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Tag Command Mapping

Organization
MadAppGang
tag-command-mapping

How tag-to-command routing works in autopilot. Defines default mappings, precedence rules, and customization patterns.

Overview

PublisherMadAppGang
Repositoryclaude-code
Skill nametag-command-mapping
Stars
281
Forks
26
Bundled files
Instructions only
LicenseMIT
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 MadAppGang on GitHub. Read the source before you install it.

Installation

Install the Tag Command Mapping 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/MadAppGang/claude-code.git /tmp/claude-code
mkdir -p .claude/skills
cp -r /tmp/claude-code/plugins/autopilot/skills/tag-command-mapping .claude/skills/tag-command-mapping
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tag Command Mapping 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 Tag Command Mapping 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 Tag Command Mapping 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.

plugin: autopilot updated: 2026-01-20

Tag-to-Command Mapping

Version: 0.1.0 Purpose: Route Linear tasks to appropriate Claude Code commands based on tags Status: Phase 1

When to Use

Use this skill when you need to:

  • Understand how Linear tags map to Claude Code commands
  • Customize tag-to-command mappings for a project
  • Handle tasks with multiple tags (precedence rules)
  • Classify tasks based on title/description text
  • Resolve the correct agent/command for a task

Overview

Tag-to-command mapping is the core routing mechanism in autopilot. When a task arrives from Linear, its labels determine which Claude Code command/agent handles execution.

Default Mappings

Linear TagCommandAgentSkills
@frontend/dev:featuredeveloperreact-typescript
@backend/dev:implementdevelopergolang, api-design
@debug/dev:debugdebuggerdebugging-strategies
@test/dev:test-architecttest-architecttesting-strategies
@review/commit-commands:commit-push-prrevieweruniversal-patterns
@refactor/dev:implementdeveloperuniversal-patterns
@research/dev:deep-researchresearchern/a
@ui/dev:uiuiui-design-review

Precedence Rules

When multiple tags are present, apply precedence order:

typescript
const PRECEDENCE = [
  '@debug',    // Bug fixing takes priority
  '@test',     // Tests before implementation
  '@ui',       // UI before generic frontend
  '@frontend', // Frontend before generic
  '@backend',  // Backend before generic
  '@review',   // Review after implementation
  '@refactor', // Refactoring is lower priority
  '@research'  // Research is lowest
];

function selectTag(labels: string[]): string {
  const agentTags = labels.filter(l => l.startsWith('@'));

  if (agentTags.length === 0) return 'default';
  if (agentTags.length === 1) return agentTags[0];

  // Multiple tags - apply precedence
  for (const tag of PRECEDENCE) {
    if (agentTags.includes(tag)) return tag;
  }

  return 'default';
}

Custom Mappings

Users can define custom mappings in .claude/autopilot.local.md:

yaml
---
tag_mappings:
  "@database":
    command: "/dev:implement"
    agent: "developer"
    skills: ["database-patterns"]
    systemPrompt: "You are a database specialist."

  "@performance":
    command: "/dev:implement"
    agent: "developer"
    skills: ["universal-patterns"]
    systemPrompt: "You are a performance optimization expert."
---

Task Classification

Beyond explicit tags, classify tasks from text:

typescript
function classifyTask(title: string, description: string): string {
  const text = `${title} ${description}`.toLowerCase();

  // Keyword patterns
  if (/\b(fix|bug|error|crash|broken)\b/.test(text)) return 'BUG_FIX';
  if (/\b(add|implement|create|new|feature)\b/.test(text)) return 'FEATURE';
  if (/\b(refactor|clean|optimize|improve)\b/.test(text)) return 'REFACTOR';
  if (/\b(ui|design|component|style|visual)\b/.test(text)) return 'UI_CHANGE';
  if (/\b(test|coverage|e2e|spec)\b/.test(text)) return 'TEST';
  if (/\b(doc|documentation|readme)\b/.test(text)) return 'DOCUMENTATION';

  return 'UNKNOWN';
}

Mapping Resolution

Complete resolution algorithm:

typescript
function resolveMapping(labels: string[], title: string, desc: string) {
  // 1. Check explicit tags
  const tag = selectTag(labels);

  if (tag !== 'default') {
    return getMappingForTag(tag);
  }

  // 2. Classify from text
  const taskType = classifyTask(title, desc);

  // 3. Map task type to default tag
  const typeToTag = {
    'BUG_FIX': '@debug',
    'FEATURE': '@frontend',
    'UI_CHANGE': '@ui',
    'TEST': '@test',
    'REFACTOR': '@refactor',
    'DOCUMENTATION': '@research',
  };

  return getMappingForTag(typeToTag[taskType] || '@frontend');
}

Examples

Example 1: Single Tag Resolution

typescript
// Task with @frontend label
const labels = ['@frontend', 'feature'];
const tag = selectTag(labels);  // '@frontend'
const mapping = getMappingForTag(tag);
// Result: { command: '/dev:feature', agent: 'developer', skills: ['react-typescript'] }

Example 2: Multiple Tag Precedence

typescript
// Task with both @frontend and @debug
const labels = ['@frontend', '@debug'];
const tag = selectTag(labels);  // '@debug' (higher precedence)
const mapping = getMappingForTag(tag);
// Result: { command: '/dev:debug', agent: 'debugger', skills: ['debugging-strategies'] }

Example 3: Text Classification Fallback

typescript
// Task without tags
const labels = [];
const title = "Fix login button not working";
const mapping = resolveMapping(labels, title, "");
// Classifies as BUG_FIX -> @debug
// Result: { command: '/dev:debug', agent: 'debugger', skills: ['debugging-strategies'] }

Best Practices

  • Use explicit tags over relying on classification
  • Create custom mappings for project-specific workflows
  • Debug > Test > UI > Frontend precedence makes sense
  • Review mapping effectiveness periodically
  • Keep tag names short and descriptive (start with @)

Frequently asked questions

What does the Tag Command Mapping AI skill do?

How tag-to-command routing works in autopilot. Defines default mappings, precedence rules, and customization patterns.

Why use Tag Command Mapping on TypingMind?

Because you install it once and use it with any model. Tag Command Mapping 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 Tag Command Mapping in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MadAppGang/claude-code/tree/main/plugins/autopilot/skills/tag-command-mapping. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Tag Command Mapping?

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 Tag Command Mapping?

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

Is the Tag Command Mapping AI skill free?

Yes. It is published on GitHub by MadAppGang under the MIT license. 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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