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Create Custom Agent

OrganizationPopular
dotnet
create-custom-agent

Creates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.

Overview

Publisherdotnet
Repositoryskills
Skill namecreate-custom-agent
Stars
5.5K
Forks
420
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 dotnet on GitHub. Read the source before you install it.

Installation

Install the Create Custom 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/dotnet/skills/tree/main/.agents/skills/create-custom-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/dotnet/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/.agents/skills/create-custom-agent .claude/skills/create-custom-agent
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Custom 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 Custom 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 Custom 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.

Create Custom Agent

This skill helps you create VS Code custom agent files that define specialized AI personas for development tasks. Custom agents configure which tools are available, provide specialized instructions, and can chain together via handoffs.

When to Use

  • Creating a new custom agent from scratch
  • Scaffolding an .agent.md file with proper frontmatter
  • Setting up agent-to-agent handoffs for multi-step workflows
  • Configuring tool restrictions for specialized roles (planner, reviewer, etc.)
  • Creating workspace-shared or user-profile agents

When Not to Use

  • Creating instruction files (use .instructions.md instead)
  • Creating reusable prompts (use .prompt.md instead)
  • Modifying existing agents (edit the file directly)

Inputs

InputRequiredDescription
Agent nameYesDescriptive name for the agent (e.g., planner, code-reviewer)
DescriptionYesBrief description shown as placeholder text in chat
Purpose/PersonaYesWhat role the agent plays and how it should behave
ToolsRecommendedList of tools or tool sets the agent can use
HandoffsOptionalNext-step agents to transition to after completing work

Workflow

Step 1: Create the agent file

Create a file with .agent.md extension in the agents/ directory:

agents/<agent-name>.agent.md

Step 2: Add YAML frontmatter

Add the header with required and optional fields:

yaml
---
name: <agent-name>
description: <brief description for chat placeholder>
tools:
  - <tool-name>
  - <tool-set-name>
---
Available frontmatter fields:
FieldRequiredDescription
nameNoDisplay name (defaults to filename)
descriptionYesPlaceholder text shown in chat input
argument-hintNoHint text guiding user interaction
toolsNoList of available tools/tool sets
agentsNoList of allowed subagents (* for all, [] for none)
modelNoAI model name or prioritized array of models
handoffsNoList of next-step agent transitions
user-invokableNoShow in agents dropdown (default: true)
disable-model-invocationNoPrevent subagent invocation (default: false)
targetNoTarget environment: vscode or github-copilot
mcp-serversNoMCP server configs for GitHub Copilot target

Step 3: Configure tools

Specify which tools the agent can use:

yaml
tools:
  - search              # Built-in tool
  - fetch               # Built-in tool
  - codebase            # Tool set
  - myServer/*          # All tools from MCP server

Common tool patterns:

  • Read-only agents: ['search', 'fetch', 'codebase']
  • Full editing agents: ['*'] or specific editing tools
  • Specialized agents: Cherry-pick specific tools

Step 4: Add handoffs (optional)

Configure transitions to other agents:

yaml
handoffs:
  - label: Start Implementation
    agent: implementation
    prompt: Implement the plan outlined above.
    send: false
    model: GPT-5.2 (copilot)

Handoff fields:

  • label: Button text displayed to user
  • agent: Target agent identifier
  • prompt: Pre-filled prompt for target agent
  • send: Auto-submit prompt (default: false)
  • model: Optional model override for handoff

Step 5: Write agent instructions (body)

Add the agent's behavior instructions in Markdown:

markdown
You are a security-focused code reviewer. Your job is to:

1. Analyze code for security vulnerabilities
2. Check for common security anti-patterns
3. Suggest secure alternatives

## Guidelines

- Focus on OWASP Top 10 vulnerabilities
- Flag hardcoded secrets immediately
- Review authentication and authorization logic

## Reference other files

See [security guidelines](../security.md) for standards.

Tips for instructions:

  • Use Markdown links to reference other files
  • Reference tools with #tool:<tool-name> syntax
  • Be specific about agent behavior and constraints

Step 6: Validate the agent

Verify the agent loads correctly:

  1. Open Command Palette (Ctrl+Shift+P)
  2. Run "Chat: New Custom Agent" or check agents dropdown
  3. Use "Diagnostics" view (right-click in Chat view) to check for errors

Template

markdown
---
name: <agent-name>
description: <brief description for chat placeholder>
argument-hint: <optional hint for user input>
tools:
  - <tool-1>
  - <tool-2>
handoffs:
  - label: <button-text>
    agent: <target-agent>
    prompt: <pre-filled-prompt>
    send: false
---

# <Agent Title>

<One paragraph describing the agent's persona and purpose.>

## Role

<Describe the agent's specialized role and expertise.>

## Guidelines

- <Guideline 1>
- <Guideline 2>
- <Guideline 3>

## Workflow

1. <Step 1>
2. <Step 2>
3. <Step 3>

## Constraints

- <Constraint 1>
- <Constraint 2>

Example Agents

Planning Agent

markdown
---
name: planner
description: Generate an implementation plan
tools:
  - search
  - fetch
  - codebase
handoffs:
  - label: Start Implementation
    agent: implementation
    prompt: Implement the plan above.
---

# Planning Agent

You are a solution architect. Generate detailed implementation plans.

## Guidelines

- Analyze requirements thoroughly before planning
- Break work into discrete, testable steps
- Identify dependencies and risks
- Do NOT make code changes

Code Review Agent

markdown
---
name: code-reviewer
description: Review code for quality and security issues
tools:
  - search
  - codebase
---

# Code Review Agent

You are a senior engineer performing code review.

## Focus Areas

- Security vulnerabilities
- Performance concerns
- Code maintainability
- Test coverage gaps

## Output Format

Provide findings as:
1. **Critical**: Must fix before merge
2. **Warning**: Should address
3. **Suggestion**: Nice to have

Validation Checklist

  • File has .agent.md extension
  • File is in agents/ directory
  • YAML frontmatter is valid (proper indentation, no syntax errors)
  • Description is non-empty and descriptive
  • Tools list contains only available tools
  • Handoff agent names match existing agents
  • Instructions are clear and actionable
  • Agent appears in agents dropdown

Common Pitfalls

PitfallSolution
Agent not appearing in dropdownCheck file is in agents/ directory with .agent.md extension
YAML syntax errorsValidate frontmatter indentation and quoting
Tools not workingVerify tool names exist; unavailable tools are ignored
Handoffs not showingTarget agent must exist; check agent identifier
Instructions too vagueBe specific about role, constraints, and workflow
Agent invoked as subagent unexpectedlySet disable-model-invocation: true
Want agent only as subagentSet user-invokable: false

References

Frequently asked questions

What does the Create Custom Agent AI skill do?

Creates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.

Why use Create Custom Agent on TypingMind?

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

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

Which AI models can use Create Custom 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 Custom Agent?

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

Is the Create Custom Agent AI skill free?

Yes. It is published on GitHub by dotnet 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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