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 Task	Core Concepts	API Ref	Examples	Patterns
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

Resource	Purpose	Size	Best For
core-concepts.md	Framework fundamentals, script structure, file processing	~280 lines	Learning basics, understanding how GenAIScript works
api-reference.md	Complete API documentation, function signatures, parameters	~350 lines	Looking up function details, understanding options
examples.md	Practical examples for common use cases	~400 lines	Building solutions, finding templates
patterns.md	Advanced patterns, optimization, best practices, design patterns	~350 lines	Optimizing 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

Component	Learn 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 variables	api-reference.md § Environment + core-concepts.md
Token management	patterns.md § Performance Optimization
Error handling	patterns.md § Error Handling
Design patterns	patterns.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.

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