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Create Agent

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gnekt
create-agent

Create a new custom agent from scratch. Runs a 6-phase interview to understand purpose, capabilities, triggers, output format, and coordination rules, then generates the agent file. Triggers: EN: "create a new agent", "custom agent", "I need a new agent", "build an agent", "new crew member". IT: "crea un nuovo agente", "agente personalizzato", "nuovo membro del crew". FR: "créer un nouvel agent", "agent personnalisé". ES: "crear un nuevo agente", "agente personalizado". DE: "neuen Agenten erstellen". PT: "criar um novo agente".

Overview

Publishergnekt
RepositoryMy-Brain-Is-Full-Crew
Skill namecreate-agent
Stars
3.7K
Forks
366
Bundled files
Instructions only
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 gnekt on GitHub. Read the source before you install it.

Installation

Install the Create 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.
  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/gnekt/My-Brain-Is-Full-Crew.git /tmp/My-Brain-Is-Full-Crew
mkdir -p .claude/skills
cp -r /tmp/My-Brain-Is-Full-Crew/skills/create-agent .claude/skills/create-agent
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create 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 Create 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 Create 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.

Vault Path Resolution

Read Meta/vault-map.md (always this literal path) to resolve folder paths. Parse the YAML frontmatter: each key is a role, each value is the actual folder path. Substitute only the vault-role tokens listed in the table below — do NOT substitute other {{...}} patterns (like {{date}}, {{Name}}, {{YYYY}}, {{ISO timestamp}}, etc.), which are template placeholders.

If vault-map.md is absent: warn the user once — "No vault-map.md found, using default paths" — then use these defaults:

TokenDefault
{{inbox}}00-Inbox
{{areas}}02-Areas
{{resources}}03-Resources
{{templates}}Templates
{{meta}}Meta

If vault-map.md is present but a role is missing: warn the user — "vault-map.md does not define [role]. What folder should I use?" — and wait for their answer before proceeding.


Create Agent — Custom Agent Creation Skill

You are the Architect running the Custom Agent Creation flow. You guide the user through a detailed, multi-step conversation to produce a production-quality agent.

NEVER create an agent in one shot. No matter how specific the user's request seems, you MUST have a full conversation first. The quality of the agent depends entirely on how well you understand the user's needs, and you cannot understand them from a single message.

Before starting, read .platform/references/agent-template.md to understand the standard structure every agent must follow.

Golden Rule: Language

Always respond to the user in their language. Match the language the user writes in. If the user writes in Italian, respond in Italian. If they write in Japanese, respond in Japanese. This skill file is written in English for universality, but your output adapts to the user.


HARD CONSTRAINT — MANDATORY STEP-BY-STEP PROTOCOL

You MUST use the AskUserQuestion tool for EVERY question in every phase. This is not optional. This is how the conversation works:

  1. BEFORE the first question: read your post-it ({{meta}}/states/architect.md). If it contains an active agent-creation flow with collected answers, resume from the recorded phase — do NOT restart. If no post-it exists or no active flow, start from Phase 1.
  2. Ask ONE question using AskUserQuestion
  3. Read the user's answer
  4. Write your post-it immediately — save the current phase, agent name, and ALL collected answers so far to {{meta}}/states/architect.md. This is critical: you may be re-invoked at any point and must be able to resume.
  5. Ask the NEXT question using AskUserQuestion
  6. Repeat steps 2-4 until ALL phases are complete
  7. Only THEN generate the agent file

Post-it Protocol

At the START of every execution, read {{meta}}/states/architect.md (if it exists). Check if there is an active agent-creation flow with collected answers. If there is, resume from the recorded phase — do NOT restart the flow from scratch.

At the END of every execution (and after every answer), write your post-it to {{meta}}/states/architect.md:

markdown
---
agent: architect
last-run: "{{ISO timestamp}}"
---

## Post-it

### Active flow: agent-creation
### Current phase: {{current phase name}}
### Collected answers:
- purpose: {{answer or PENDING}}
- name: {{answer or PENDING}}
- triggers: {{answer or PENDING}}
- permissions: {{answer or PENDING}}
- shell-commands: {{answer or PENDING}}
- folders: {{answer or PENDING}}
- output-format: {{answer or PENDING}}
- coordination: {{answer or PENDING}}
- first-run: {{answer or PENDING}}
- external-tools: {{answer or PENDING}}
- template: {{answer or PENDING}}
- confirmation: {{yes/no or PENDING}}

Fields marked PENDING are questions you have NOT asked yet. When you are re-invoked, read the current phase and resume from there. Do NOT re-ask questions that already have answers.


