优化信息收集 · Info Gathering Optimizer

它解决什么问题

做调研、访谈或需求收集时,最容易出的问题不是写得慢,而是目标不清、来源混杂、缺项不自知:拿到一堆笔记却拼不成能用的结论。直接问 AI,常得到大段文字而非可交付的结构。

这个技能做什么

先把收集目标、口径与交付形式问清楚,只收集必要信息,缺什么补什么;再把素材整理成结论先行的结构化报告:每个结论挂证据、每条证据标来源,风险与建议分开列,中英术语保持一致。

为什么比裸提示词强

• 先问后收:一次一个问题,避免无效提问与信息遗漏。
• 结论先行:打开就能用,不用从长文里提炼。
• 可追溯:证据、风险、建议一一对应,便于复核。

典型用例

• 把访谈录音与笔记整理成结构化纪要。
• 做竞品调研的信息收集与缺口清单。
• 把客户反馈归纳成带优先级的产品建议。

局限

需要你配合回答澄清问题;适合文本类信息,深度量化建模请另配分析工具。

English · 英文介绍

The problem

When doing research, interviews or requirements gathering, the most common problem is not writing slowly, but unclear goals, mixed sources, and unawareness of missing items: you get a bunch of notes but can't put them together into a usable conclusion. Asking the AI ​​directly often results in large blocks of text rather than deliverable structures.

What it does

First, clarify the collection objectives, caliber and delivery form, collect only necessary information, and fill in whatever is missing; then organize the materials into a structured report with conclusions first: each conclusion is linked to evidence, each piece of evidence is marked with a source, risks and suggestions are listed separately, and Chinese and English terminology are consistent.

Why is it better than naked prompt words?

• Ask first and accept later: one question at a time to avoid invalid questions and missing information.
• Conclusion first: open it and use it, no need to extract it from a long article.
• Traceability: evidence, risks, and suggestions correspond one to one for easy review.

Typical use cases

• Organize interview recordings and notes into structured minutes.
• Information collection and gap list for competitive product research.
• Summarize customer feedback into prioritized product recommendations.

Limitations

Your cooperation is required to answer clarification questions; it is suitable for text-based information. Please use additional analysis tools for in-depth quantitative modeling.