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产品透镜

使用此技能验证产品构思,在构建任何功能之前确保其正确性。

产品透镜 是什么?

产品透镜(Product Lens)是一个专注于产品诊断而非实现规格编写的专业AI技能。它适用于多种场景:开始新功能前验证“为什么”、进行每周产品评审、在功能选择中犹豫不决时、发布前检查用户体验流畅度,以及将模糊想法转化为产品简报。该技能支持四种工作模式:产品诊断(类似YC办公时间自动提问)、创始人评审(通过项目文件分析产品市场契合度)、用户旅程审计(模拟新用户实际体验并评估摩擦点)、以及功能优先级排序(使用ICE评分法从众多创意中选出最佳方案)。所有输出均为可操作记录,每个建议都附带具体后续步骤。它可与/browser-qa、/design-system audit、/canary-watch和product-capability等其他技能集成,覆盖从产品验证到实现的全流程。

兼容平台✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/product-lens

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

产品透镜 — 先思考,再构建

此领域专注于产品诊断,而非实现规格编写。

如果用户需要一个持久的 PRD 转 SRS 或能力合同产物,请转交给 product-capability。

何时使用

  • 开始任何功能之前 — 验证“为什么”
  • 每周产品评审 — 我们是否在构建正确的东西?
  • 在功能选择之间纠结时
  • 发布之前 — 对用户旅程进行合理性检查
  • 将模糊的想法转化为产品简报,再开始工程规划时

工作原理

模式 1:产品诊断

如同 YC 办公时间一样自动化。提出关键问题:

1. 这是为谁做的?(具体的人,而不是“开发者”)
2. 痛点是什么?(量化:频率有多高,有多严重,他们今天怎么做的?)
3. 为什么是现在?(发生了什么变化使得这件事变得可能/必要?)
4. 10 星版本是什么?(如果时间和金钱不限)
5. 最小可行产品(MVP)是什么?(能够验证假设的最小东西)
6. 反目标是什么?(你明确不构建什么?)
7. 你如何知道它有效?(指标,而不是感觉)

输出:一份 PRODUCT-BRIEF.md,包含答案、风险以及是否继续的建议。

如果结果是“是的,构建这个”,下一个领域是 product-capability,而不是更多创始人的虚张声势。

模式 2:创始人评审

通过创始人的视角审查你当前的项目:

1. 阅读 README、CLAUDE.md、package.json、最近的提交
2. 推断:这试图成为什么?
3. 评分:产品-市场契合信号(0-10)
   - 使用增长轨迹
   - 留存指标(重复贡献者、回头用户)
   - 收入信号(定价页面、计费代码、Stripe 集成)
   - 竞争护城河(什么难以复制?)
4. 识别:能让这件事实现 10 倍增长的那一个东西
5. 标记:你正在构建但无关紧要的事情

模式 3:用户旅程审计

映射实际用户体验:

1. 以新用户身份克隆/安装产品
2. 记录每一个摩擦点(令人困惑的步骤、错误、缺失的文档)
3. 计时每个步骤
4. 与竞争对手的引导流程进行比较
5. 评分:价值实现时间(用户需要多久才能获得第一次成功?)
6. 建议:引导流程的前 3 个修复项

模式 4:功能优先级排序

当你有 10 个想法但需要选出 2 个时:

1. 列出所有候选功能
2. 对每个功能评分:影响(1-5)× 信心(1-5)÷ 工作量(1-5)
3. 按 ICE 分数排名
4. 应用约束条件:资金跑道、团队规模、依赖关系
5. 输出:带理由的优先路线图

输出

所有模式输出的是可操作的文档,而非论文。每个建议都附带具体的下一步行动。

集成

配合使用:

  • /browser-qa 验证用户旅程审计结果
  • /design-system audit 进行视觉打磨评估
  • /canary-watch 进行发布后监控
  • product-capability 当产品简报需要变成可实现的性能计划时

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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