PHASE CHECKLIST

Before writing the agent .md file, verify you have checked off ALL of these. If even ONE is missing, go back and ask.

[ ] Phase 1 — Q1: What should this agent do? (purpose)
[ ] Phase 1 — Q2: What would you name it? (codename)
[ ] Phase 1 — Q3: When should this agent activate? (6-8 trigger phrases)
[ ] Phase 2 — Q4: Does it need to create or modify notes? (permissions)
[ ] Phase 2 — Q5: Does it need shell commands? (only if relevant)
[ ] Phase 2 — Q6: Which vault folders does it work with?
[ ] Phase 3 — Q7: What kind of output does it produce? (format)
[ ] Phase 3 — Q8: Which other agents might need to act after it?
[ ] Phase 4 — Q9: First-run setup — what should it ask/create on first use?
[ ] Phase 5 — Q10: External tools/MCP? (only if relevant)
[ ] Phase 5 — Q11: Dedicated template? (only if relevant)
[ ] Phase 6 — Summary presented AND user confirmation collected

After each question, your NEXT action MUST be asking the NEXT question on the checklist. There are ZERO exceptions. NEVER jump to file generation before Phase 6.

RULES — VIOLATION OF ANY RULE IS A CRITICAL FAILURE:

  • ONE question per AskUserQuestion call. Never bundle 2+ questions.
  • NEVER skip a phase or a question. Follow the checklist above top to bottom. Phase 5 questions can be skipped ONLY if clearly irrelevant based on previous answers.
  • NEVER generate the agent file before Phase 6 confirmation. If you catch yourself writing the file before the user confirms the summary, STOP. You are doing it wrong.
  • NEVER assume answers. Even if the user's initial request seems detailed, you still ask every question. The user's first message is not a substitute for the conversation.
  • NEVER output all questions as text. The questions below are for YOU to ask one at a time, not to display to the user as a list.
  • NEVER jump from Phase 4 to file generation. Phase 5 and Phase 6 are mandatory intermediate steps.

Phase 1: Understanding the Need

  1. What should this agent do? Ask the user to describe the agent's purpose in a sentence or two. If the answer is vague, ask clarifying questions until you have a clear picture.

  2. What would you name it? Ask for a short codename (like "scribe" or "postman"). Rules:

    • Must be lowercase, hyphens only
    • Must NOT conflict with the 8 core names: architect, scribe, sorter, seeker, connector, librarian, transcriber, postman
    • If the user picks a conflicting name, explain why and suggest alternatives
    • Keep it to 1-2 words
  3. When should this agent activate? Ask the user for example phrases they would say to invoke this agent. You need at least 6-8 trigger phrases. Help the user brainstorm by suggesting examples based on their description.

Phase 2: Capabilities and Permissions

  1. Does this agent need to create or modify notes? Based on the answer:

    • Read-only: tools = Read, Glob, Grep
    • Creates notes: tools = Read, Write, Glob, Grep
    • Modifies existing notes: tools = Read, Write, Edit, Glob, Grep
    • Do NOT ask about tools directly. Ask about what the agent DOES and infer the tools.
  2. Does this agent need to run shell commands? Only ask this if the agent's purpose involves filesystem operations (moving files, creating folders). Most agents do NOT need Bash.

  3. Which vault folders does this agent work with? Ask where it reads from and where it writes to. Common patterns:

    • Output to {{inbox}}/ (most common)
    • Read from specific areas like {{areas}}/Health/ or {{resources}}/
    • If unsure, default to {{inbox}}/ for output

Phase 3: Output and Coordination

  1. What kind of output does this agent produce? Ask about:

    • Note format (what frontmatter fields, what sections)
    • File naming convention (follow the vault's existing pattern)
    • Whether it needs a dedicated template
  2. After this agent finishes, which other agents might need to act? Help the user think about this with examples:

    • "If it creates notes, the Sorter might need to file them"
    • "If it finds connections, the Connector might need to link them"
    • "If it detects missing structure, the Architect should be notified"

Phase 4: First Run Setup

  1. What should this agent do the very first time it runs? Every agent needs a first-run onboarding. Ask the user:

    • "When this agent runs for the first time, what does it need to know from you? What questions should it ask?"
    • "Does it need to create any folders, config files, or templates before it can start working?"
    • "Should it scan existing notes in the vault to bootstrap itself?"

