summarize
Skill1 starsChanged 8 months agoMITView on GitHub
Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).
- Reads credentials
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 66 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 31
Use this skill immediately when the user asks any of:
- Distinctive: line 54
If the user asked for a transcript but it’s huge, return a tight summary first, then ask which section/time range to expand.
- Very specific: line 65
Default model is google/gemini-3-flash-preview if none is set.
“Common” is measured: kept by at least 6 in 10 of the 66 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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)
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 autoYouTube: 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
Other versions89 projects use a version of this.
Word for word · 11
- casibase/casibase★ 5.7k100% same
- the-open-agent/openagent★ 5.7k100% same
- linuxhsj/openclaw-zero-token★ 5.2k100% same
- OpenBMB/EdgeClaw★ 1.2k100% same
- AtomicBot-ai/atomicbot★ 325100% same
- cohen-liel/hivemind★ 108100% same
- TermiX-official/cryptoclaw★ 100100% same
- yunze7373/openclaw-termux★ 2100% same
- AnasNafees1802/BabyClaw★ 1100% same
- jpoindexter/theft-kit★ 1100% same
1 more not listed
Edited · 30
- moltbot/moltbot★ 393k81% same
- clawdbot/clawdbot★ 393k81% same
- steipete/warelay★ 392k81% same
- moltbot/clawdbot★ 392k81% same
- steipete/clawdis★ 392k81% same
- molt-bot/clawdbot★ 391k81% same
- openclaw/openclaw★ 391k81% same
- spinabot/brigade★ 11k98% same
- OpenBMB/PilotDeck★ 4.5k68% same
- Bitterbot-AI/bitterbot-desktop★ 2.5k98% same
20 more not listed
Wrote their own version · 48
- steipete/summarize★ 6.7ksame name
- mitsuhiko/agent-commands★ 3.2ksame name
- mitsuhiko/agent-stuff★ 3.2ksame name
- RTGS2017/NagaAgent★ 1.5ksame name
- Xxiii8322766509/NagaAgent★ 1.5ksame name
- cashew-labs/libretto★ 898same name
- saffron-health/libretto★ 883same name
- cyrusagents/cyrus★ 868same name
- ceedaragents/cyrus★ 856same name
- SerhiiKorniienko/bullshit-detector★ 151same name
38 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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In this repository59 other files it gives its agents.
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