Borrowing it
Nothing to install: this file belongs to zhouguoqing/QianYuan.AIAgenticFramework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zhouguoqing/QianYuan.AIAgenticFramework/main/.agents/skills/summarize/SKILL.mdgit clone --depth 1 https://github.com/zhouguoqing/QianYuan.AIAgenticFrameworkWrote 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/zhouguoqing/qianyuan.aiagenticframework/summarize)<a href="https://agentmods.dev/skills/zhouguoqing/qianyuan.aiagenticframework/summarize"><img src="https://agentmods.dev/badge/skills/zhouguoqing/qianyuan.aiagenticframework/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/zhouguoqing/qianyuan.aiagenticframework/summarize"><img src="https://agentmods.dev/badge/skills/zhouguoqing/qianyuan.aiagenticframework/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 | $0.00072 | $0.00608 |
| Opus 5.5 | $0.00029 | $0.00243 |
| Sonnet 5.5 | $0.00014 | $0.00122 |
| Haiku 4.5 | $0.00007 | $0.00061 |
Grade A, and why
summarize scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Summarize CLI
Use this skill to run summarize effectively in terminal workflows.
Focus on practical usage and command execution, not broad project background.
Workflow
- Confirm input type and desired output format.
- Run a minimal real command first (
summarize "<input>"). - Select a model/provider and ensure matching API credentials.
- Add flags incrementally only after a baseline run succeeds.
- If it fails, re-run with
--verboseor--jsonbefore changing multiple variables.
Quick Patterns
- Summarize a URL:
summarize "https://example.com" - Summarize a local file:
summarize "/path/to/file.pdf" - Summarize piped input:
cat notes.md | summarize - - Summarize YouTube/media URL:
summarize "https://youtube.com/watch?v=..." - Force model/provider:
summarize "https://example.com" --model openai/gpt-5-mini - Control length:
summarize "https://example.com" --length long - Return diagnostics JSON:
summarize "https://example.com" --json - Extract content without summarizing:
summarize "https://example.com" --extract --format md
Configuration Rules
- Prefer explicit
--modelon task-critical runs. - Use
~/.summarize/config.jsonfor stable defaults. - Remember precedence for model selection:
--modelSUMMARIZE_MODEL~/.summarize/config.json- built-in default (
auto)
Troubleshooting Flow
- Re-run with
--verbose. - Confirm API key matches the chosen provider/model.
- Switch to a known-good model (for example
openai/gpt-5-miniorgoogle/gemini-3-flash-preview). - For media or YouTube failures, verify external dependencies (
yt-dlp,ffmpeg, optionallytesseract). - Use
--jsonto inspect extraction and metric fields.
Scope
- Prioritize how to run commands and fix concrete failures.
- Do not include full repository-level documentation unless explicitly requested.
- Use references/cli.md only for deeper flag/provider details.
References
Read references/cli.md for install commands, provider keys, advanced flags, and error-specific guidance.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 57 lines · 72 tokens per session scan A 44ebbaf806a9
summarize is a skill published in the GitHub repository zhouguoqing/QianYuan.AIAgenticFramework (37 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 608 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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