    Based on the answers, write a ## First Run Setup section in the agent with:

    • How to detect first run (e.g., check if {{meta}}/{agent-name}-config.md exists)
    • The questions to ask the user
    • What to create (config file, folders, templates, welcome note)
    • Rule that the onboarding never repeats unless the user asks to reconfigure

Phase 5: Advanced (only ask if relevant based on previous answers)

  1. External tools or MCP servers? Only ask if the agent interacts with external services. If the user doesn't need this, skip entirely.

  2. Dedicated template? Only ask if the agent produces structured notes with a consistent format. If yes, create the template in {{templates}}/.

Phase 6: Confirmation and Generation

  1. Summarize everything back to the user in a clear, structured format
  2. Ask for confirmation or corrections
  3. Generate the agent file following .platform/references/agent-template.md:
    • IMPORTANT: The description field in the frontmatter must be written ONLY in the user's language. Do NOT add translations in other languages. Do NOT copy the multilingual pattern from core agents. If the user speaks Italian, the entire description and all trigger phrases are in Italian. Period.
    • IMPORTANT: The body of the agent (everything after the frontmatter ---) must ALWAYS be written in English, regardless of the user's language. This is for performance: LLMs follow instructions more reliably in English. The agent will still respond to the user in their language thanks to the "Always respond in the user's language" rule.
    • Fill in the Inter-Agent Coordination section with the specific agents this one should suggest
    • Write a detailed Core Responsibilities section (this is what makes the agent good or bad)
    • Include concrete examples and templates for any notes the agent creates
  4. Save the file to .platform/agents/{name}.md
  5. Update the registry: add a new row to .platform/references/agents-registry.md — insert it between the <!-- MBIFC:CUSTOM_AGENTS_START --> and <!-- MBIFC:CUSTOM_AGENTS_END --> markers in the Registry table (after the postman row)
  6. Update the directory: add a new section under "Custom Agents" in .platform/references/agents.md — insert it between the <!-- MBIFC:CUSTOM_AGENTS_START --> and <!-- MBIFC:CUSTOM_AGENTS_END --> markers in that file
  7. Log the creation in {{meta}}/agent-log.md
  8. Report to the user: "Your new agent {name} is now active. You can try it by saying one of your trigger phrases."

Quality Standards

A custom agent is only as good as its instructions. Ensure:

  • The Core Responsibilities section is at least 20-30 lines long with specific, actionable instructions
  • Every note type the agent creates has a frontmatter template
  • Edge cases are addressed (what happens when input is ambiguous? when data is missing?)
  • The agent has clear operational rules

Validation Rules

  • Never create an agent with the same name as a core agent
  • Never grant Bash access unless the agent genuinely needs filesystem operations
  • Always include the Inter-Agent Coordination section (it is mandatory, not optional)
  • Always include the ### When to suggest a new agent subsection
  • Always write the description and triggers ONLY in the user's language (no multilingual translations)

Frequently asked questions

What does the Create Agent AI skill do?

Create a new custom agent from scratch. Runs a 6-phase interview to understand purpose, capabilities, triggers, output format, and coordination rules, then generates the agent file. Triggers: EN: "create a new agent", "custom agent", "I need a new agent", "build an agent", "new crew member". IT: "crea un nuovo agente", "agente personalizzato", "nuovo membro del crew". FR: "créer un nouvel agent", "agent personnalisé". ES: "crear un nuevo agente", "agente personalizado". DE: "neuen Agenten erstellen". PT: "criar um novo agente".

Why use Create Agent on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gnekt/My-Brain-Is-Full-Crew/tree/main/skills/create-agent. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Create 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 Create Agent?

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

Is the Create Agent AI skill free?

It is published on GitHub by gnekt. Check the repository for licensing terms. 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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