Engineer Command

Command Creator

This skill provides guidance for creating effective flowai commands.

Question Format (FR-UNIVERSAL.QA-FORMAT)

When asking the user a choice (IDE, scope, examples to cover):

• Each question MUST be a numbered list item (1., 2., …) — not a heading, bold-only line, or paragraph.
• For multi-select questions, when the user delegates with agent's choice (or equivalent), pick the subset yourself, emit a one-line justification of the pick, and proceed without re-asking for confirmation.

About flowai Commands

Commands are modular, self-contained packages that extend flowai's capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform flowai from a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.

What Commands Provide

1. Specialized workflows - Multi-step procedures for specific domains
2. Tool integrations - Instructions for working with specific file formats or APIs
3. Domain expertise - Company-specific knowledge, schemas, business logic
4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks

IDE Detection and Command Placement

Commands work across multiple IDEs. Before creating a command, determine the current environment and ask the user where to place it.

Command Paths by IDE

Note: Claude Code unifies commands and skills. .claude/commands/ is the legacy path; .claude/skills/ (SKILL.md format) is recommended for new commands.

OpenCode supports $ARGUMENTS, $1-$N, @filepath and bang-backtick shell interpolation (!shell command) in command templates. Keep that bang glued to the preceding character: Claude Code executes any bang-backtick pair preceded by whitespace while it expands a slash command, and a code span does not escape it.

Detection Strategy

1. Check for IDE-specific markers in the project:
   • .cursor/ directory → Cursor
   • .claude/ directory → Claude Code
   • .opencode/ directory or opencode.json → OpenCode
2. If multiple detected or none → ask the user
3. Ask: personal command (user-level) or project command (shared via repo)?

Core Principles

Concise is Key

The context window is a public good. Commands share the context window with everything else flowai needs: system prompt, conversation history, other Commands' metadata, and the actual user request.

Default assumption: flowai is already very smart. Only add context flowai doesn't already have. Challenge each piece of information: "Does flowai really need this explanation?" and "Does this paragraph justify its token cost?"

Prefer concise examples over verbose explanations.

Set Appropriate Degrees of Freedom

Match the level of specificity to the task's fragility and variability:

High freedom (text-based instructions): Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.

Medium freedom (pseudocode or scripts with parameters): Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.

Low freedom (specific scripts, few parameters): Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.

Think of flowai as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).

Anatomy of a Command

Every command consists of a required SKILL.md file and optional bundled resources, located in .cursor/skills/cmd-<name>:

cmd-<name>/
├── SKILL.md (required)
│   ├── YAML frontmatter metadata (required)
│   │   ├── name: (required)
│   │   └── description: (required)
│   └── Markdown instructions (required)
└── Bundled Resources (optional)
    ├── scripts/          - Executable code (Python/Bash/etc.)
    ├── references/       - Documentation intended to be loaded into context as needed
    └── assets/           - Files used in output (templates, icons, fonts, etc.)

SKILL.md (required)

Every SKILL.md consists of:

• Frontmatter (YAML): Contains name and description fields. These are the only fields that flowai reads to determine when the command gets used, thus it is very important to be clear and comprehensive in describing what the command is, and when it should be used.
• Body (Markdown): Instructions and guidance for using the command. Only loaded AFTER the command triggers (if at all).

Bundled Resources (optional)

Scripts (scripts/)

Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.

• When to include: When the same code is being rewritten repeatedly or deterministic reliability is needed
• Example: scripts/rotate_pdf.py for PDF rotation tasks
• Benefits: Token efficient, deterministic, may be executed without loading into context
• Note: Scripts may still need to be read by flowai for patching or environment-specific adjustments

References (references/)

Documentation and reference material intended to be loaded as needed into context to inform flowai's process and thinking.

• When to include: For documentation that flowai should reference while working
• Examples: references/finance.md for financial schemas, references/mnda.md for company NDA template, references/policies.md for company policies, references/api_docs.md for API specifications
• Use cases: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
• Benefits: Keeps SKILL.md lean, loaded only when flowai determines it's needed
• Best practice: If files are large (>10k words), include grep search patterns in SKILL.md
• Avoid duplication: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the command—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.

