跳到正文
FunCoding

搜索

搜索文档、Skill 和 MCP

app-store-optimization

Improves visibility and conversion in the App Store and Google Play — metadata, keywords, screenshots, ratings, and the listing experience that turns an impression into an install. Use this to audit or optimize an app listing, plan a launch listing, diagnose poor install conversion, or improve store search visibility.

AI 与智能体2kplugins/demand-generation/skills/app-store-optimization/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/cbrock84/headcount/app-store-optimization/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

App store optimization

Two levers, and they are separate problems: being found, and being installed once found. Diagnose which is failing before changing anything.

Being found

The stores index different fields, so the same metadata does not work on both.

  • App name / title — the single heaviest field. Brand plus the primary descriptive term. Do not spend it on brand alone.
  • Subtitle and keyword field — no repetition across fields; duplicated terms are wasted characters, not reinforcement.
  • Long description — indexed on one store, effectively not on the other. Write it for the store that indexes it and for humans on the store that does not.
  • Category — pick where you can rank, not where you technically belong.

Target terms with real intent. Ranking first for a term nobody searches is a vanity result.

Being installed

Most visitors decide from the first screenshot and the rating, without scrolling or reading.

  • Screenshots — the first two carry the decision. Lead with the outcome or the core screen, with a caption stating the benefit. Never lead with an onboarding or login screen.
  • Icon — recognizable at actual size, distinct from category conventions. Test at real scale on a device.
  • Rating — the strongest single conversion factor. Prompt for review after a success moment, never on launch or mid-task.
  • Video — only if it demonstrates something a screenshot cannot. A weak one costs installs.

Reviews

Respond to negative reviews specifically and without defensiveness, naming the fix and its version where there is one. Prospects read the responses as much as the complaints, and a pattern of real answers converts.

Watch review text for recurring themes — it is the cheapest continuous product research available.

Testing

Change one element at a time and let it run a full weekly cycle; app traffic is strongly day-of-week seasonal. Attributing a lift to the wrong change is worse than not testing.

Sources

references/sources.md in this skill lists the outside authorities that settle the questions here — what each one is authoritative for, and what you may do with it. Check them before answering on anything they cover, and cite what you used. Most are free to read and not free to reproduce; the use note on each is binding.

Tooling

The consoles are the source of truth: App Store Connect and Google Play Console, including their own experiment features — product page optimization and store listing experiments — which test on real store traffic rather than a simulation.

Keyword and competitor research: AppTweak, Sensor Tower, data.ai, AppFollow, and similar. Treat their volume estimates as directional; the stores do not publish the underlying numbers.

Review management and reply workflows live in the consoles or in the same tools, and replying is the part most teams skip.

Never

  • Chase a keyword the app does not deliver on. Installs from a mismatched query become one-star reviews and a worse ranking than you started with.
  • Change metadata, screenshots, and the icon in the same release. Nothing that moves afterward can be attributed.
  • Solicit ratings from a user mid-task. The prompt lands where frustration is highest and the score reflects that.
  • Ignore reviews on the version you just shipped. They are the fastest signal you will get that a release broke something.

相似的 Skill

brand-guidelines
anthropics/skills180k

brand-guidelines

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

AI 与智能体

internal-comms
anthropics/skills180k

internal-comms

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

AI 与智能体

template-skill
anthropics/skills180k

template-skill

Replace with description of the skill and when Claude should use it.

AI 与智能体

mcp-builder
anthropics/skills180k

mcp-builder

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

AI 与智能体

algorithmic-art
anthropics/skills180k

algorithmic-art

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

AI 与智能体

academy-guide
anthropics/skills180k

academy-guide

Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

AI 与智能体