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.
git clone --depth 1 https://github.com/tajmahal226/compound-engineering-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/tajmahal226/compound-engineering-plugin/generate_command)<a href="https://agentmods.dev/commands/tajmahal226/compound-engineering-plugin/generate_command"><img src="https://agentmods.dev/badge/commands/tajmahal226/compound-engineering-plugin/generate_command/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/tajmahal226/compound-engineering-plugin/generate_command"><img src="https://agentmods.dev/badge/commands/tajmahal226/compound-engineering-plugin/generate_command.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00014 | $0.00988 |
| Opus 5.5 | $0.00006 | $0.00395 |
| Sonnet 5.5 | $0.00003 | $0.00198 |
| Haiku 4.5 | $0.00001 | $0.00099 |
Grade A, and why
generate_command scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to generate_command — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create a Custom Claude Code Command
Create a new slash command in .claude/commands/ for the requested task.
Goal
#$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
- Be specific and clear - detailed instructions yield better results
- Break down complex tasks - use step-by-step plans
- Use examples - reference existing code patterns
- Include success criteria - tests pass, linting clean, etc.
- Think first - use "think hard" or "plan" keywords for complex problems
- 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 purposeargument-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)
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.
- 1mo ago First seen · 164 lines · 14 tokens per session scan A c6104c4d1b9d
generate_command is a command published in the GitHub repository tajmahal226/compound-engineering-plugin (4 stars, last pushed 7mo ago), licensed MIT. It adds 14 tokens to every session and 988 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to generate_command, differing in 1 line, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.