Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add geronimo-iia/agent-skills --skill summarizegit clone --depth 1 https://github.com/geronimo-iia/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/geronimo-iia/agent-skills/summarize)<a href="https://agentmods.dev/skills/geronimo-iia/agent-skills/summarize"><img src="https://agentmods.dev/badge/skills/geronimo-iia/agent-skills/summarize/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/geronimo-iia/agent-skills/summarize"><img src="https://agentmods.dev/badge/skills/geronimo-iia/agent-skills/summarize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00063 | $0.00954 |
| Opus 5.5 | $0.00025 | $0.00382 |
| Sonnet 5.5 | $0.00013 | $0.00191 |
| Haiku 4.5 | $0.00006 | $0.00095 |
Grade A, and why
summarize scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://r.jina.ai/https://example.com" | llm "summarize this" How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Summarize
Composable pipeline for summarizing web pages, documents, audio, and video. Mix and match tools based on input type and model preference.
Install
llm needs a persistent install so plugins survive between calls:
uv tool install llm
llm install llm-ollama # optional: local models via Ollama
brew install steipete/tap/summarize # optional: all-in-one CLI alternative
markitdown and fabric work as one-shot uvx calls — no permanent install needed.
Quick start by input type
URL → summary
# Jina Reader: zero-install, returns clean markdown
curl -s "https://r.jina.ai/https://example.com" | llm "summarize this"
# With a specific model
curl -s "https://r.jina.ai/https://example.com" | llm -m claude-opus-5 "summarize"
PDF / Word / PPTX / HTML → summary
uvx markitdown file.pdf | llm "summarize"
uvx markitdown file.docx | llm "summarize"
YouTube / audio → summary
# Via summarize CLI (handles transcription)
summarize "https://youtu.be/<id>" --youtube auto
# Local: yt-dlp + whisper pipeline
yt-dlp -x --audio-format mp3 -o /tmp/audio.mp3 "https://youtu.be/<id>"
uvx openai-whisper /tmp/audio.mp3 --output_format txt
llm "summarize" < /tmp/audio.txt
Stdin / arbitrary text
cat notes.txt | llm "summarize"
echo "long text..." | llm -m ollama/llama3.2 "summarize in 3 bullets"
llm — model selection
llm models # list available models
llm -m claude-opus-5 "..." # Anthropic (needs ANTHROPIC_API_KEY)
llm -m gpt-4o "..." # OpenAI (needs OPENAI_API_KEY)
llm -m ollama/llama3.2 "..." # local via Ollama (no key needed)
llm -m gemini-1.5-flash "..." # Google (needs GEMINI_API_KEY)
Set default model once:
llm models default claude-sonnet-5
fabric — opinionated extraction patterns
Useful when you want structured extraction, not just a summary:
uvx fabric --pattern summarize < input.txt
curl -s "https://r.jina.ai/https://example.com" | uvx fabric --pattern extract_wisdom
curl -s "https://r.jina.ai/https://example.com" | uvx fabric --pattern extract_ideas
uvx fabric --list # see all available patterns
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 112 lines · 63 tokens per session scan A 6e20fa73903c
summarize is a skill published in the GitHub repository geronimo-iia/agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 954 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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