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Creating An Agent

Organization
ed3dai
creating-an-agent

Use when creating specialized subagents for Claude Code plugins or the Task tool - covers description writing for auto-delegation, tool selection, prompt structure, and testing agents

Overview

Publishered3dai
Repositoryed3d-plugins
Skill namecreating-an-agent
Stars
249
Forks
33
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 ed3dai on GitHub. Read the source before you install it.

Installation

Install the Creating An 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/ed3dai/ed3d-plugins.git /tmp/ed3d-plugins
mkdir -p .claude/skills
cp -r /tmp/ed3d-plugins/plugins/ed3d-extending-claude/skills/creating-an-agent .claude/skills/creating-an-agent
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Creating An 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 Creating An 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 Creating An 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.

Creating an Agent

REQUIRED BACKGROUND: Read ed3d-extending-claude:writing-claude-directives for foundational guidance on token efficiency, compliance techniques, and directive structure. This skill focuses on agent-specific patterns.

What is an Agent?

An agent is a specialized Claude instance with:

  • Defined tools (Read, Edit, Bash, etc.)
  • Specific responsibilities (code review, security audit, research)
  • A focused system prompt

Agents are spawned via the Task tool or defined in plugin agents/ directories.

When to Create an Agent

Create when:

  • Task requires specialized expertise
  • Workflow benefits from tool restrictions
  • You want consistent behavior across invocations
  • Task is complex enough to warrant context isolation

Don't create for:

  • Simple, one-off tasks
  • Tasks the main Claude handles well
  • Purely conversational interactions

Agent File Structure

agents/
  my-agent.md

Template:

markdown
---
name: agent-name
description: Use when [specific triggers] - [what agent does]
tools: Read, Grep, Glob, Bash
model: sonnet
---

# Agent Name

[Agent system prompt - who they are, what they do]

## Responsibilities
- Task 1
- Task 2

## Workflow
1. Step 1
2. Step 2

Description: The Critical Field

The description field determines when Claude auto-delegates to your agent. It's searched when matching tasks to available agents.

Writing Effective Descriptions

Format: "Use when [specific triggers/symptoms] - [what the agent does]"

Write in third person. Injected into system prompt.

yaml
# Bad: vague, no triggers
description: Helps with code

# Bad: first person
description: I review code for security issues

# Good: specific triggers + action
description: Use when reviewing code for security vulnerabilities, analyzing authentication flows, or checking for common security anti-patterns like SQL injection, XSS, or insecure dependencies

Include:

  • Specific symptoms that trigger use
  • Domain keywords (security, performance, testing)
  • File types or patterns if relevant
  • Actions the agent performs

Length: Max 1024 characters. Be specific, not verbose.

Tool Selection

Choose tools based on agent responsibilities:

ToolWhen to Include
ReadReading files, analyzing code
GrepSearching code patterns
GlobFinding files by pattern
EditModifying existing files
WriteCreating new files
BashRunning commands, git, tests
TaskCreate/TaskUpdateTracking multi-step workflows (TodoWrite in older versions)
TaskSpawning sub-agents
WebFetch/WebSearchResearch tasks

Principle: Include only what the agent needs. Fewer tools = more focused behavior.

Example restrictions:

  • Code reviewer: Read, Grep, Glob (no write access)
  • Implementor: Read, Edit, Write, Bash, Grep, Glob
  • Researcher: Read, WebFetch, WebSearch, Glob

Agent Prompt Structure

Role Definition

Start with who the agent is:

markdown
You are a security expert specializing in web application security and secure coding practices.

