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Agent Skill · 研究检索

deepproduct(deepproduct 搜索)

deepproduct 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。

deepproduct 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 50,189。

总安装 624周安装 26GitHub Stars 1下载 208核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:deepproduct(deepproduct 搜索)
来源仓库:https://github.com/skinnyandbald/fish-skills
仓库路径:skills/deepproduct
安装命令:
npx skills add https://github.com/skinnyandbald/fish-skills --skill deepproduct
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/skinnyandbald/fish-skills --skill deepproduct

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

deepproduct 用于生成深度产品研究提示词,支持根据项目上下文定制调研方向。适用于需要分析用户流程、界面模式或特定功能设计的产品团队。通过参数化输入主题,自动构建结构化的研究问题清单和调研框架。使用前需确认项目背景信息,避免脱离实际场景生成无效建议。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/deepproduct

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/skinnyandbald/fish-skills --skill deepproduct;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

deepproduct 怎么安装?

在终端执行 npx skills add https://github.com/skinnyandbald/fish-skills --skill deepproduct。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

deepproduct 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

deepproduct 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

deepproduct 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

deepproduct 用的人多吗?

公开数据是累计安装 624 次,近一周安装 26 次,下载 208 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

deepproduct 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
deepproduct

deepproduct 搜索 · 本页

6241操作浏览器未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Deep Product Research Prompt Generator

Deep product analysis tool.

Arguments: $ARGUMENTS

Instructions

Generate a comprehensive deep research prompt for the product question "$ARGUMENTS" tailored to the current project's product context — its users, UI/UX patterns, domain, and existing design decisions.

If no topic is provided, ask the user what product question they want to research (e.g., onboarding flow, navigation patterns, empty states, pricing page, settings UX, notification design, search experience, mobile responsiveness).


Phase 1: Understand the Product

Analyze the current project to build a product profile. You're looking for what this product IS, who it's for, and what design decisions have already been made.

App Type & Domain

Determine what kind of product this is:

  • Platform type: Web app, desktop app (Electron/Tauri), mobile app, CLI, browser extension, SaaS, marketplace, etc.
  • Domain: E-commerce, developer tools, productivity, social, education, healthcare, finance, content/media, etc.
  • Business model clues: Free/paid, subscription, freemium, marketplace fees (check for pricing pages, plan tiers, billing code)

Look in:

  • README.md, CLAUDE.md, or any project docs
  • Route/page files for feature scope
  • Landing page or marketing copy if present
  • Package name, descriptions in package.json / composer.json / Cargo.toml

User-Facing Features

Map the product surface by scanning routes, pages, and navigation:

SourceWhat to look for
Route definitions (e.g., routes/web.php, app/routes.ts, src/pages/, src/app/)Feature scope — what screens/pages exist
Navigation components (sidebar, header, tabs)Information architecture — how features are organized
Layout filesPage structure patterns — shared chrome, content areas
Auth/role codeUser types — admin, member, guest, team roles
Form componentsData collection patterns — what users input
Dashboard/home pagePrimary user workflow — what users see first
Settings pagesCustomization surface — what users can configure
Notification/email templatesCommunication patterns — how the product talks to users

Design System & UI Patterns

Identify the existing design language:

  • Component library: shadcn/ui, Radix, Material UI, Ant Design, Headless UI, custom components
  • CSS approach: Tailwind, CSS modules, styled-components, Sass
  • Design tokens: Colors, spacing, typography (check theme files, CSS variables, tailwind config)
  • Layout patterns: Sidebar + content, top nav, dashboard grid, wizard/stepper, split pane
  • Interaction patterns: Modals vs. inline editing, toasts vs. banners, forms vs. command palettes
  • Existing component inventory: What reusable UI components already exist

Look in:

  • tailwind.config.* for design tokens
  • components/ui/ or similar for component library
  • Theme/design token files
  • Storybook config if present

User Context

Piece together who uses this product:

  • User roles: Check auth, permissions, middleware for distinct user types
  • Onboarding: Is there a setup wizard, welcome screen, or tutorial?
  • Collaboration: Multi-user? Teams? Sharing? Real-time?
  • Data ownership: Personal data, team data, public data?

Phase 2: Confirm Product Profile with User

IMPORTANT: First output the detected product profile as a text message to the user. Do NOT put the profile details inside the AskUserQuestion tool.

