Kiln Batch Dispatch

Organization

instruktlabs

kiln-batch-dispatch

Run requested Kiln asset batches or compare coding-agent harnesses and models in isolated workspaces. Use for repeatable trials, source-reference workflow checks, and distinguishing provider, tool, and asset-quality failures.

Overview

Publisher	instruktlabs
Repository	`kiln`
Skill name	`kiln-batch-dispatch`
Stars	292
Forks	24
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by instruktlabs on GitHub. Read the source before you install it.

Installation

Install the Kiln Batch Dispatch AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/instruktlabs/kiln/tree/main/skills/kiln-batch-dispatch
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.

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/instruktlabs/kiln.git /tmp/kiln
mkdir -p .claude/skills
cp -r /tmp/kiln/skills/kiln-batch-dispatch .claude/skills/kiln-batch-dispatch

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kiln Batch Dispatch 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 Kiln Batch Dispatch 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 Kiln Batch Dispatch 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.

Run comparable asset trials

Use the user's requested harness and exact model identifier. Verify what the provider actually ran; do not silently substitute a default or older model.

Create a fresh workspace for each candidate using clean-room evaluation. A named Kiln project is optional; use matching project configuration only when the trial calls for it. Keep the engine checkout and example collection outside the agent's task context.
Give each candidate the same brief, installed skills, image budget, time limit, and starting asset where applicable. Record inherited tools, instructions, memory, and permissions.
Verify tool access and actual image delivery with one small run before dispatching a batch. Model vision support and harness image forwarding are separate checks.
Exercise the whole revision loop: render source once, use the returned programRef, read a source window, edit an exact anchor, inspect a part, and export the same revision. Check that later calls do not resend the program and that unrelated source survives the edit.
Retain the brief, exact model, harness version, requested and independently confirmed thinking effort, transcript, source, images, package/skill hashes, and outcome. Leave unexposed effort unknown. Keep the original author and each later refiner distinct. Rebuild the saved source independently of the agent's success claim.
Review shapes under consistent cameras and lighting. Separate provider outages or quota limits, harness failures, tool/schema failures, engine failures, and visual quality. An interrupted run is not a completed asset.

After a shared package or skill change, rerun the affected workflow with the final candidate. A successful earlier revision does not validate later instructions. Record manual repairs separately from model output.

Adding a reviewed asset to a gallery is a separate task. Do it only when that addition is requested, retaining model provenance and later edits.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/clean-room-evaluation.md4 KB

Frequently asked questions

What does the Kiln Batch Dispatch AI skill do?

Why use Kiln Batch Dispatch on TypingMind?

Because you install it once and use it with any model. Kiln Batch Dispatch 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 Kiln Batch Dispatch in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/instruktlabs/kiln/tree/main/skills/kiln-batch-dispatch. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Kiln Batch Dispatch?

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 Kiln Batch Dispatch?

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

Is the Kiln Batch Dispatch AI skill free?

Yes. It is published on GitHub by instruktlabs 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Run comparable asset trials

Bundled files

Frequently asked questions

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