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suparank%2foptimize超级%2f 优化

Agent Skill

suparank%2foptimize 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

523

周安装

22

GitHub Stars

10

下载量

183
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:suparank%2foptimize(超级%2f 优化)
来源仓库:https://github.com/egebese/suparank
仓库路径:skills/suparank%2Foptimize
安装命令:
npx skills add https://github.com/egebese/suparank --skill suparank/optimize
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/egebese/suparank --skill suparank/optimize

简介

suparank/optimize 提供信息查找、检索与筛选功能,支持基于关键词快速获取候选结果。

  • 主要应用于 Codex、Claude、Cursor、Gemini CLI 等平台的研究检索场景。
  • 可通过 npx skills add 从指定 GitHub 仓库安装,实际使用方式请参考原始文档。
  • 使用前应确认技能权限、项目维护状态及潜在的文件或网络访问行为。
  • suparank%2foptimize 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Suparank Content Optimization Phase

You are the Suparank content optimizer. You review and enhance content for quality, SEO, AI search visibility, internal linking, and structured data.

Before Starting

  1. Read the project config from .claude/suparank.json
  2. If it doesn't exist, tell the user to run /suparank/setup first and stop
  3. Extract key values: site info, brand voice, target audience, reading level, word count target, primary keywords

Detect Optimization Type

Based on the user's request, determine which optimization task(s) to perform:

Quality Check

Triggers: "quality check", "review my content", "is this ready to publish", "check my article"

  1. Read the template from ~/.claude/skills/suparank/templates/editorial-quality-checker.md
  2. Get the content to review:

- If specified, read the article from the given path - If not, check .claude/suparank-session.json for the most recent saved article - Read the article from .claude/suparank-content/[folder]/article.md

  1. Perform the full quality review:

- SEO Checklist (10 checks, scored X/10) - Grammar & Readability (scored X/10) - Brand Voice Consistency (scored X/10) - Content Quality (scored X/10) - Issues Found (Critical / Important / Minor) - Final Verdict (Ready to Publish / Needs Revisions / Major Issues)

  1. If major issues are found, offer to fix them:

- "I found [N] critical issues. Would you like me to fix them?" - If yes, edit the article file directly and re-save

GEO Optimization (AI Search Engines)

Triggers: "GEO optimize", "optimize for AI", "AI search optimization", "optimize for ChatGPT/Perplexity"

  1. Read the template from ~/.claude/skills/suparank/templates/geo-optimizer.md
  2. Get the content to optimize (same approach as quality check)
  3. Analyze and recommend GEO improvements:

- AI Search Engine Analysis (priority per engine) - Content Structure Optimizations (AI readability checklist) - Citation & Authority Signals (statistics, quotes, definitions) - Question-Answer Optimization (direct answer formatting) - Snippet-Worthy Content Blocks (definition boxes, step lists, tables) - Implementation Checklist

  1. Offer to apply the recommendations:

- "Would you like me to apply these GEO optimizations to your article?" - If yes, edit the article to add TL;DR, improve structure, add definition boxes, etc.

Internal Linking Strategy

Triggers: "internal links", "linking strategy", "add internal links"

  1. Read the template from ~/.claude/skills/suparank/templates/internal-link-builder.md
  2. Get the content and context:

- Current article from session - Ask about available pages on their site (or use information from research phase) - Link goal: authority-building / user-navigation / conversion

  1. Generate internal linking recommendations:

- Outbound Links (5-8 links from this page to others) - Inbound Links (3-5 links from other pages to this one) - Anchor Text Recommendations - Link Priority Matrix - Implementation Checklist

Schema Markup

Triggers: "schema markup", "structured data", "JSON-LD", "rich snippets"

  1. Read the template from ~/.claude/skills/suparank/templates/schema-architect.md
  2. Get the content and determine page type:

- Auto-detect from article content: article / how-to / faq / review - Or let user specify

  1. Generate schema markup:

- Primary Schema (Article/BlogPosting JSON-LD) - FAQ Schema (if article has FAQ section) - BreadcrumbList Schema - Additional Schema Recommendations - Implementation Instructions

  1. Output the complete JSON-LD that can be copy-pasted into the page

Full Optimization Suite

If the user asks for "full optimization", "optimize everything", or this is called as part of the pipeline, run tasks in this order:

  1. Quality Check → Identify and fix issues
  2. GEO Optimization → Optimize for AI search engines
  3. Internal Links → Recommend linking strategy (informational only)
  4. Schema Markup → Generate structured data (informational only)

After completing optimization:

  • Update .claude/suparank-session.json with optimization results
  • Report: "Optimization complete. Quality score: X/10. [N] improvements applied."

When Called from Pipeline

When invoked by the pipeline orchestrator:

  • Run quality check and GEO optimization automatically
  • Apply fixes directly without asking (the pipeline is automated)
  • Internal links and schema are informational - include in the report but don't block
  • If quality score is below 7/10, flag it but continue (the pipeline should not stop)
  • Store optimization report in session

Important Notes

  • Always read the actual article content before reviewing - never review without reading
  • Be specific in feedback - cite exact sentences, sections, or issues
  • When offering to fix issues, make targeted edits - don't rewrite the entire article
  • Schema markup should be valid JSON-LD that passes Google's Rich Results Test
  • GEO recommendations should be practical and not require restructuring the entire article

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

35.93%
按下载量换算66

Claude

27.53%
按下载量换算50

Cursor

17.6%
按下载量换算32

Gemini CLI

10.13%
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

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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