bedrock_ai_chat

JavaScript Agent Pattern

All MCP tools are directly accessible as JavaScript functions in agents:

function action(params) {
    try {
        // Direct MCP tool access
        const ticket = jira_get_ticket(params.ticketKey);
        const analysis = gemini_ai_chat(`Analyze: ${ticket.fields.description}`);

        // Process and return
        return { success: true, result: analysis };
    } catch (error) {
        return { success: false, error: error.toString() };
    }
}

📚 Detailed Documentation

Category	Document	Description
Installation	Installation Guide	Complete setup for all platforms (macOS, Linux, Windows)
	Troubleshooting	Common issues and solutions
Configuration	Configuration Overview	Environment variables and hierarchy
	CLI Output Formats	json / toon / mini — token savings up to 70%
	JSON Configuration Rules	⚠️ CRITICAL: Rules for job configurations
	Jira Setup	API tokens and 58 tools
	Azure DevOps	PAT setup and 38+ tools
	Gemini AI	Free tier configuration (15 req/min)
	Other AI Providers	OpenAI, Claude, DIAL, Ollama
Jobs	Jobs Reference	Complete guide to all 23 jobs
	Teammate	Flexible AI assistant with custom instructions
	CliAgent	Lightweight CLI-agent orchestration without a tracker ticket
	Expert	Domain expert Q&A based on project context
	TestCasesGenerator	Automated test case generation
	InstructionsGenerator	Build reusable implementation instructions from tracker tickets
	JSRunner	Execute a standalone JavaScript agent with DMtools context
	DevProductivityReport	Developer productivity metrics from tracker and SCM data
	BAProductivityReport	BA productivity metrics across created work and status changes
	QAProductivityReport	QA productivity metrics across bugs, tests, and comments
	ReportGenerator	Generate JSON and HTML analytics reports from configurable sources
	ReportVisualizer	Render an existing report JSON as interactive HTML
	KBProcessingJob	Process source material into knowledge-base artifacts
Agents	Agent Best Practices	⚠️ CRITICAL: Patterns and lessons learned
	JavaScript Agents	GraalJS development with 334+ MCP tools
	Teammate Configs	JSON-based AI workflows (CLI safety v1.7.133+)
	CLI Integration	Cursor, Claude, Copilot, Gemini CLI agents
Testing	Test Generation	Xray test case creation