Step 1: Display the profile as text output

Output a message like this (with actual detected values):

I detected the following product profile for this project:

**Product:**
- Desktop app (Tauri) — developer productivity tool
- Manages local development environments and processes

**Users:**
- Individual developers
- No collaboration/team features detected

**Key Features:**
- Process management dashboard
- Log viewer with search
- Project configuration
- System tray integration

**Design:**
- React + Tailwind CSS
- shadcn/ui component library
- Sidebar + content layout
- Dark mode support

**Maturity:**
- Active development, core features established
- No onboarding flow detected

Step 2: Then ask for confirmation

AFTER displaying the profile above, use the AskUserQuestion tool with a simple confirmation question:

  • Question: "Does this product profile look correct?"
  • Options: "Yes, looks correct" / "Need corrections"

Wait for user confirmation before proceeding. If the user provides corrections, incorporate them.


Phase 3: Generate the Deep Research Prompt

Once the profile is confirmed, generate a comprehensive research prompt. The prompt should be structured for a deep research tool (like Claude, Perplexity, or similar).

Prompt Template

Generate output in this format (replace placeholders with actual product details):


START OF GENERATED PROMPT

I'm building a product with the following profile:

Product:

  • [App type, platform, domain]
  • [Core purpose in one sentence]

Target Users:

  • [Primary user types and their goals]
  • [Technical sophistication level]
  • [Usage context: work, personal, team, etc.]

Current Feature Set:

  • [List key features/screens]

Design System:

  • [Component library, CSS approach]
  • [Layout patterns currently used]
  • [Key interaction patterns]

Product Maturity:

  • [Stage: early prototype, MVP, established product, etc.]
  • [Notable gaps or areas under development]

I need comprehensive research on [TOPIC from $ARGUMENTS] — specifically product design best practices, UX patterns, and real-world examples for a product like mine.

Research Scope

1. UX Patterns & Best Practices

For [TOPIC] in products like mine, research:

  • Established UX patterns used by successful products in this domain
  • Interaction design best practices specific to [app type]
  • Information architecture considerations for [TOPIC]
  • Common UX mistakes products make with [TOPIC]
  • Accessibility considerations for [TOPIC]

2. Real-World Examples & Inspiration

Find examples of [TOPIC] from:

  • Direct competitors or products in the same domain
  • Best-in-class examples from any domain that solved [TOPIC] well
  • Before/after case studies showing how products improved [TOPIC]
  • Note what makes each example effective or ineffective

For each example, describe:

  • What the product does
  • How they handle [TOPIC]
  • What makes their approach work (or not)
  • Screenshots or detailed descriptions if possible

3. User Psychology & Behavior

Research the human side of [TOPIC]:

  • User expectations — what do users expect from [TOPIC] in this type of product?
  • Mental models — how do users think about [TOPIC]?
  • Decision fatigue and cognitive load — how does [TOPIC] affect user effort?
  • Error recovery — what happens when things go wrong with [TOPIC]?
  • Progressive disclosure — how much complexity to show upfront vs. on demand?

4. Product-Specific Considerations

Given my product profile, research:

  • How [TOPIC] should work for [user type] specifically
  • [App type]-specific constraints and opportunities for [TOPIC]
  • How [TOPIC] interacts with my existing features
  • Scale considerations — how should [TOPIC] work with 10 items vs. 1,000?

5. Measuring Success

Research how to know if [TOPIC] is working:

  • Key metrics to track for [TOPIC] (engagement, completion rate, time-on-task, etc.)
  • User signals that [TOPIC] is working well or poorly
  • A/B testing opportunities for [TOPIC]
  • Qualitative signals — what to listen for in user feedback

Requested Output Format

Please provide your findings organized as:

  1. Executive Summary

- Top 10 most important [TOPIC] decisions for a product like mine - Priority-ranked recommendations

  1. Pattern Library

- Proven UX patterns for [TOPIC] with descriptions - When to use each pattern - Tradeoffs between approaches

  1. Real-World Examples

- 5-10 examples from real products - What each does well and what could be improved - Applicability to my product

  1. Design Recommendations

- Specific recommendations for my product - Wireframe-level descriptions where helpful - Copy/microcopy suggestions where relevant - Component and layout suggestions that fit my design system

  1. Edge Cases & Empty States

- First-time user experience for [TOPIC] - Empty states, zero-data states - Error states and recovery flows - Power user vs. new user considerations - Extreme data scenarios (none, few, many, too many)

  1. Anti-Patterns

- What NOT to do with [TOPIC] - Common mistakes products make - Why they're problematic for users

  1. Implementation Priorities

- What to build first (MVP of [TOPIC]) - What to add later (nice-to-have enhancements) - What to skip entirely

  1. Resources

- Relevant articles, case studies, talks - Design system references - Tools for prototyping or testing [TOPIC]

END OF GENERATED PROMPT


Phase 4: Present the Output

Output the generated prompt as plain text that the user can easily copy.

