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 renky1025/agent-skills --skill infocardgit clone --depth 1 https://github.com/renky1025/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/renky1025/agent-skills/infocard)<a href="https://agentmods.dev/skills/renky1025/agent-skills/infocard"><img src="https://agentmods.dev/badge/skills/renky1025/agent-skills/infocard/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/renky1025/agent-skills/infocard"><img src="https://agentmods.dev/badge/skills/renky1025/agent-skills/infocard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 61 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00212 | $0.02919 |
| Opus 5.5 | $0.00085 | $0.01168 |
| Sonnet 5.5 | $0.00042 | $0.00584 |
| Haiku 4.5 | $0.00021 | $0.00292 |
Grade A, and why
infocard 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 23d 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.
Exa MCP / Camoufox；通用用 `curl -s "https://r.jina.ai/<URL>"` 或 WebFetch。文本输入跳过本步。 How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
infocard: 智能信息卡片生成器
没有"默认布局"：先读懂内容，再让视觉形式从内容的思想形状中长出来。
Purpose
把 URL 或纯文本转成一张（或双语两张）可交付的信息卡片 PNG。技能不套固定模板，而是先理解原文的
思想形状（密度 / 结构 / 情绪），据此选择版式、配色与图形，再用无头浏览器按 .card 边界截图到
~/Downloads/infocard-img/。
When to Use
- 用户要把一篇文章 / 一条推文 / 一个链接 / 一段文本做成图片卡片。
- 用户要概念图、科普长图、金句卡、产品发布卡、版本对比卡、benchmark 数据卡。
- 触发词：信息卡片、知识卡片、概念图、科普长图、金句卡、发布卡、对比卡、做成卡片、卡片配图、 infocard、knowledge card、concept card、turn this article into an image card。
When NOT to Use
- 用户要咨询 / 研报 / PPT 封面质感 -> 交给
mckinsey-cover。 - 用户要摄影质感、写实、产品实拍图 -> 交给
image-design。 - 用户要工程化规格出图、透明底素材、UI 原型、角色一致性 -> 交给
spec-image。 - 用户只要文字摘要、明确不要图片 -> 直接回答，不要出图。
Workflow
- 解析输入：首个非
--的 token 为输入；http(s)://开头为 URL，否则为文本。参数取--theme/--width/--output/--lang，缺省见description，--output缺省时自动提取文件名。 - 获取内容：URL -> Twitter/X 用
twitter tweet <URL>；GitHub 用gh或 Jina；微信公众号用 Exa MCP / Camoufox；通用用curl -s "https://r.jina.ai/<URL>"或 WebFetch。文本输入跳过本步。 - 提取元信息并定模式：标题(≤15 字)、副标题(≤30 字)、来源、核心要点、金句(<25 字)、数据； 归入概念解说 / 金句 / 密集知识三类模式之一。
- 三维判断（含内部自检）：定密度（留白）、结构（版式）、情绪（主题）；产品/对比类另列核心 优势、对比数值、规格参数；确认密度 / 结构 / 情绪 / 锚点 / 配色互相自洽。
- 选主题与版式：按
## Decision Rules选定--theme，再读该主题的布局规范。 - 语言：
auto按原文生成单语（中文占比 >50% 判中文）；zh/en/both跨语言时必须走/translate-polisher，严禁直译；术语/品牌名（Claude Code、HTML、MCP…）与难译短语 （one-shot、intent alignment）保留英文。 - 生成 HTML：遵守
## Constraints的骨架与硬规则。单语写/tmp/infocard_{name}.html； 双语先译后写，分别_zh.html/_en.html。 - 截图：按
## Scripts的 capture.js 调用方式执行。 - 展示：用
present_files展示生成的 PNG。
Decision Rules
--theme 缺省 = editorial。长文/专访/报告/知识图谱 -> editorial；产品/模型发布、版本对比、
benchmark -> dashboard；科普、概念解析、知识长图、方法论图解 -> knowledge；其余按情绪映射
（沉思 -> slate/indigo，锐利 -> coral/sunset，温暖/科研 -> forest，技术 -> purple，
优雅 -> guofeng）。完整对照表见 references/content-modes.md。
- 主题已定 -> 只读
references/theme-palettes.md中对应那一节，取 CSS 变量原值。 - 主题为
editorial（默认）-> 读references/editorial-layout.md。 - 主题为
dashboard-> 读references/dashboard-layout.md。 - 主题为
knowledge-> 读references/knowledge-layout.md。 - 判定内容模式、密度与结构 -> 读
references/content-modes.md。 - 生成 HTML 需要图标 -> 读
references/svg-icon-sprite.md取<symbol>与图标映射。 - 用户想预览主题配色 -> 展示
assets/theme_colorcards.png；需要卡片骨架 -> 参考assets/template.html（legacy，body 含padding/100vh，capture.js 会清除；只借结构与配色）。
What ships with it
13 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.
- assets/template.html 26 KB
- assets/theme_colorcards.png 283 KB
- package-lock.json 1.7 KB
- package.json 175 B
- references/content-modes.md 2.0 KB
- references/dashboard-layout.md 560 B
- references/editorial-layout.md 843 B
- references/knowledge-layout.md 3.9 KB
- references/svg-icon-sprite.md 5.4 KB
- references/theme-palettes.md 2.4 KB
- scripts/capture_dsh.js 2.0 KB runs code
- scripts/capture.js 6.8 KB runs code
- skills-lock.json 9.3 KB
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.
- 23d ago Changed · -73 lines · +95 tokens per session 4d7744145ff8
- 1mo ago First seen · 224 lines · 117 tokens per session scan A 6e86e0f13a7a
infocard is a skill published in the GitHub repository renky1025/agent-skills (11 stars, last pushed 7d ago), licensed MIT. It adds 212 tokens to every session and 2,919 once invoked, about $0.0008 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 2026-08-31.
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