Individual skill
file-to-code
Generates production-ready code from file specifications such as CSV files, JSON schemas, SQL DDL, protobuf definitions, or requirements documents. Use when the user wants to convert a data file or specification into working code. Trigger with phrases like "generate code from this CSV", "create an API from this schema", "build a parser for this file", or "turn this spec into code".
skills/.curated/file-to-code/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Observed behavior
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- Last checked
- Nov 12, 2026
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Repository context
- Repository stars (not skill ratings)
- 2,916
- Repository last updated
- Nov 12, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- code-generation Declared skill tag
- requirements Declared skill tag
- automation Declared skill tag
- api-design Declared skill tag
- data Derived category
- data-databases Derived category
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SKILL.mdcore · 6,348 bytes
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# File to Code
Generate production-ready code from file specifications, data schemas, and requirements documents.
## Overview
This skill reads structured input files -- CSV data, JSON schemas, SQL DDL statements, protobuf definitions, OpenAPI specs, or plain-text requirements -- and generates complete, production-ready code to process, serve, or transform that data. Instead of manually writing boilerplate models, validation logic, and CRUD endpoints, this skill analyzes the input structure and produces well-typed code with proper error handling, input validation, and test coverage.
The skill supports multiple output languages and frameworks. It infers types from data samples, respects constraints defined in schemas, and follows best practices for the target framework. When generating API endpoints, it includes request validation, error responses, and OpenAPI documentation. When generating data processing pipelines, it includes type coercion, null handling, and logging.
## Instructions
1. **Point to the input file** or paste its contents:
- "Read `data/users.csv` and generate a REST API for it"
- "Here's my JSON schema: `{ ... }` -- generate TypeScript types and a validator"