Assets (assets/)

Files not intended to be loaded into context, but rather used within the output flowai produces.

• When to include: When the command needs files that will be used in the final output
• Examples: assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typography
• Use cases: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
• Benefits: Separates output resources from documentation, enables flowai to use files without loading them into context

What to Not Include in a Command

A command should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:

• README.md
• INSTALLATION_GUIDE.md
• QUICK_REFERENCE.md
• CHANGELOG.md
• etc.

The command should only contain the information needed for an AI agent to do the job at hand. It should not contain auxilary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.

Progressive Disclosure Design Principle

Commands use a three-level loading system to manage context efficiently:

1. Metadata (name + description) - Always in context (~100 words)
2. SKILL.md body - When command triggers (<5k words)
3. Bundled resources - As needed by flowai (Unlimited because scripts can be executed without reading into context window)

Progressive Disclosure Patterns

Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the command knows they exist and when to use them.

Key principle: When a command supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.

Pattern 1: High-level guide with references

# PDF Processing

## Quick start

Extract text with pdfplumber:
[code example]

## Advanced features

- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns

flowai loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.

Pattern 2: Domain-specific organization

For Commands with multiple domains, organize content by domain to avoid loading irrelevant context:

bigquery/
├── SKILL.md (overview and navigation)
└── reference/
    ├── finance.md (revenue, billing metrics)
    ├── sales.md (opportunities, pipeline)
    ├── product.md (API usage, features)
    └── marketing.md (campaigns, attribution)

When a user asks about sales metrics, flowai only reads sales.md.

Similarly, for commands supporting multiple frameworks or variants, organize by variant:

cloud-deploy/
├── SKILL.md (workflow + provider selection)
└── references/
    ├── aws.md (AWS deployment patterns)
    ├── gcp.md (GCP deployment patterns)
    └── azure.md (Azure deployment patterns)

When the user chooses AWS, flowai only reads aws.md.

Pattern 3: Conditional details

Show basic content, link to advanced content:

# DOCX Processing

## Creating documents

Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).

## Editing documents

For simple edits, modify the XML directly.

**For tracked changes**: See [REDLINING.md](REDLINING.md)
**For OOXML details**: See [OOXML.md](OOXML.md)

flowai reads REDLINING.md or OOXML.md only when the user needs those features.

Important guidelines:

• Avoid deeply nested references - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md.
• Structure longer reference files - For files longer than 100 lines, include a table of contents at the top so flowai can see the full scope when previewing.

Command Creation Process

Command creation involves these steps:

1. Understand the command with concrete examples
2. Plan reusable command contents (scripts, references, assets)
3. Initialize the command (run init_command.ts)
4. Edit the command (implement resources and write SKILL.md)
5. Package the command (run package_command.ts)
6. Iterate based on real usage

Follow these steps in order, skipping only if there is a clear reason why they are not applicable.

Step 1: Understanding the Command with Concrete Examples

Skip this step only when concrete user utterances are already on record — the words someone would actually type to invoke the command. A familiar domain is not that, and neither is a list of capability areas: "starting/stopping services, viewing logs, rebuilding containers, checking health" is a feature spec, while "bring up just the db", "why is my api container restarting?" and "rebuild after I changed the Dockerfile" are examples. The difference decides the description field, which is the only thing that makes the command trigger at all — a description written from domain knowledge instead of from validated utterances is the substitution this step exists to prevent. Given a feature spec, either ask what the user would say to trigger the command, or draft the utterances yourself and have them confirmed before moving on. It remains valuable even when working with an existing command.

To create an effective command, clearly understand concrete examples of how the command will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.

For example, when building an image-editor command, relevant questions include:

• "What functionality should the image-editor command support? Editing, rotating, anything else?"
• "Can you give some examples of how this command would be used?"
• "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this command being used?"
• "What would a user say that should trigger this command?"

To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.

Conclude this step when there is a clear sense of the functionality the command should support.

