skill-name

Filter and summarize large API or file data into compact cached summaries.

24|3|Updated Aug 2, 2020
One-click install
npx skills add https://github.com/ooloth/dotfiles --skill skill-name-ooloth
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill-name
Source: https://github.com/ooloth/dotfiles/tree/main/tools/claude/config/skills/@template
Command: npx skills add https://github.com/ooloth/dotfiles --skill skill-name-ooloth

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This template demonstrates the MCP code execution pattern and best practices for building Claude skills that process data deterministically and return curated results.

Core Features & Use Cases

  • Deterministic processing: Structured data handling with typed interfaces.
  • Caching patterns: Illustrates how to cache results to reduce repeated work.
  • Error handling: Clear user-friendly error messages and boundaries.

Quick Start

Copy this template to your own skill and customize the logic, then run locally to validate.

Frequently Asked Questions about skill-name

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce token usage when processing large data from APIs?

Filter and summarize raw data before returning results to cut token overhead. This template demonstrates deterministic filtering patterns, caching for reuse, and field sanitization to keep only essential information from API responses.

What's the best way to handle sensitive data when fetching from APIs or files?

Sanitize secrets and sensitive fields before processing or caching results. This skill implements deterministic security by removing credentials, tokens, and private data at the filtering stage, reducing exposure in stored or returned data.

How do I cache results to avoid repeated API calls in Claude workflows?

Implement caching patterns within your skill's processing logic to store filtered results locally. This template shows how to cache curated data after fetching and filtering, so subsequent requests reuse results instead of re-fetching.

Can I use typed data models with MCP code execution in Claude?

Yes. This template demonstrates strict typing via hints and data models for deterministic processing. Structured interfaces ensure consistent data handling, validation, and type safety across filtered results before returning to Claude.

What error handling patterns work best for data-heavy Claude skills?

Use clear, user-friendly error messages with defined boundaries for processing failures. This skill shows how to handle errors gracefully during filtering, caching, and sanitization so users understand what failed and why.

Do I need to validate data before filtering it for token reduction?

Yes. Validation ensures filtered results are accurate and safe. This template includes error handling and boundary checks to verify data integrity before caching or returning summaries, maintaining deterministic output.