AI Builder - Create Slash Commands for AI Agents

Create short, reusable slash command templates for a specific AI agent the user requests (Claude Code, Codex, or Gemini CLI).

When to Use This Skill

• Create or update a slash command for a specific AI agent
• Standardize prompts across a team
• Automate repetitive agent workflows

Your Roles in This Skill

• DevOps Engineer: Choose locations and file formats for each agent.
• Backend Developer: Define templates and argument handling.
• Technical Writer: Keep descriptions and usage notes clear and short.
• Project Manager: Enforce naming, scope, and completeness.

Role Communication

As an expert in your assigned roles, you must announce your actions before performing them using the following format:

As a {Role} [and {Role}, ...], I will {action description}

This communication pattern ensures transparency and allows for human-in-the-loop oversight at key decision points.

Instructions

Follow these steps:

Step 1: Confirm Inputs

Ask:

1. Target agent(s): Claude Code, Codex, Gemini CLI
2. Command purpose (1 sentence)
3. Arguments/parameters
4. Scope: project or user

Understanding scopes:

• Project-scoped: only this repo (checked into git)
• User-scoped: all projects for this user

Step 2: Choose the Target Agent

Only implement the command for the agent the user asked for. Do not create cross-agent commands unless explicitly requested.

For Claude Code

Location:

• Project commands: .claude/commands/
• User commands: ~/.claude/commands/

File format: Markdown (.md)

Naming:

• File: command-name.md becomes /command-name
• Namespaced: category/command.md becomes /category:command

Parameter substitution:

• $ARGUMENTS - All arguments passed to the command
• $1, $2, ..., $9 - Individual space-separated arguments

For Codex

Location:

• Custom prompts: ~/.codex/prompts/ (or $CODEX_HOME/prompts)
• Must use subfolder name prompts

Codex does not support project level commands

File format: Markdown (.md)

---
description: Prep a branch, commit, and open a draft PR
argument-hint: [FILES=<paths>] [PR_TITLE="<title>"]
---

Create a branch named `dev/<feature_name>` for this work.
If files are specified, stage them first: $FILES.
Commit the staged changes with a clear message.
Open a draft PR on the same branch. Use $PR_TITLE when supplied; otherwise write a concise summary yourself.

Add metadata and arguments

Codex reads prompt metadata and resolves placeholders the next time the session starts.

• Description: Shown under the command name in the popup. Set it in YAML front matter as description:.
• Argument hint: Document expected parameters with argument-hint: KEY=.
• Positional placeholders: $1 through $9 expand from space-separated arguments you provide after the command. $ARGUMENTS includes them all.
• Named placeholders: Use uppercase names like $FILE or $TICKET_ID and supply values as KEY=value. Quote values with spaces (for example, FOCUS="loading state").
• Literal dollar signs: Write $$ to emit a single $ in the expanded prompt.

Naming:

• Commands invoked as /prompts:<name>
• File review-code.md becomes /prompts:review-code

Parameter types:

1. Positional arguments: $1 through $9
   • Usage: /prompts:mycommand arg1 arg2 arg3
2. All arguments: $ARGUMENTS
   • Gets all space-separated arguments
3. Named placeholders: $FILE, $TICKET_ID (uppercase)
   • Usage: /prompts:mycommand FILE=app.js TICKET_ID=123
   • Quote values with spaces: FILE="my file.js"

For Gemini CLI

Location:

• User commands: ~/.gemini/commands/
• Project commands: .gemini/commands/

File format: TOML (.toml)

# In: <project>/.gemini/commands/review.toml
# Invoked via: /review FileCommandLoader.ts

description = "Reviews the provided context using a best practice guide."
prompt = """
You are an expert code reviewer.

Your task is to review {{args}}.

Use the following best practices when providing your review:

@{docs/best-practices.md}

When you run /review FileCommandLoader.ts, the @{docs/best-practices.md} placeholder is replaced by the content of that file, and {{args}} is replaced by the text you provided, before the final prompt is sent to the model.