Before the prompt, add:

Here's your deep research prompt for "[TOPIC]" tailored to your product. Copy this and paste it into your preferred research tool:

After the prompt, add:

Tip: This prompt works well with Claude, ChatGPT, Perplexity, or similar AI research tools. For best results, use a tool that can search the web for current information and real product examples.

Topic-Specific Additions

Depending on the topic provided in $ARGUMENTS, emphasize different aspects:

If topic is about "onboarding" / "first-run" / "setup":

  • Emphasize time-to-value, activation metrics, progressive profiling
  • Include wizard vs. contextual onboarding patterns, empty state design
  • Request examples of great onboarding from similar product types

If topic is about "navigation" / "information architecture":

  • Emphasize wayfinding, discoverability, mental models
  • Include sidebar vs. top nav vs. command palette patterns, breadcrumbs, search
  • Request examples of navigation scaling from simple to complex

If topic is about "search" / "filtering" / "discovery":

  • Emphasize query patterns, faceted search, typeahead, result ranking
  • Include empty results, suggested searches, filter UX, saved searches
  • Request examples from data-heavy products in similar domains

If topic is about "settings" / "preferences" / "configuration":

  • Emphasize organization, discoverability, defaults, dangerous settings
  • Include inline vs. dedicated settings page, search within settings, import/export
  • Request examples of settings UX that scales well

If topic is about "notifications" / "alerts" / "messaging":

  • Emphasize notification fatigue, urgency levels, channel selection
  • Include in-app vs. push vs. email, notification preferences, batching
  • Request examples of notification systems users actually like

If topic is about "empty states" / "zero data":

  • Emphasize first-time experience, calls to action, placeholder content
  • Include illustration vs. text, educational empty states, sample data
  • Request examples of empty states that drive engagement

If topic is about "forms" / "data entry" / "input":

  • Emphasize validation UX, inline errors, progressive forms, autosave
  • Include multi-step forms, conditional fields, smart defaults
  • Request examples of complex forms that feel simple

If topic is about "tables" / "lists" / "data display":

  • Emphasize sorting, pagination vs. infinite scroll, bulk actions, column management
  • Include responsive table patterns, inline editing, density controls
  • Request examples of data-dense UIs that remain usable

If topic is about "dashboard" / "home" / "overview":

  • Emphasize information hierarchy, actionable vs. informational, customization
  • Include widget patterns, activity feeds, status summaries, quick actions
  • Request examples of dashboards that serve both new and power users

If topic is about "pricing" / "plans" / "billing":

  • Emphasize comparison clarity, plan differentiation, upgrade paths
  • Include pricing psychology, trial experiences, plan change UX
  • Request examples of pricing pages with high conversion rates

If topic is about "mobile" / "responsive" / "touch":

  • Emphasize touch targets, thumb zones, progressive enhancement
  • Include responsive patterns, mobile-specific interactions, offline states
  • Request examples of products that transition well between desktop and mobile

If topic is about "dark mode" / "theming":

  • Emphasize readability, color contrast, image handling, user preference
  • Include system preference detection, smooth transitions, edge cases
  • Request examples of products with excellent dark mode implementations

If topic is about "error handling" / "error states":

  • Emphasize error recovery, clear messaging, suggested actions
  • Include form errors, page-level errors, network errors, permission errors
  • Request examples of products with graceful error handling

If topic is about "collaboration" / "sharing" / "teams":

  • Emphasize permissions, real-time presence, conflict resolution
  • Include sharing models, role management, activity feeds, mentions
  • Request examples of collaboration UX from similar product types

Notes

  • Always include the product's actual features and user types — they matter for relevant research
  • If you can't determine something about the product, note it as "[unknown]" and ask the user
  • The generated prompt should be self-contained and not require additional context
  • Tailor the examples section to the actual product domain (don't request generic examples)
  • Focus on product/UX decisions, not technical implementation — the prompt should help someone make design decisions, not write code

平台分布

Codex

37.33%
按下载量换算78

Claude

28.84%
按下载量换算60

Cursor

18.46%
按下载量换算38

Gemini CLI

8.75%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。目前只有一个公开来源,建议同时核对源仓库。

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