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Envelope Team

CommunityPopular
davepoon
envelope-team

Design and generate .envelope.json AI agent team definitions — the open standard for multi-agent teams with hierarchy, access policies, human-in-the-loop gates, and cron schedules.

Overview

Publisherdavepoon
Repositorybuildwithclaude
Skill nameenvelope-team
Stars
3.6K
Forks
586
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 davepoon on GitHub. Read the source before you install it.

Installation

Install the Envelope Team 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/davepoon/buildwithclaude/tree/main/plugins/all-skills/skills/envelope-team
  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/davepoon/buildwithclaude.git /tmp/buildwithclaude
mkdir -p .claude/skills
cp -r /tmp/buildwithclaude/plugins/all-skills/skills/envelope-team .claude/skills/envelope-team
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Envelope Team 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 Envelope Team 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 Envelope Team 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.

Envelope Team

Design and generate .envelope.json AI agent team definition files — the open standard for building and deploying multi-agent teams on Envelope.

When to Use This Skill

  • User asks to build, design, or generate an Envelope team
  • User describes a workflow that could be automated by a team of AI agents
  • User wants to create a .envelope.json file for deployment
  • User needs help with agent hierarchy, access policies, or gates

What This Skill Does

  1. Takes a natural-language description of the team's purpose
  2. Designs the agent hierarchy (supervisor → managers → workers)
  3. Generates a schema-valid .envelope.json file
  4. Includes access policies, variables, secrets, and gates as appropriate
  5. Explains any schema concepts the user asks about

How to Use

Basic Usage

Build me an Envelope team for customer support triage — one supervisor,
two agents that read Zendesk tickets, and a Slack notifier for escalations.
Create an Envelope team definition for outbound sales — an SDR manager
overseeing two SDRs who work HubSpot leads and a RevOps analyst.

With human-in-the-loop gates

Build an Envelope team that drafts marketing emails and pauses for
human approval before sending.

Example

User: "Build me an Envelope team for content moderation — a supervisor and two reviewer agents that check posts against community guidelines."

Output:

json
{
  "$schema": "https://schema.openenvelope.org/team/v1.json",
  "name": "Content Moderation Team",
  "slug": "content-moderation",
  "version": "1.0.0",
  "description": "A supervisor and two reviewer agents that check posts against community guidelines.",
  "visibility": "team",
  "category": "ops",
  "requiredVariables": ["companyName"],
  "requiredSecrets": ["MODERATION_API_KEY"],
  "metadata": { "generatedBy": "Claude Code · openenvelope.org" },
  "agents": [
    {
      "key": "supervisor",
      "name": "Moderation Supervisor",
      "role": "supervisor",
      "capabilities": ["Route content to reviewer agents", "Aggregate decisions", "Escalate edge cases"],
      "model": "anthropic:claude-sonnet-4-5",
      "systemPrompt": "You supervise the content moderation team at {{companyName}}. Delegate each item to a reviewer and consolidate their verdicts."
    },
    {
      "key": "policy-reviewer",
      "name": "Policy Reviewer",
      "role": "reviewer",
      "capabilities": ["Check content against community guidelines", "Flag policy violations"],
      "model": "anthropic:claude-haiku-3-5",
      "systemPrompt": "You review content for policy violations at {{companyName}}. Return a verdict of approve, flag, or remove with a reason.",
      "reportsToKey": "supervisor",
      "accessPolicy": {
        "accessPolicyVersion": "1",
        "rules": [
          { "host": "api.moderation-service.com", "action": "allow" },
          { "host": "*", "action": "deny" }
        ]
      }
    },
    {
      "key": "spam-reviewer",
      "name": "Spam Reviewer",
      "role": "reviewer",
      "capabilities": ["Detect spam, bot activity, and duplicate content"],
      "model": "anthropic:claude-haiku-3-5",
      "systemPrompt": "You detect spam and bot activity at {{companyName}}. Return a verdict of approve, flag, or remove with a confidence score.",
      "reportsToKey": "supervisor"
    }
  ]
}

Schema Reference

Top-level fields

FieldRequiredDescription
$schemayesAlways https://schema.openenvelope.org/team/v1.json
nameyesHuman-readable team name
slugyesURL-safe, lowercase, hyphens only
versionyesSemver e.g. "1.0.0"
descriptionyesWhat this team does
visibilityyes"public" · "team" · "private"
requiredVariablesnoNon-sensitive config, interpolated via {{varName}}
requiredSecretsnoAPI keys, stored encrypted, injected as ${SECRET_NAME}
schedulenoCron schedule { cron, timezone, task }
agentsyesAgent definitions
gatesnoHuman-in-the-loop checkpoints

Agent fields

FieldRequiredDescription
keyyesUnique identifier within this file
nameyesDisplay name
roleyesFree-form e.g. "supervisor", "analyst", "sdr"
capabilitiesyesWhat this agent can do — used for delegation routing
modelyese.g. anthropic:claude-sonnet-4-5, anthropic:claude-haiku-3-5
systemPromptyesAgent instructions. Use {{varName}} and ${SECRET_NAME}
reportsToKeynokey of manager agent. Omit for the top-level supervisor
accessPolicynoOutbound HTTP allowlist

Hierarchy rule

Exactly one agent should have no reportsToKey — this is the supervisor that receives the initial task. All others reference their manager's key.

Access policy

json
"accessPolicy": {
  "accessPolicyVersion": "1",
  "rules": [
    { "host": "api.example.com", "action": "allow" },
    { "host": "*", "action": "deny" }
  ]
}

Human-in-the-loop gates

json
"gates": [
  {
    "name": "approval-check",
    "type": "approval",
    "trigger": { "afterAgent": "drafter" },
    "onApprove": "continue",
    "onReject": "halt"
  }
]

Tips

  • Use anthropic:claude-sonnet-4-5 for supervisors and managers; anthropic:claude-haiku-3-5 for leaf agents doing repetitive work
  • Put anything org-specific (company name, support email, Slack channel) in requiredVariables
  • End access policy rules with { "host": "*", "action": "deny" } for a strict allowlist
  • Add gates before any agent that sends emails, posts publicly, or makes purchases
  • Validate before deploying: npx @openenvelope/schema validate ./team.envelope.json

Links

Frequently asked questions

What does the Envelope Team AI skill do?

Design and generate .envelope.json AI agent team definitions — the open standard for multi-agent teams with hierarchy, access policies, human-in-the-loop gates, and cron schedules.

Why use Envelope Team on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/davepoon/buildwithclaude/tree/main/plugins/all-skills/skills/envelope-team. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Envelope Team?

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 Envelope Team?

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

Is the Envelope Team AI skill free?

Yes. It is published on GitHub by davepoon 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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