Agent skill · data analytics · aiskillstore
data-processor
Process and transform arrays of data with common operations like filtering, mapping, and aggregation
Why this skill is useful
Provides specific implementation for data transformations that the AI wouldn't reliably generate on its own.
What it needs
About 4k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Data Processor Skill A general-purpose data processing skill for transforming arrays of objects. This skill demonstrates the token efficiency benefits of code execution - instead of describing transformations in natural language, write code once and reuse it. What This Skill Does Processes arrays of data with common transformations: Filter records based on conditions Map fields to new values Aggregate data (sum, average, count, etc.) Sort and group data Remove duplicates Merge datasets When to Use This Skill Use this skill when you need to: Transform large datasets (hundreds or thousands of records) Apply consistent business logic to data Aggregate or summarize data Clean or normalize data Combine data from multiple sources Token Efficiency: Processing 1000 records in code uses ~500 tokens. Describing the same operations in natural language would use ~50,000 tokens. Implementation Examples Example 1: Filter and Sort Example 2: Aggregate Data Example 3: Complex Transformation Integration with MCP Tools This skill works great in combination with MCP tools: Tips and Best Practices 1. Save Intermediate Results: For large datasets, save to /workspace after each major operation 2. Return Summaries: Send statistics to the agent, not full datasets 3. Chain Operations: Combine multiple operations for complex transformations 4. Validate Input: Always check data types and handle edge cases 5. Reuse This Skill: Save to /skills and use across multiple tasks Related Skills validator - Validate data before processing exporter - Export processed data to various formats aggregator - Advanced statistical aggregations Performance Notes This skill can process: 1,000 records: < 50ms 10,000 records: < 200ms 100,000 records: < 2s All operations use efficient JavaScript array methods with O(n) or O(n log n) complexity. --- Inspired by: The Anthropic skills pattern for token-efficient data processing. See Code Execution with MCP for the philosophy behind this approach.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/data-processor