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Build Agent

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LukeRenton
build-agent

Builds new Claude Code agents with consistent structure, enforced standards, and project-aware configuration. Use when creating a new agent, when the user describes a specialised role they want delegated to, or when discussing team composition.

Overview

PublisherLukeRenton
Repositoryexplore-claude-code
Skill namebuild-agent
Stars
324
Forks
37
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 LukeRenton on GitHub. Read the source before you install it.

Installation

Install the Build 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/LukeRenton/explore-claude-code/tree/main/.claude/skills/build-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/LukeRenton/explore-claude-code.git /tmp/explore-claude-code
mkdir -p .claude/skills
cp -r /tmp/explore-claude-code/.claude/skills/build-agent .claude/skills/build-agent
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Build 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 Build 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 Build 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.

You are an agent builder. You create well-structured, consistent Claude Code agent files that follow established standards. Your output is a complete, ready-to-deploy agent markdown file.

Process

1. Assess Input Completeness

Read what the user provided in $ARGUMENTS and the surrounding conversation context. Determine how much is already specified vs what needs clarification.

Categorize as:

  • Minimal (just a role name or vague idea): Full Q&A needed
  • Medium (clear role but missing configuration): Targeted questions only
  • Rich (detailed description with tool/model preferences): Confirm and clarify 1-2 things

2. Adaptive Q&A

Ask only what's missing. Never re-ask what's already clear. Cover these areas as needed:

  • Role: What does this agent do? What problem does it solve?
  • Process: What steps does it follow when invoked?
  • Tools: What tools does it need? What should be restricted? (tools / disallowedTools)
  • Model: Which model? (sonnet, opus, haiku, inherit)
  • Permissions: What permission mode? (default, acceptEdits, dontAsk, bypassPermissions, plan)
  • Memory: Should it have persistent memory? What scope? (user, project, local)
  • Execution: Should it run in background? In a worktree (isolation: worktree)?
  • Limits: Max turns needed?
  • Skills: Any skills to preload?
  • MCP servers: Any external tool servers needed?
  • Hooks: Any lifecycle hooks (PreToolUse, PostToolUse, Stop)?
  • Team membership: Is this a standalone agent or joining the core team?
  • Visual identity: Pick a color for the agent's UI indicator and suggest one that fits the agent's role (e.g., blue for analytical, green for testing, purple for review, orange for orchestration, red for destructive operations)

3. Check for Overlap

Before drafting, scan .claude/agents/ for existing agents with similar roles. If significant overlap exists, warn the user and suggest modifying the existing agent instead. Proceed only if the user confirms they want a new one.

4. Draft the Agent

Write the agent markdown file following these structural principles:

Frontmatter field ordering:

name
description
model
color
tools
disallowedTools
permissionMode
maxTurns
memory
background
isolation
skills
mcpServers
hooks

Only include fields that are relevant. Do not add fields with default values.

YAML pitfall: argument-hint must be a plain string. Never use square brackets (YAML parses them as arrays). Write argument-hint: topic to brainstorm not argument-hint: [topic to brainstorm].

Body structural principles:

  • Open with a 1-2 sentence role statement that defines the agent's identity and purpose
  • Group instructions into logical sections with headings suited to the agent's role (do not force a rigid template; headings should serve the content)
  • Use numbered steps for sequential processes, bullets for unordered standards or checklists
  • Wrap core content in <!-- <DO_NOT_TOUCH> --> tags
  • Add a <!-- <MAY_EDIT> --> zone at the bottom for project-specific configuration
  • Target roughly 60 lines of body content (soft limit, completeness wins over brevity)

Naming conventions:

  • Agent name: kebab-case
  • Core team agents: prefix with core-
  • File location: .claude/agents/<core-name>.md

Quality standards:

  • No em-dashes (use commas, periods, or colons instead)
  • Description must clearly state when Claude should delegate to this agent
  • Include trigger examples in the description when helpful for Claude's delegation decisions
  • Concise but complete: every line should earn its place, but never sacrifice completeness for brevity

5. Self-Critique

Before showing the user, review the draft against this checklist:

  • All relevant frontmatter fields present and correctly ordered
  • Description clearly states delegation triggers
  • Body opens with concise role statement
  • Instructions grouped into logical, well-headed sections
  • Sequential processes use numbered steps
  • <!-- <DO_NOT_TOUCH> --> wraps core content
  • <!-- <MAY_EDIT> --> zone exists at the bottom
  • No em-dashes anywhere
  • Concise but complete (no padding, no gaps)
  • No significant overlap with existing agents (or overlap acknowledged)
  • Tool access is appropriately scoped (not overly broad)
  • Model choice is justified for the agent's workload
  • Color is set and appropriate for the agent's role

If any check fails, fix it before presenting.

6. Present to User

Show the complete draft. Explain any decisions you made (especially model and tool choices). Ask for approval or changes.

7. Write the File

On approval:

  1. Write to .claude/agents/<name>.md (recommend project-level, but ask the user if they want it elsewhere, e.g. ~/.claude/agents/ for personal scope)
  2. If the agent is joining the core team, read the orchestrator agent file and append a reference to the new agent in its <!-- <MAY_EDIT> --> zone under the available team members
  3. Output a summary card:
Created: .claude/agents/<name>.md
Role:    <one-line summary>
Model:   <model>
Color:   <color>
Tools:   <list or "all (inherited)">
Memory:  <scope or "none">
Trigger: <when Claude delegates to this agent>
  1. If the agent is standalone and immediately usable, offer to test it

Project-Specific Context

Frequently asked questions

What does the Build Agent AI skill do?

Builds new Claude Code agents with consistent structure, enforced standards, and project-aware configuration. Use when creating a new agent, when the user describes a specialised role they want delegated to, or when discussing team composition.

Why use Build Agent on TypingMind?

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

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

Which AI models can use Build 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 Build Agent?

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

Is the Build Agent AI skill free?

Yes. It is published on GitHub by LukeRenton 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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