| name | web-summary |
| description | Summarise a single web page or YouTube video into short/medium/long notes and extract semantic topic links for Logseq or Obsidian. Trigger when the user says "summarise this URL/article/video", "get the YouTube transcript", "pull the key points from this page", or "make Logseq/Obsidian topic links from this". Runs an MCP FastMCP server that scrapes the URL and summarises via the Ontology Loom facade (model-swappable LLM door). NOT for interactive browser automation (use browser/playwright), NOT for multi-URL comparison or structured extraction (use web-researcher scrape_page or the browser sidecar), NOT for broad multi-source cited web search (use perplexity-research/web-researcher), and NOT for text you already hold locally (summarise it directly).
|
| version | 2.1.0 |
| author | agentbox-claude |
| mcp_server | true |
| protocol | fastmcp |
| entry_point | mcp-server/server.py |
| dependencies | ["httpx","youtube-transcript-api"] |
Web Summary Skill
Single-URL content summarisation and topic extraction via a FastMCP server. It
fetches the page (or YouTube transcript) and summarises it through the Ontology
Loom facade — the load-bearing, model-swappable LLM door (agentbox ADR-051). The
former Z.AI service on port 9600 is retired; see references/architecture.md.
When to use
- Summarise one web article, blog post, or documentation page
- Extract and summarise a YouTube video transcript
- Generate semantic topic links for note-taking (Logseq, Obsidian)
- Produce short, medium, or long summaries; extract key concepts from text
When not to use
- Interactive browser automation (clicking, filling forms, live scraping) — use the
browser or playwright skills.
- Multi-URL comparison or structured data extraction from URLs — use
web-researcher (scrape_page / search_and_scrape) or the browser sidecar for JS-rendered pages.
- Broad, multi-source web search with citations — use
perplexity-research or web-researcher.
- Content you already have as local text — summarise it directly without this pipeline.
Tools
| Tool | Description |
|---|
summarize_url | Summarise content from any single URL (web or YouTube) |
youtube_transcript | Extract full transcript from a YouTube video |
generate_topics | Generate semantic topic links from text |
health_check | Verify Ontology Loom facade connectivity |
Examples
summarize_url({
"url": "https://example.com/article",
"length": "medium",
"include_topics": True,
"format": "logseq"
})
youtube_transcript({: , : })
generate_topics({: , : , : })
