
summarize
★ 3by firecrawl · part of firecrawl/openclaw
Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).
This is the playbook your agent receives when the skill activates — you don't need to read it to use the skill, but it's here to audit before installing.
Summarize
Fast CLI to summarize URLs, local files, and YouTube links.
When to use (trigger phrases)
Use this skill immediately when the user asks any of:
- “use summarize.sh”
- “what’s this link/video about?”
- “summarize this URL/article”
- “transcribe this YouTube/video” (best-effort transcript extraction; no
yt-dlpneeded)
YouTube: summary vs transcript
Best-effort transcript (URLs only):
summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto --extract-onlyIf the user asked for a transcript but it’s huge, return a tight summary first, then ask which section/time range to expand.
Model + keys
Set the API key for your chosen provider:
- OpenAI:
OPENAI_API_KEY - Anthropic:
ANTHROPIC_API_KEY - xAI:
XAI_API_KEY - Google:
GEMINI_API_KEY(aliases:GOOGLE_GENERATIVE_AI_API_KEY,GOOGLE_API_KEY)
Default model is google/gemini-3-flash-preview if none is set.
Useful flags
--length short|medium|long|xl|xxl|<chars>--max-output-tokens <count>--extract-only(URLs only)--json(machine readable)--firecrawl auto|off|always(fallback extraction)--youtube auto(Apify fallback ifAPIFY_API_TOKENset)
Config
Optional config file: ~/.summarize/config.json
{ "model": "openai/gpt-5.2" }Optional services:
FIRECRAWL_API_KEYfor blocked sitesAPIFY_API_TOKENfor YouTube fallback
npx skills add firecrawl/openclaw --skill "summarize" --full-depthRun this in your project — your agent picks the skill up automatically.
Quick start
summarize "https://example.com" --model google/gemini-3-flash-preview
summarize "/path/to/file.pdf" --model google/gemini-3-flash-preview
summarize "https://youtu.be/dQw4w9WgXcQ" --youtube autoNo common issues documented yet. If you hit a problem, the repository's GitHub Issues page is the best place to look.
Licensed under MIT— you can use, modify, and redistribute it under that license's terms.
View the full license file on GitHub →