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Guide for creating specialized Claude Code subagents with proper YAML frontmatter, focused descriptions, system prompts, and tool configurations.
Passed 20 of 22 test cases with the skill, and 13 of 22 without it.
and 4 more in the full report
7 fixed13 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
Show the bash command to create the personal user-level directory structure for global subagents on a Unix machine.
| Checked | Without skill | With skill |
|---|---|---|
| runs mkdir -p ~/.agent/agents | Missed | Passed |
The instructions your model reads when the skill loads.
This skill guides you through creating custom subagents for this platform. Subagents are specialized AI assistants that run in isolated contexts with custom system prompts.
Subagents help you:
If you have previous conversation context, infer the subagent's purpose and behavior from what was discussed. Create the subagent based on specialized tasks or workflows that emerged in the conversation.
| Location | Scope | Priority |
|---|---|---|
| Workspace agents directory | Current project | Higher |
| User agents directory | All your projects | Lower |
When multiple subagents share the same name, the higher-priority location wins.
Project subagents (workspace-level): Ideal for codebase-specific agents. Check into version control to share with your team.
User subagents (user-level): Personal agents available across all your projects.
Create a .md file with YAML frontmatter and a markdown body (the system prompt):
---
name: code-reviewer
description: Reviews code for quality and best practices
---
You are a code reviewer. When invoked, analyze the code and provide
specific, actionable feedback on quality, security, and best practices.
test cases passed, vs 13 / 22 without
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