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Dust Call Agent

OrganizationPopular
dust-tt
dust-call-agent

Call a Dust agent for Dust company context or to access tools, data, and actions unavailable through the current agent's native capabilities. Never use a Dust agent as a proxy for Slack, Notion, Google Drive, calendars, or any other service when native access is available; use the native tool instead because it is faster and more efficient.

Overview

Publisherdust-tt
Repositorydust
Skill namedust-call-agent
Stars
1.5K
Forks
370
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 dust-tt on GitHub. Read the source before you install it.

Installation

Install the Dust Call Agent 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.
    https://github.com/dust-tt/dust/tree/main/.claude/skills/dust-call-agent
  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/dust-tt/dust.git /tmp/dust
mkdir -p .claude/skills
cp -r /tmp/dust/.claude/skills/dust-call-agent .claude/skills/dust-call-agent
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dust Call Agent 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 Dust Call Agent 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 Dust Call Agent 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.

Access Dust agents that have context on all the company, e.g. recent projects, engineering, sales, marketing, etc., via the Dust CLI non-interactively, e.g.: $ dust chat -a dust -m "create an issue for this: ..." $ dust chat -a deep-dive -m "Research all info we have on kubernetes probe failures in recent weeks."

For GitHub issue creation, use the dust agent rather than issueBot or gh; dust has specific guidance for writing issues.

A conversation with an agent can be continued after the first message using the argument -c CONVERSATION_STRING_ID. The conversation id will be returned in the JSON result from the initial call. $ dust chat -a dust -c 'TdWyn4aDt1' -m "also add a subsequent issue about this: ..."

Use --projectName or --projectId to create the conversation inside a specific project (space). These cannot be used with -c (only for new conversations): $ dust chat -a prea --projectName "Engineering" -m "summarize recent incidents" $ dust chat -a prea --projectId "abc123" -m "summarize recent incidents"

Use -d / --details to get detailed message information in the output (raw event stream, tool actions, and full agent message payload): $ dust chat -a prea -d -m "what's the status of project X?"

If the CLI errors because login is needed, ask the user to perform it manually.

An agent may take long to answer. Avoid repeating an agent call if possible, especially if it timed out without a clear error, because:

  • the agent call may not be idempotent, e.g. when creating an issue, if the conversation on Dust has been started, repeating will create two issues;
  • multiple conversations are created in the user's Dust workspace, which bloats their conversation history.

If the CLI timed out but returned a conversationId and messageId, you can safely fetch the result without side effects: $ dust chat -c <conversationId> --messageId <messageId>

Otherwise, wait for a clear answer. If you decide to time out with no conversation ID, make no assumption on success or failure; report back to the user.

Frequently asked questions

What does the Dust Call Agent AI skill do?

Call a Dust agent for Dust company context or to access tools, data, and actions unavailable through the current agent's native capabilities. Never use a Dust agent as a proxy for Slack, Notion, Google Drive, calendars, or any other service when native access is available; use the native tool instead because it is faster and more efficient.

Why use Dust Call Agent on TypingMind?

Because you install it once and use it with any model. Dust Call Agent 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 Dust Call Agent in TypingMind?

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

Which AI models can use Dust Call Agent?

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 Dust Call Agent?

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

Is the Dust Call Agent AI skill free?

Yes. It is published on GitHub by dust-tt 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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