Claude-skill-registry genaiscript

Comprehensive expertise for working with Microsoft's GenAIScript framework - a JavaScript/TypeScript-based system for building automatable LLM prompts and AI workflows. Use when creating, debugging, or optimizing GenAIScript scripts, implementing prompts-as-code, working with tools and agents, processing files (PDF, CSV, DOCX), defining schemas, or building AI automation workflows.

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/genaiscript" ~/.claude/skills/majiayu000-claude-skill-registry-genaiscript && rm -rf "$T"
manifest: skills/data/genaiscript/SKILL.md
source content

GenAIScript Expert

You are an expert in Microsoft's GenAIScript framework, a JavaScript-based system for building automatable prompts and AI workflows. This skill provides orchestrated access to comprehensive GenAIScript documentation.

What GenAIScript Feature Do I Need?

Use this decision table to find the right resource for your task:

Your TaskCore ConceptsAPI RefExamplesPatterns
Understanding framework fundamentals
Explaining script structure, workflow basics
Learning specific API functions
Using
$
,
def()
,
defSchema()
,
defTool()
, etc.
Building practical solutions
Code review, doc generation, testing scripts
Designing robust solutions
Performance, error handling, modular architecture
Advanced workflows, design patterns, optimization
Token management, caching, parallelization

Quick Start

1. Basic Script Structure

script({
    title: "My Script",
    description: "What this does",
    model: "openai:gpt-4"
})

def("FILE", env.files)
$`Analyze the FILE and provide insights.`

See resources/core-concepts.md for detailed explanation.

2. Include Context

// Include file content
def("CODE", env.files, { endsWith: ".ts", lineNumbers: true })

// Include structured data
const rows = await parsers.CSV(env.files[0])
defData("ROWS", rows)

// Define output structure
const schema = defSchema("RESULT", {
    type: "object",
    properties: { /* schema */ }
})

See resources/api-reference.md for all functions.

3. Common Patterns

  • Code review & analysis → resources/examples.md (Code Quality section)
  • Documentation generation → resources/examples.md (Documentation section)
  • Data extraction → resources/examples.md (Data Processing section)
  • Performance optimization → resources/patterns.md (Performance section)

3-Phase Orchestration Protocol

Phase 1: Task Analysis

Determine what you're building:

Script Purpose:

  • Analysis: Review code, find issues, validate structure
  • Generation: Create tests, docs, code, configs
  • Transformation: Convert formats, migrate code, refactor
  • Integration: Connect APIs, process files, orchestrate workflows

Complexity Level:

  • Simple: Single LLM call, clear requirements
  • Intermediate: 2-3 LLM calls, structured outputs
  • Advanced: Multi-step workflows, agents, tools, caching

Phase 2: Resource Selection

Load resources based on task type:

  • Starting out → Load
    resources/core-concepts.md
  • Need API details → Load
    resources/api-reference.md
  • Building solution → Load
    resources/examples.md
    (find similar example)
  • Optimizing → Load
    resources/patterns.md
    (see advanced patterns)
  • Complex task → Load
    resources/patterns.md
    (design patterns section)

Phase 3: Execution & Validation

While building:

  • Reference decision table above to navigate resources
  • Use examples as templates
  • Follow patterns for performance/reliability

Before using script:

  • Validate file inputs are available
  • Test with sample data
  • Check token budget (see patterns/performance)
  • Verify schema matches expected output

Core Concepts Overview

GenAIScript enables:

  • Prompt-as-Code: Build prompts programmatically with JavaScript/TypeScript
  • File Processing: Import context from PDFs, DOCX, CSV, and other formats
  • Tool Integration: Define custom tools and agents for LLMs
  • Structured Output: Generate files, edits, and structured data from LLM responses
  • MCP Support: Integrate with Model Context Protocol tools and resources

For detailed explanation of concepts, see resources/core-concepts.md

Resource Files

ResourcePurposeSizeBest For
core-concepts.mdFramework fundamentals, script structure, file processing~280 linesLearning basics, understanding how GenAIScript works
api-reference.mdComplete API documentation, function signatures, parameters~350 linesLooking up function details, understanding options
examples.mdPractical examples for common use cases~400 linesBuilding solutions, finding templates
patterns.mdAdvanced patterns, optimization, best practices, design patterns~350 linesOptimizing performance, handling complex tasks

Common Workflows

I want to...

Analyze existing code

  1. Read
    resources/core-concepts.md
    (understand
    def()
    )
  2. Check
    resources/examples.md
    → Code Quality section
  3. See
    resources/patterns.md
    → Error Handling

Generate documentation

  1. Check
    resources/examples.md
    → Documentation section
  2. Use example as template
  3. See
    resources/api-reference.md
    for
    defFileOutput()

Process files and extract data

  1. Read
    resources/core-concepts.md
    (file processing section)
  2. Check
    resources/examples.md
    → Data Processing section
  3. Reference
    resources/api-reference.md
    → Parsers

Build multi-step workflow

  1. See
    resources/patterns.md
    → Design Patterns (Chain of Responsibility)
  2. Check
    resources/examples.md
    → Advanced Workflows section
  3. Reference
    resources/api-reference.md
    for function details

Optimize performance or debug

  1. See
    resources/patterns.md
    → Performance Optimization section
  2. Check
    resources/patterns.md
    → Error Handling section
  3. Reference
    resources/api-reference.md
    for token management options

Quick Reference

ComponentLearn More
$
template tag
api-reference.md § Core Functions
def()
file inclusion
api-reference.md § Core Functions
defSchema()
output structure
api-reference.md § Core Functions + examples.md
defTool()
,
defAgent()
api-reference.md § Core Functions
Parsers (PDF, CSV, XLSX, etc.)api-reference.md § Parsers
Environment variablesapi-reference.md § Environment + core-concepts.md
Token managementpatterns.md § Performance Optimization
Error handlingpatterns.md § Error Handling
Design patternspatterns.md § Design Patterns

Getting Help

When helping with GenAIScript:

  1. Ask what they're building - Analysis? Generation? Transformation?
  2. Point to resource - Use decision table above
  3. Show example - See
    resources/examples.md
    for similar use case
  4. Check patterns - For optimization/debugging, see
    resources/patterns.md
  5. Reference API - For specific functions, see
    resources/api-reference.md

VS Code Integration

GenAIScript includes a VS Code extension with:

  • Syntax highlighting for
    .genai.mjs
    files
  • IntelliSense for API functions
  • Debug support with breakpoints
  • Script runner to test scripts
  • Output preview for generated files
# Running scripts
genaiscript run <script-name>
genaiscript run <script-name> file1.ts file2.ts
genaiscript run <script-name> --var KEY=value
genaiscript run <script-name> --model openai:gpt-4

See

resources/core-concepts.md
for more details.


Navigation Tip: Each resource file contains cross-references. Start with the resource matching your task type, then follow "See also" links as needed.