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lovstudio%3afind-logolovstudio%3a 查找徽标

Agent Skill

lovstudio%3afind-logo 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

588

周安装

25

GitHub Stars

45

下载量

206
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:lovstudio%3afind-logo(lovstudio%3a 查找徽标)
来源仓库:https://github.com/lovstudio/skills
仓库路径:skills/lovstudio%3Afind-logo
安装命令:
npx skills add https://github.com/lovstudio/skills --skill lovstudio:find-logo
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/lovstudio/skills --skill lovstudio:find-logo

简介

lovstudio%3afind-logo 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用该技能。
  • 安装前需确认权限范围和维护状态,注意可能触发联网、命令执行或文件读写操作。
  • 建议结合原始 README 和仓库内容进一步核验具体功能和用法边界。

SKILL.md

find-logo — collect brand logos, prefer wide + transparent

Takes a brand name or URL, probes Clearbit + the site's own og:image / <link rel=icon> / favicon, scores each candidate, and archives the best one plus a couple of alternates into ~/.lovstudio/logo-collection/<slug>/.

When to Use

  • User asks to collect one or more brand logos for a slide/poster/site lineup
  • User names companies to drop into a partners/press strip
  • User gives a URL and wants its logo pulled down cleanly

Workflow (MANDATORY)

Step 1: Identify each brand

Accept any mix of names and URLs. If the user gave only a name with no obvious domain, ask — don't silently guess .com (script will guess, but for non-US or ambiguous brands that fails).

Use AskUserQuestion when:

  • Brand name is ambiguous (e.g. "Apple" = fruit vs. Inc.)
  • No URL and the domain isn't guessable (xAIx.ai, not xai.com)
  • User gave a list without URLs

Step 2: Fetch — one brand per invocation

python3 ~/.claude/skills/lovstudio-find-logo/scripts/find_logo.py \
  --name "Anthropic" --url https://anthropic.com --json

For a batch, loop; the script is idempotent per <slug>/ (re-runs overwrite).

Step 3: Inspect score; fall back to WebSearch if needed

  • Exit code 0 → logo archived. The printed score is your quality signal:

- ≥ 60 — solid: SVG or transparent PNG with wide/square aspect - 20–60 — usable: probably a favicon or small PNG - < 20 — weak: only ICO or tiny stub found

  • Exit code 2 / status: "no-candidates" → script found nothing. Do NOT give up. Use WebSearch for "<brand> logo svg site:*.com" or the brand's press-kit page, then re-invoke with --url <direct-image-url> is not supported — if you have a direct image URL, curl -o it into ~/.lovstudio/logo-collection/<slug>/logo.<ext> and hand-write meta.json using the existing layout as a template.

Step 4: Report

Report back with the archive path and the primary's aspect + format. If the score is weak, tell the user and offer to retry with a specific press-kit URL or Wikipedia SVG.

CLI Reference

ArgumentDefaultDescription
--nameBrand/product name. Used for slug + meta.
--urlOfficial URL or bare domain. Overrides the name-based domain guess.
--slugslugified nameOverride the directory slug under the archive root.
--out~/.lovstudio/logo-collectionArchive root.
--keep-alts2How many runner-up candidates to keep as alt-N.<ext>.
--jsonoffEmit a JSON result to stdout (use this when chaining).

At least one of --name or --url is required.

Archive Layout

~/.lovstudio/logo-collection/
├── anthropic/
│   ├── logo.png            # primary (highest score)
│   ├── alt-1.png           # runner-ups
│   ├── alt-2.png
│   └── meta.json           # sources, scores, dimensions, fetched_at
├── vercel/
│   ├── logo.png            # 1200x628 transparent banner
│   └── ...
└── stripe/
    ├── logo.svg
    └── ...

Scoring Heuristic (why a candidate wins)

  • Format: SVG (+40) > PNG (+20) > WebP (+10) > JPG (-10) > ICO (-20)
  • Transparency: +30 if alpha channel present (SVG always counts)
  • Aspect ratio: +25 for wide (≥2:1), +10 for landscape (≥1.3:1), -5 for square, -15 for tall/portrait
  • Short edge: +15 if ≥128px, +5 if ≥64px, -20 if <32px
  • Size sanity: -30 if payload <400 bytes (almost certainly a stub)

This matches the "prefer 长条形 + rgba" preference — wide transparent logos come out on top, square favicons land as alternates.

Dependencies

Stdlib only (urllib, html.parser, argparse). No pip install required.

Known Limits

  • The name → domain guess is a crude lowercase-strip + .com suffix. For anything not on .com, pass --url explicitly.
  • No Clearbit API key is used — we hit the unauthenticated endpoint, which covers most major brands but not all.
  • WebSearch fallback is Claude's responsibility, not the script's.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.9%
按下载量换算70

Claude

30.94%
按下载量换算64

Cursor

19.03%
按下载量换算39

Gemini CLI

9.37%
按下载量换算19

安全审计

暂无安全审计结果可展示。

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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