Step 2: Planning the Reusable Command Contents

To turn concrete examples into an effective command, analyze each example by:

1. Considering how to execute on the example from scratch
2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly

Example: When building a pdf-editor command to handle queries like "Help me rotate this PDF," the analysis shows:

1. Rotating a PDF requires re-writing the same code each time
2. A scripts/rotate_pdf.py script would be helpful to store in the command

Example: When designing a webapp-builder command for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows:

1. Writing a frontend webapp requires the same boilerplate HTML/React each time
2. An assets/hello-world/ template containing the boilerplate HTML/React project files would be helpful to store in the command

Example: When building a big-query command to handle queries like "How many users have logged in today?" the analysis shows:

1. Querying BigQuery requires re-discovering the table schemas and relationships each time
2. A references/schema.md file documenting the table schemas would be helpful to store in the command

To establish the command's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.

Step 3: Initializing the Command

At this point, it is time to actually create the command.

Skip this step only if the command being developed already exists, and iteration or packaging is needed. In this case, continue to the next step.

When creating a new command from scratch, always run the init_command.ts script. The script conveniently generates a new template command directory that automatically includes everything a command requires, making the command creation process much more efficient and reliable.

Usage:

deno run -A scripts/init_command.ts <command-name> --path <output-directory>

The script:

• Creates the command directory at the specified path
• Generates a SKILL.md template with proper frontmatter and TODO placeholders
• Creates example resource directories: scripts/, references/, and assets/
• Adds example files in each directory that can be customized or deleted

After initialization, customize or remove the generated SKILL.md and example files as needed.

Step 4: Edit the Command

When editing the (newly-generated or existing) command, remember that the command is being created for another instance of flowai to use. Include information that would be beneficial and non-obvious to flowai. Consider what procedural knowledge, domain-specific details, or reusable assets would help another flowai instance execute these tasks more effectively.

Learn Proven Design Patterns

Consult these helpful guides based on your command's needs:

• Multi-step processes: See references/workflows.md for sequential workflows and conditional logic
• Specific output formats or quality standards: See references/output-patterns.md for template and example patterns

These files contain established best practices for effective command design.

Start with Reusable Command Contents

To begin implementation, start with the reusable resources identified above: scripts/, references/, and assets/ files. Note that this step may require user input. For example, when implementing a brand-guidelines command, the user may need to provide brand assets or templates to store in assets/, or documentation to store in references/.

Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.

Any example files and directories not needed for the command should be deleted. The initialization script creates example files in scripts/, references/, and assets/ to demonstrate structure, but most commands won't need all of them.

Update SKILL.md

Writing Guidelines: Always use imperative/infinitive form.

Frontmatter

Write the YAML frontmatter with name and description:

• name: The command name
• description: This is the primary triggering mechanism for your command, and helps flowai understand when to use the command.
  • Include both what the Command does and specific triggers/contexts for when to use it.
  • Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Command" sections in the body are not helpful to flowai.
  • Example description for a docx command: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when flowai needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"

Do not include any other fields in YAML frontmatter.

Body

Write instructions for using the command and its bundled resources.

Step 5: Packaging a Command

Once development of the command is complete, it must be packaged into a distributable .skill file that gets shared with the user. The packaging process automatically validates the command first to ensure it meets all requirements:

deno run -A scripts/package_command.ts <path/to/command-folder>

Optional output directory specification:

deno run -A scripts/package_command.ts <path/to/command-folder> ./dist

The packaging script will:

1. Validate the command automatically, checking:

   • YAML frontmatter format and required fields
   • Command naming conventions and directory structure
   • Description completeness and quality
   • File organization and resource references

2. Package the command if validation passes, creating a .skill file named after the command (e.g., my-command.skill) that includes all files and maintains the proper directory structure for distribution. The .skill file is a zip file with a .skill extension.

If validation fails, the script will report the errors and exit without creating a package. Fix any validation errors and run the packaging command again.

Step 6: Iterate

After testing the command, users may request improvements. Often this happens right after using the command, with fresh context of how the command performed.

Iteration workflow:

1. Use the command on real tasks
2. Notice struggles or inefficiencies
3. Identify how SKILL.md or bundled resources should be updated
4. Implement changes and test again