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待分类只读github未标认证来源可访问许可证需确认审计通过

titletitle 命令行

Agent Skill

title 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

1,346

周安装

55

GitHub Stars

124

下载量

436
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:title(title 命令行)
来源仓库:https://github.com/kenneth-liao/ai-launchpad-marketplace
仓库路径:skills/title
安装命令:
npx skills add https://github.com/kenneth-liao/ai-launchpad-marketplace --skill title
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/kenneth-liao/ai-launchpad-marketplace --skill title

简介

title 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 确认具体用法。
  • 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操作。
  • title 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Title Generation

Overview

This skill generates high-performing titles and headlines optimized for engagement across any content type. Titles are designed to spark curiosity, complement visual assets where applicable, and compel the audience to click, open, or engage.

Core Principle: Every title must prompt a specific question in the audience's mind. Description alone is insufficient — curiosity is non-negotiable.

When to Use

Use this skill when:

  • The user asks to create a title, headline, or subject line
  • The user requests title ideas or brainstorming for content
  • The user wants to improve or optimize an existing title
  • Working on content creation and a title is needed
  • The user asks for multiple title variations to test

Content Type Resolution

Before generating titles, determine the content type and load the appropriate platform-specific reference file:

Content TypeReference FileKey Focus
YouTube videoreferences/youtube-title-formulas.mdCTR, curiosity, thumbnail complementarity
Newsletter / emailreferences/newsletter-subject-lines.mdOpen rate, preview text, inbox competition
Social media postreferences/social-headlines.mdScroll-stopping, platform-specific hooks

Essential: Read the relevant reference file before generating titles — each platform has unique patterns and constraints that directly affect performance, and skipping this step leads to generic titles that underperform.

If the content type does not match any reference file, apply the universal principles below and adapt to the format.

Prerequisites

Gather Context

Before generating titles, gather the following information from conversation context, the user's filesystem, or by asking the user directly.

Required Information:

  • Content topic: What is the content about?
  • Target audience: Who is this for?
  • Key message: What is the main takeaway or hook?

Highly Recommended Information:

  • Visual asset description: What does the thumbnail, header image, or preview show?
  • Target emotion: What emotion should the title evoke? (curiosity, shock, excitement, urgency)
  • Content type: Video, newsletter, social post, blog article, etc.

Title Generation Workflow

Step 1: Gather Context

Collect required information if not already provided. Ask the user for anything missing:

To create an optimized title, I need to understand:
1. What is the content about? (topic)
2. Who is your target audience?
3. What is the main hook or takeaway?
4. Do you have a visual asset (thumbnail, header image)? If so, what does it show?
5. What emotion should the title evoke?

Step 2: Load Platform Reference

Read the appropriate platform-specific reference file based on the content type identified in Step 1.

Step 3: Identify the Question

Before writing any title, identify the specific question you want in the audience's mind:

  • What question will make them curious enough to engage?
  • Does this question align with the content?
  • Is the curiosity gap strong enough to drive action?

Examples of effective questions to prompt:

  • "What mistakes am I making?" (mistake framing)
  • "What happened?" (outcome uncertainty)
  • "Why would someone do that?" (extreme behavior)
  • "How is that possible?" (surprising claim)

Step 4: Generate Title Options

Generate 3-5 title variations that:

  1. Prompt the identified question
  2. Complement (not duplicate) any visual assets
  3. Align with the target emotion
  4. Follow platform-specific best practices from the reference file

Step 5: Verify Against Checklist

For each title, verify against the universal checklist:

  • Curiosity Test: Does this prompt a specific question?
  • Complementarity Test: Does this work WITH visual assets (not duplicate them)?
  • Click/Open Compulsion Test: Is the curiosity gap strong enough?
  • Non-Descriptive Test: Does this go beyond merely describing content?
  • Target Audience Test: Will this resonate with the intended audience?

Step 6: Present and Refine

Present title options to the user with:

  1. The title itself
  2. The question it prompts in the audience's mind
  3. How it complements the visual asset (if applicable)
  4. Why it should drive engagement

Example presentation:

Here are 3 optimized title options:

1. "The AI Agent Mistake That Cost Me 10 Hours"
   - Prompts: "What mistake? How can I avoid it?"
   - Complements thumbnail showing frustrated face + error message
   - Creates urgency through time cost

2. "I Built This AI Agent Wrong (Here's What I Learned)"
   - Prompts: "What did they do wrong? What's the lesson?"
   - Personal experience framing creates relatability

3. "Why Your AI Agents Keep Breaking (And Mine Don't)"
   - Prompts: "Why do mine break? What's their secret?"
   - Creates contrast and curiosity

Step 7: Iterate Based on Feedback

If the user requests changes:

  1. Understand what aspect needs adjustment (curiosity, tone, length, etc.)
  2. Regenerate while maintaining checklist compliance
  3. Re-verify against the checklist

Voice Application

Before finalizing any written output, invoke the creator-stack:voice skill to apply voice rules. Titles should sound authentic to the user's voice, not generic.

Brand Compliance

When creating assets for The AI Launchpad, invoke creator-stack:brand-guidelines to resolve the correct design system and check anti-patterns.

Quality Assurance

Priority Order

  1. Spark curiosity (highest priority)
  2. Complement visual asset
  3. Raise audience question
  4. Create click/open compulsion

Rejection Criteria

Regenerate if the title:

  • Merely describes the content without sparking curiosity
  • Duplicates text that appears on the visual asset
  • Answers the question instead of raising it
  • Uses generic patterns without intrigue
  • Fails the "What question does this raise?" test

Success Criteria

A successful title:

  • Prompts a specific, compelling question in the audience's mind
  • Works synergistically with any visual asset
  • Creates a curiosity gap strong enough to drive engagement
  • Aligns with the target audience and content type
  • Passes all 5 universal checklist items

Common Pitfalls

  1. Generic Description: "AI Agents Tutorial" describes but does not intrigue. Add curiosity.
  2. Answering the Question: "How to Fix AI Agent Memory in 3 Steps" gives away too much. Tease, do not tell.
  3. Ignoring Platform: A YouTube title and a newsletter subject line have different constraints. Load the right reference.
  4. Thumbnail/Asset Duplication: If the thumbnail says "BROKEN", the title should not also say "broken." Complement, do not repeat.
  5. Single Option: Always provide 3-5 variations for the user to choose from.

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

能力 4

展示第三方安全扫描或审计结果

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

34.14%
按下载量换算149

Claude

29.68%
按下载量换算129

Cursor

17.94%
按下载量换算78

Gemini CLI

10.77%
按下载量换算47

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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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