add

Fetch source URLs and save content into raw/ subdirectories with YAML frontmatter.

1|Updated Apr 7, 2026
One-click install
npx skills add https://github.com/tommy-fcy/labwiki --skill add-tommy-fcy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: add
Source: https://github.com/tommy-fcy/labwiki/tree/main/.claude/skills/add
Command: npx skills add https://github.com/tommy-fcy/labwiki --skill add-tommy-fcy

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the process of fetching external sources and storing them into the appropriate raw/ subdirectory without performing any summarization or wiki processing.

Core Features & Use Cases

  • Zero-token downloads: Downloads are performed by an external script (tools/fetch.py) or fallbacks, leaving no LLM tokens used.
  • Structured storage: Automatically saves fetched content into raw/papers, raw/refs, or raw/experiments with YAML frontmatter.
  • Use Case: Collect research papers, notes, or web content into the wiki's raw storage for later ingestion.

Quick Start

Provide a URL and have the AI fetch it into the appropriate raw/ subdirectory using fetch.py.

Frequently Asked Questions about add

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

FAQPage Schema
How do I fetch web content into raw storage without using LLM tokens?▼

To fetch web content into raw storage with zero-token downloads, the Skill delegates the retrieval to an external script (fetch.py), saving the file directly into a raw/ subdirectory without consuming LLM tokens for the download process.

What is the best way to automatically save fetched papers and references with metadata?▼

Automatically saving fetched papers and references with metadata is handled by storing files under raw/papers or raw/refs and injecting YAML frontmatter containing source_url, type, title, and captured_at fields.

Can I use fetch.py to collect research papers for later ingestion into a wiki?▼

Yes, you can use fetch.py to collect research papers, notes, or web content into the wiki's raw storage directories for later ingestion, organizing them into raw/papers, raw/refs, or raw/experiments as appropriate.

Does the fetch process perform summarization or wiki processing on downloaded content?▼

No, the fetch process does not perform summarization or wiki processing; it strictly automates fetching external sources and storing them into the appropriate raw/ subdirectory in their original raw format.

What types of source URLs can I download into the raw experiments subdirectory?▼

You can download source URLs for papers, notes, experiments, and web content into the raw experiments subdirectory. The Skill evaluates the source and routes the file into raw/papers, raw/refs, or raw/experiments as appropriate.