Capabilities Manage logo

Capabilities Manage

OrganizationPopular
shareAI-lab
capabilities-manage

Kode capability-management playbook: treat features (LSP, statusline, output styles, plugins, notifications) as configurable capabilities and drive changes through the agent CLI (SlashCommand/Task) instead of pushing users into menu-like flows. Use when the user asks to enable/disable/configure a capability, diagnose why it’s off, or wants the agent to self-manage Kode’s own features (meta capability management).

Overview

PublishershareAI-lab
RepositoryKode-CLI
Skill namecapabilities-manage
Stars
5.2K
Forks
771
Bundled files
Instructions only
LicenseApache-2.0
Links
Skill sourceRepository
  • 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 shareAI-lab on GitHub. Read the source before you install it.

Installation

Install the Capabilities Manage 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/shareAI-lab/Kode-CLI.git /tmp/Kode-CLI
mkdir -p .claude/skills
cp -r /tmp/Kode-CLI/packages/builtin-skills/skills/capabilities-manage .claude/skills/capabilities-manage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Capabilities Manage 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 Capabilities Manage 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 Capabilities Manage 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.

Capabilities Manage

Goal

Make users manage Kode features by expressing intent (“enable LSP for TS”, “fix my statusline”) while the agent performs the necessary actions via the agent CLI.

Rules (do not violate)

  • Do not output “installation menu” scripts or long lists of install commands.
  • Prefer SlashCommand to run Kode commands (/statusline, /lsp, /plugin ...) instead of asking the user to do it manually.
  • Keep changes minimal and reversible; verify after each change.

Workflow

  1. Clarify which capability: statusline / lsp / output-style / plugins (or multiple).
  2. Inspect current state with minimal friction:
    • Read settings files (~/.kode/settings.json, .kode/settings.local.json).
    • For interactive status screens, ask the user to open them (single step): /lsp, /output-style.
  3. Apply changes:
    • statusline: create a Task with subagent_type statusline-setup (do not ask the user to memorize the command).
    • lsp: ensure a plugin provides .lsp.json mappings; manage via /plugin, then re-check via /lsp screen.
    • output styles: set outputStyle in settings (or ask the user to choose via /output-style); for edits, edit the output style markdown file and then re-check /output-style.
  4. Verify: re-check status screens and run a minimal real operation.

Capabilities audit (recommended for /capabilities)

Keep this fast and low-friction: default output should be a short checklist and only one question when a choice is required.

  1. Read current settings (best effort):
    • ~/.kode/settings.json (global)
    • .kode/settings.local.json (project, if present)
  2. Produce a compact checklist (OK / Needs attention) for:
    • Statusline: global settings.json contains statusLine.
    • Output style: either settings file contains a non-empty outputStyle string.
    • Plugins & LSP readiness: mention that LSP is plugin-driven; if the user cares, ask them to open /lsp (single step) to confirm resolved servers.
    • Permission friction: if the user reports unexpected denials/repeated prompts, invoke the permissions-debug skill.
  3. Auto-fix what you can safely:
    • Statusline: if requested, create a Task with subagent_type statusline-setup (do not ask the user to memorize the command).
    • Output style: set outputStyle in .kode/settings.local.json (project) or ~/.kode/settings.json (global) and re-read to verify.
  4. Verify each fix immediately by re-reading the changed file(s) and summarizing what changed.

Frequently asked questions

What does the Capabilities Manage AI skill do?

Kode capability-management playbook: treat features (LSP, statusline, output styles, plugins, notifications) as configurable capabilities and drive changes through the agent CLI (SlashCommand/Task) instead of pushing users into menu-like flows. Use when the user asks to enable/disable/configure a capability, diagnose why it’s off, or wants the agent to self-manage Kode’s own features (meta capability management).

Why use Capabilities Manage on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/shareAI-lab/Kode-CLI/tree/main/packages/builtin-skills/skills/capabilities-manage. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Capabilities Manage?

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 Capabilities Manage?

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

Is the Capabilities Manage AI skill free?

Yes. It is published on GitHub by shareAI-lab under the Apache-2.0 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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