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 l3gi0nXXXX/Metis-agent --skill summarizegit clone --depth 1 https://github.com/l3gi0nXXXX/Metis-agentWrote 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/l3gi0nxxxx/metis-agent/summarize)<a href="https://agentmods.dev/skills/l3gi0nxxxx/metis-agent/summarize"><img src="https://agentmods.dev/badge/skills/l3gi0nxxxx/metis-agent/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/l3gi0nxxxx/metis-agent/summarize"><img src="https://agentmods.dev/badge/skills/l3gi0nxxxx/metis-agent/summarize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00032 | $0.01281 |
| Opus 5 | $0.00016 | $0.00641 |
| Sonnet 5 | $0.00006 | $0.00256 |
| Haiku 4.5 | $0.00003 | $0.00128 |
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 10d 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.
- **不要默认用 Shell 执行本页中的 bash 示例。** 在 Windows 上 Shell 往往会落到 PowerShell/CMD,与 bash 的引号、管道、`|` 重定向等语义不一致,容易误触发 `curl`/`Invoke-WebRequest` 或解析失败。 How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Summarize
Fast CLI to summarize URLs, local files, and YouTube links.
Metis / magic-cli(必读)
- 不要默认用 Shell 执行本页中的 bash 示例。 在 Windows 上 Shell 往往会落到 PowerShell/CMD,与 bash 的引号、管道、
|重定向等语义不一致,容易误触发curl/Invoke-WebRequest或解析失败。 - Windows:禁止用 Shell 跑
curl抓网页。 在 PowerShell 里curl常是Invoke-WebRequest的别名,会出现Supply values for the following parameters: Uri:等交互式提示,自动化会卡死;与「用 summarize 拉 URL」无关时也不要用curl凑合。 summarize未安装 / 提示 “not recognized” 时:不要反复用 Shell 调summarize或假定 PATH 已有。应:说明需先安装并把可执行文件加入 PATH(见 summarize.sh);对 URL 摘要:请用户复制页面正文到对话、或导出为本地文件后用 读文件 工具;若环境提供 网页抓取 / MCP fetch(非 Shell),可用其拉取后再由模型总结。不要因缺 CLI 就改用curl。- 优先顺序(在 CLI / 网关里):
- 本地文件:先用内置 读文件 能力(如
read_file/ 工作区文件工具)把正文读入,再由模型做摘要或抽取;不要为了「走 summarize CLI」而先开 Shell。 - URL / YouTube:仅当已确认本机存在
summarize(如用户说明已装,或你先说明风险后用户同意执行)再用 CLI;命令写成 单行,路径与引号按 CMD 或当前 Shell 规则,不要假设存在bash。 - 仍缺工具时:说明限制并建议用户在 本机独立终端(已配置好
summarize与 PATH)中自行运行下方示例,而不是在代理里反复试 Shell。
- 本地文件:先用内置 读文件 能力(如
- 下列
bash代码块仅作 参考 与 非 Metis 环境 下使用;在本仓库交互中 不 将其当作首选执行方式。
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)
若无法使用 summarize CLI(尤其 Windows)
- 先说明:本机未安装或不在 PATH 时,不要继续用 Shell 调
summarize。 - URL 摘要:请用户粘贴页面正文到对话,或保存为本地文件后走 读文件;若 IDE/环境提供 非 Shell 的网页/MCP 获取,可用之,再由模型归纳(勿用 Shell
curl)。 - 华为开发者等文档站:同样适用;禁止用
curl在 PowerShell 里硬拉以免卡在Uri:交互。
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 auto
YouTube: summary vs transcript
Best-effort transcript (URLs only):
summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto --extract-only
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.
- 10d ago First seen · 104 lines · 32 tokens per session scan A 42a75d3fe19e
summarize is a skill published in the GitHub repository l3gi0nXXXX/Metis-agent (129 stars, last pushed 2d ago), licensed MIT. It adds 32 tokens to every session and 1,281 once invoked, about $0.0002 per session on Opus 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 2026-08-30.
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