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Status

Organization
MadAppGang
status

Show active tracks, progress, current tasks, and blockers

Overview

PublisherMadAppGang
Repositoryclaude-code
Skill namestatus
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 Status 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/conductor/skills/status .claude/skills/status
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Status 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 Status 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 Status 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: conductor updated: 2026-01-20

<read_only>
  This skill ONLY reads files.
  It does NOT modify any conductor/ files.
  For modifications, use other skills.
</read_only>

<comprehensive_scan>
  Parse ALL of:
  - conductor/tracks.md (index)
  - conductor/tracks/*/plan.md (all plans)
  - conductor/tracks/*/metadata.json (state)
</comprehensive_scan>

</critical_constraints>

<core_principles> Always end with clear "Next Action" recommendation. Don't just report status, guide next step.

<principle name="Blocker Visibility" priority="high">
  Prominently display any blocked tasks.
  Blockers need attention.
</principle>

</core_principles>

<phase number="2" name="Analysis">
  <step>Count tasks by status: pending, in_progress, complete, blocked</step>
  <step>Calculate completion percentage per track</step>
  <step>Identify current phase and task</step>
  <step>Find any blocked tasks</step>
</phase>

<phase number="3" name="Presentation">
  <step>Display overview summary</step>
  <step>Show per-track details</step>
  <step>Highlight blockers if any</step>
  <step>Recommend next action</step>
</phase>

Example:

  • Total tasks: 15
  • Completed: 6
  • In Progress: 1
  • Pending: 8
  • Completion: 40%
  </progress_calculation>

  <status_priority>
    Display order by priority:
    1. BLOCKED tasks (need attention)
    2. IN_PROGRESS tasks (current work)
    3. Active tracks summary
    4. Completed tracks (brief)
  </status_priority>
</knowledge>

<examples>
  <example name="Single Active Track">
    <user_request>What's my status?</user_request>
    <correct_output>
      ## Conductor Status

      ### Active Tracks: 1

      **feature_auth_20260105** - User Authentication
      - Progress: [========------] 53% (8/15 tasks)
      - Phase: 2/4 - Core Authentication
      - Current: 2.3 Create login endpoint
      - Blockers: None

      ### Next Action
      Continue task 2.3 (Create login endpoint) in feature_auth track.
      Run: `conductor:implement`
    </correct_output>
  </example>

  <example name="Multiple Tracks with Blocker">
    <user_request>Show me the status</user_request>
    <correct_output>
      ## Conductor Status

      ### BLOCKERS (1)
      - **feature_auth_20260105** Task 2.4: "Waiting for API key from team lead"

      ### Active Tracks: 2

      **feature_auth_20260105** - User Authentication
      - Progress: [=======-------] 47% (7/15 tasks)
      - Phase: 2/4 - Core Authentication
      - Status: BLOCKED at 2.4

      **bugfix_login_20260104** - Login redirect fix
      - Progress: [==============] 100% (5/5 tasks)
      - Status: Ready for review

      ### Next Action
      Resolve blocker in feature_auth (Task 2.4) or complete review of bugfix_login.
    </correct_output>
  </example>
</examples>

<formatting>
  <status_template>
## Conductor Status

### Overview
- Active Tracks: {N}
- Total Progress: {X}% ({completed}/{total} tasks)
- Blockers: {N}

{#if blockers}
### BLOCKERS
{#each blocker}
- **{track_id}** Task {task_id}: "{blocker_description}"
{/each}
{/if}

### Active Tracks
{#each active_track}
**{track_id}** - {title}
- Progress: [{progress_bar}] {percent}% ({completed}/{total})
- Phase: {current_phase}/{total_phases} - {phase_name}
- Current: {current_task_id} {current_task_title}
{/each}

{#if completed_tracks}
### Completed Tracks
{#each completed_track}
- {track_id} - Completed {date}
{/each}
{/if}

### Next Action
{recommendation}
  </status_template>
</formatting>

Frequently asked questions

What does the Status AI skill do?

Show active tracks, progress, current tasks, and blockers

Why use Status on TypingMind?

Because you install it once and use it with any model. Status 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 Status in TypingMind?

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

Which AI models can use Status?

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 Status?

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

Is the Status 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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