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Pm Ticketing Integration

Community
bobmatnyc
pm-ticketing-integration

Ticket-driven development protocol

Overview

Publisherbobmatnyc
Repositoryclaude-mpm
Skill namepm-ticketing-integration
Stars
152
Forks
34
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bobmatnyc on GitHub. Read the source before you install it.

Installation

Install the Pm Ticketing Integration AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bobmatnyc/claude-mpm.git /tmp/claude-mpm
mkdir -p .claude/skills
cp -r /tmp/claude-mpm/plugin/skills/mpm-ticketing-integration .claude/skills/pm-ticketing-integration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pm Ticketing Integration in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pm Ticketing Integration on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pm Ticketing Integration is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Ticketing Integration Protocol

Ticketing System Default

GitHub is always the default ticketing system. The ticketing_agent uses mcp__github__* tools unless JIRA or Linear are explicitly configured.

Routing order (evaluated by ticketing_agent):

  1. User mentions "jira", a PROJ-123-style ID, or env has JIRA_URL/JIRA_API_TOKEN → JIRA
  2. User mentions "linear", a LIN-/TEAM--style ID, or env has LINEAR_API_KEY → Linear
  3. All other cases → GitHub (mcp__github__*)

When GitHub MCP tools are unavailable, fall back to gh issue CLI commands.

Ask Before Creating

If the user references a ticket/issue but no matching GitHub issue is found:

  • ticketing_agent MUST NOT auto-create a new issue.
  • ticketing_agent MUST ask: "I didn't find an existing issue for [topic]. Should I create one on GitHub, or did you mean a different issue?"
  • Auto-create only when user explicitly says "create a ticket/issue for X."

Detection Rules

PM detects ticket context from:

  • Ticket ID patterns: PROJ-123, #123, MPM-456, JJF-62
  • Ticket URLs: github.com/.../issues/123, linear.app/.../issue/XXX
  • Explicit references: "work on ticket", "implement issue", "fix bug #123"
  • Session start context (first user message with ticket reference)

CRITICAL ENFORCEMENT

PM MUST NEVER use these tools directly - ALWAYS delegate to ticketing agent:

  • ❌ PM using WebFetch on ticket URLs → Delegate to ticketing
  • ❌ PM using mcp__mcp-ticketer__* tools → Delegate to ticketing
  • ❌ PM using ANY tools to access tickets → ONLY delegate to ticketing agent

Delegation Rule: ALL ticket operations must be delegated to ticketing agent.

TICKET-DRIVEN DEVELOPMENT PROTOCOL (TkDD)

When ticket detected (PROJ-123, #123, ticket URLs, "work on ticket"):

PM MUST Execute This Workflow

1. Work Start → Delegate to ticketing:

Task:
  agent: "ticketing"
  task: "Start work on ticket {ticket_id}"
  acceptance_criteria:
    - Transition ticket to 'in_progress'
    - Add comment: "Work started by Claude MPM"
    - Confirm state change

2. Each Phase → Comment with deliverables:

Task:
  agent: "ticketing"
  task: "Update ticket {ticket_id} with progress"
  context: |
    Phase completed: {phase_name}
    Deliverables: {deliverable_summary}
  acceptance_criteria:
    - Add comment with phase completion details
    - Include links to commits/PRs if applicable

3. Work Complete → Transition to done/closed:

Task:
  agent: "ticketing"
  task: "Complete ticket {ticket_id}"
  context: |
    Work summary: {summary}
    QA verification: {qa_evidence}
    Files changed: {file_list}
  acceptance_criteria:
    - Transition to 'done' or 'closed'
    - Add comprehensive completion comment
    - Link PR if created

4. Blockers → Comment blocker details:

Task:
  agent: "ticketing"
  task: "Report blocker on ticket {ticket_id}"
  context: |
    Blocker: {blocker_description}
    Impact: {impact}
    Waiting on: {dependency}
  acceptance_criteria:
    - Update ticket state to 'blocked'
    - Add blocker details in comment
    - Notify relevant stakeholders if applicable

Documentation Routing with Ticket Context

When Ticket Context Provided

When user starts session with ticket reference:

  • PM delegates to ticketing agent to attach work products
  • Research findings → Attached as comments to ticket
  • Specifications → Attached as files or formatted comments
  • Still create local docs as backup in {docs_path}/
  • All agent delegations include ticket context

When NO Ticket Context

  • All documentation goes to {docs_path}/ (default: docs/research/)
  • No ticket attachment operations
  • Named with pattern: {topic}-{date}.md

Ticket Context Propagation

When ticket is detected, PM includes ticket context in all delegations:

Task:
  agent: "{any_agent}"
  task: "{task_description}"
  context: |
    Ticket: {ticket_id}
    Ticket summary: {summary_from_ticketing_agent}
    {other_context}
  acceptance_criteria:
    {criteria}

This ensures all agents know work is ticket-driven and can reference it.

Example TkDD Workflow

User: "Work on ticket PROJ-123"
PM delegates to ticketing: Get ticket details
PM delegates to ticketing: Transition to 'in_progress', comment "Work started"
PM delegates to research: Investigate approach (with ticket context)
PM delegates to ticketing: Comment "Research phase complete: {findings}"
PM delegates to engineer: Implement feature (with ticket context)
PM delegates to ticketing: Comment "Implementation complete: {files}"
PM delegates to QA: Verify implementation
PM delegates to ticketing: Transition to 'done', comment "Work complete: {summary}"

Violation Prevention

Circuit Breaker: PM using ticket tools directly triggers:

  • Violation #1: ⚠️ WARNING - Must delegate immediately
  • Violation #2: 🚨 ESCALATION - Session flagged for review
  • Violation #3: ❌ FAILURE - Session non-compliant

This enforcement ensures PM maintains pure coordination role.

Frequently asked questions

What does the Pm Ticketing Integration AI skill do?

Ticket-driven development protocol

Why use Pm Ticketing Integration on TypingMind?

Because you install it once and use it with any model. Pm Ticketing Integration is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pm Ticketing Integration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bobmatnyc/claude-mpm/tree/main/plugin/skills/mpm-ticketing-integration. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pm Ticketing Integration?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pm Ticketing Integration?

As many as you like. As long as a model supports skills, you can use Pm Ticketing Integration with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pm Ticketing Integration AI skill free?

It is published on GitHub by bobmatnyc. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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