generate_command

A workflow for creating custom slash commands, which are named instructions launched from a coding tool’s command menu.

In plain words
What is it for?
Use it to create commands in .claude/commands/ for file changes, development work, web research, browser automation, integrations, and validation.
Why use it?
It provides a consistent structure so new commands clearly describe their task, steps, tools, and success checks.

Command

Part of the compound-engineering plugin — 20 skills, 17 commands, 1 MCP server shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/tajmahal226/compound-engineering-plugin/generate_command
Clone the repo
git clone --depth 1 https://github.com/tajmahal226/compound-engineering-plugin

Or install compound-engineering, the plugin that ships this one along with the rest of its 20 skills, 17 commands, 1 MCP server.

Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 988 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.00988
Opus 5 $0.00007 $0.00494
Sonnet 5 $0.00003 $0.00198
Haiku 4.5 $0.00001 $0.00099

Measured 3d ago against content hash c6104c4d1b9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

generate_command scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

plugins/compound-engineering/commands/generate_command.md · 164 lines

How it starts

The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create a Custom Claude Code Command

Create a new slash command in .claude/commands/ for the requested task.

Goal

#$ARGUMENTS

Key Capabilities to Leverage

File Operations:

  • Read, Edit, Write - modify files precisely
  • Glob, Grep - search codebase
  • MultiEdit - atomic multi-part changes

Development:

  • Bash - run commands (git, tests, linters)
  • Task - launch specialized agents for complex tasks
  • TodoWrite - track progress with todo lists

Web & APIs:

  • WebFetch, WebSearch - research documentation
  • GitHub (gh cli) - PRs, issues, reviews
  • Playwright - browser automation, screenshots

Integrations:

  • AppSignal - logs and monitoring
  • Context7 - framework docs
  • Stripe, Todoist, Featurebase (if relevant)

Best Practices

  1. Be specific and clear - detailed instructions yield better results
  2. Break down complex tasks - use step-by-step plans
  3. Use examples - reference existing code patterns
  4. Include success criteria - tests pass, linting clean, etc.
  5. Think first - use "think hard" or "plan" keywords for complex problems
  6. Iterate - guide the process step by step

Required: YAML Frontmatter

EVERY command MUST start with YAML frontmatter:

---
name: command-name
description: Brief description of what this command does (max 100 chars)
argument-hint: "[what arguments the command accepts]"
---

Fields:

  • name: Lowercase command identifier (used internally)
  • description: Clear, concise summary of command purpose
  • argument-hint: Shows user what arguments are expected (e.g., [file path], [PR number], [optional: format])

Structure Your Command

# [Command Name]

[Brief description of what this command does]

## Steps

1. [First step with specific details]
   - Include file paths, patterns, or constraints
   - Reference existing code if applicable

2. [Second step]
   - Use parallel tool calls when possible
   - Check/verify results

3. [Final steps]
   - Run tests
   - Lint code
   - Commit changes (if appropriate)

## Success Criteria

- [ ] Tests pass
- [ ] Code follows style guide
- [ ] Documentation updated (if needed)

Read the full file on GitHub · 164 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 164 lines · 14 tokens per session scan A c6104c4d1b9d

Subscribe to this mod's changes

generate_command is a command published in the GitHub repository tajmahal226/compound-engineering-plugin (4 stars, last pushed 6mo ago), licensed MIT. It adds 14 tokens to every session and 988 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.