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Infra Setup

OrganizationPopular
evo-hq
infra-setup

Non-user-invocable provider/setup reference for evo backend switching, prerequisite checks, and auth/install guidance.

Overview

Publisherevo-hq
Repositoryevo
Skill nameinfra-setup
Stars
1.5K
Forks
110
Bundled files
1
LicenseApache-2.0
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.

  • 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 evo-hq on GitHub. Read the source before you install it.

Installation

Install the Infra Setup 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/evo-hq/evo.git /tmp/evo
mkdir -p .claude/skills
cp -r /tmp/evo/plugins/evo/npm/skills/infra-setup .claude/skills/infra-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Infra Setup 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 Infra Setup 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 Infra Setup 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.

Infra Setup

Use this when the user wants to change where experiments run: local worktrees, pool slots, or a remote provider such as Modal, E2B, Daytona, AWS, Azure, SSH, manual, or a custom dotted-path provider.

Goals

  • Be explicit about the target backend/provider.
  • Check prerequisites before mutating evo config.
  • Never install provider SDKs silently.
  • Give one actionable auth command per provider.
  • Keep provider credentials separate from benchmark runtime env.

Flow

  1. Identify the target:
    • worktree or pool means local backends.
    • modal, e2b, ssh:..., or another remote spec means backend=remote.
  2. If the target is remote, parse the provider choice the same way evo CLI does:
  • modal
  • e2b
  • daytona
  • aws
  • azure
  • manual
  • ssh:user@host[:port]
    • another built-in provider name
    • dotted import path for a custom provider
  1. Check whether evo is on PATH and whether it is the expected evo-hq-cli package (evo --version). If the provider SDK is missing, evo's provider loader prints the provider-specific extra or SDK package to install; use that message rather than guessing.
  2. For SDK-backed providers, verify the SDK import only when you can run the check in the same environment that owns the evo executable. If missing, ask the user before installing it.
    • If evo was installed with uv tool or pip/venv, prefer the matching extra on evo-hq-cli:
      • uv-tool: uv tool install --reinstall 'evo-hq-cli[<provider-extra>]'
      • venv / pip: python -m pip install 'evo-hq-cli[<provider-extra>]'
    • If evo was installed with pipx, inject the provider SDK into the same evo-hq-cli environment:
      • pipx: pipx inject evo-hq-cli <provider-sdk>
  3. Check auth and show exactly one provider-specific auth command or setup step. Use references/provider-matrix.md.
  4. Once prerequisites are satisfied, run the explicit config command:
bash
evo config backend remote --provider <provider> --provider-config ...

Or for local backends:

bash
evo config backend worktree
evo config backend pool --workspaces /abs/slot-a,/abs/slot-b
  1. Be explicit that incomplete provider setup usually surfaces on evo new --remote <provider> ..., because that is where remote allocation and bootstrap actually happen.
  2. If the benchmark itself needs application keys, configure runtime env separately with evo env load <path> --all or evo env load <path> --allow KEY1,KEY2. Provider auth provisions the sandbox; runtime env is what benchmark/gate processes see.

Pre-assumptions

Before trying to switch a workspace to a remote provider, confirm the basics:

  • the target backend is clear from the user's request; only ask if the intent is genuinely ambiguous between worktree, pool, and remote
  • the machine running evo has the right provider SDK or transport installed
  • the user has auth for that provider available now, not "somewhere else"
  • the provider-specific minimum config exists
    • modal: auth + optional config
    • e2b: API key + optional config
    • daytona: API key and API URL/target if needed
    • aws: creds, region, image, SSH key pair/private key, and usually network config
    • azure: subscription, resource group, region, SSH key/private key, and VM/image choices
    • ssh: reachable host, working SSH user, and key/port if needed
    • manual: reachable remote endpoint URL and bearer token
  • for SSH-backed VM providers, the guest assumptions are plausible before allocation:
    • the image enables SSH
    • the SSH user matches the image
    • the image architecture matches the selected instance type
    • the host can run evo's remote workspace runtime

Provider notes

See references/provider-matrix.md for the compact provider summary, common config, and provider-specific setup/auth command.

Bundled files

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

Frequently asked questions

What does the Infra Setup AI skill do?

Non-user-invocable provider/setup reference for evo backend switching, prerequisite checks, and auth/install guidance.

Why use Infra Setup on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/evo-hq/evo/tree/main/plugins/evo/npm/skills/infra-setup. 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 Infra Setup?

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 Infra Setup?

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

Is the Infra Setup AI skill free?

Yes. It is published on GitHub by evo-hq 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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