Responsibilities

Explicit, numbered list:

markdown
## Your Responsibilities

1. Identify security vulnerabilities
2. Review authentication logic
3. Check for insecure dependencies
4. Report findings with severity ratings

Workflow

Step-by-step process:

markdown
## Workflow

1. **Scan:** Use Grep to find common vulnerability patterns
2. **Analyze:** Use Read to examine flagged files
3. **Verify:** Use Bash to run security audit tools
4. **Report:** Provide structured findings

Output Format

Define expected structure:

markdown
## Reporting Format

For each finding:
- **Severity:** Critical/High/Medium/Low
- **Location:** `file:line`
- **Issue:** What's vulnerable
- **Impact:** What attacker could do
- **Fix:** How to remediate

Constraints

What the agent should NOT do:

markdown
## Constraints

- Report findings only; do not modify code
- Ask for clarification if scope is unclear
- Escalate to human for ambiguous security decisions

Model Selection

ModelUse For
haikuSimple tasks, fast iteration, high volume
sonnetBalanced capability/cost, most tasks
opusComplex reasoning, critical decisions, code review

Specify in frontmatter:

yaml
model: opus

Testing Agents

1. Baseline Test

Run the task WITHOUT the agent. Document:

  • What went wrong
  • What was missing
  • How long it took

2. Agent Test

Run with agent. Verify:

  • Agent is auto-delegated (description triggers correctly)
  • Workflow is followed
  • Output matches expected format
  • Tool restrictions are respected

3. Edge Case Testing

Test with:

  • Ambiguous inputs
  • Missing context
  • Large/complex inputs
  • Tasks outside scope (should refuse gracefully)

4. Iteration

If agent fails:

  1. Identify root cause (description? workflow? constraints?)
  2. Update agent definition
  3. Re-test

Common Patterns

Code Reviewer

markdown
---
name: code-reviewer
description: Use when reviewing code changes, pull requests, or verifying implementation quality - analyzes for bugs, style issues, and best practices
tools: Read, Grep, Glob, Bash
model: opus
---

# Code Reviewer

You are a senior engineer reviewing code for correctness, readability, and maintainability.

## Responsibilities
1. Identify bugs and edge cases
2. Check error handling
3. Verify naming and style consistency
4. Suggest improvements

## Workflow
1. Read the changed files
2. Analyze for issues
3. Provide structured feedback

## Output Format
For each issue:
- **File:Line:** location
- **Severity:** Critical/Major/Minor
- **Issue:** description
- **Suggestion:** how to fix

Research Agent

markdown
---
name: researcher
description: Use when gathering information from the web, investigating APIs, or synthesizing documentation from multiple sources
tools: Read, WebFetch, WebSearch, Glob
model: sonnet
---

# Research Agent

You are a research specialist gathering and synthesizing information.

## Responsibilities
1. Search for relevant sources
2. Extract key information
3. Synthesize findings
4. Cite sources

## Workflow
1. WebSearch for relevant sources
2. WebFetch promising results
3. Extract and organize findings
4. Return structured synthesis with citations

Implementor Agent

markdown
---
name: task-implementor
description: Use when implementing specific tasks from plans - writes code, runs tests, commits changes following TDD workflow
tools: Read, Edit, Write, Bash, Grep, Glob, TaskCreate, TaskUpdate, TaskList
model: sonnet
---

# Task Implementor

You implement tasks following TDD principles.

## Responsibilities
1. Write failing test first
2. Implement minimal code to pass
3. Refactor if needed
4. Commit with descriptive message

## Constraints
- Never write implementation before test
- Run tests after each change
- Commit atomic, working changes only

Common Mistakes

MistakeFix
Vague descriptionInclude specific triggers and symptoms
Too many toolsRestrict to what's needed
No workflowAdd step-by-step process
No output formatDefine expected structure
First-person descriptionWrite in third person
Overly broad scopeNarrow to specific responsibility
No testingTest auto-delegation and output quality

Checklist

  • Description starts with "Use when...", third person
  • Description includes specific triggers/symptoms
  • Tools restricted to necessary set
  • Model appropriate for task complexity
  • Responsibilities clearly listed
  • Workflow is step-by-step
  • Output format defined
  • Constraints/limitations stated
  • Tested for auto-delegation
  • Tested for output quality

Frequently asked questions

What does the Creating An Agent AI skill do?

Use when creating specialized subagents for Claude Code plugins or the Task tool - covers description writing for auto-delegation, tool selection, prompt structure, and testing agents

Why use Creating An Agent on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ed3dai/ed3d-plugins/tree/main/plugins/ed3d-extending-claude/skills/creating-an-agent. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Creating An 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 Creating An Agent?

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

Is the Creating An Agent AI skill free?

It is published on GitHub by ed3dai. 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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