Skill: happyandlg123321-maker/voc-growth-report (version 1.1.0)

--- name: voc-growth-report description: Turn exported social media comments — especially Xiaohongshu/小红书 CSV exports from 社媒助手 — into VOC insight, growth analysis, Feishu-ready operating structures, and boss-ready HTML report delivery links. Use this whenever the user wants to analyze comment CSVs, extract user sentiment/needs/commercial intent, segment audiences, build VOC reports, generate HTML decision reports, create Feishu/Bitable comment libraries, or turn comment exports into growth recommendations. Make sure to use this skill when the user mentions 社媒助手, 评论抓取, 评论CSV, VOC分析, 用户需求洞察, 商机分析, 飞书评论库, HTML报告, Trae/Cursor/Claude Code report prompts, or asks for a link instead of raw HTML code. --- # VOC Growth Report This skill converts exported social comment data into a repeatable growth-analysis workflow. The core idea is simple: 1. ingest a CSV export, 2. analyze comments through a VOC + growth lens, 3. generate a boss-ready HTML report, 4. prefer delivering a preview link/path instead of dumping raw HTML. Use this skill especially for 小红书 / 社媒助手 CSV exports, but it also works for similar social comment exports. ## What this skill should produce Depending on the user's ask, produce one or more of these: - a cleaned analysis brief, - a prompt pack for Trae / Cursor / Claude Code / Codex, - a field schema for Feishu Bitable, - a boss-ready HTML report prompt, - a local preview link delivery workflow. ## Default workflow ### Step 1: Confirm the real deliverable First identify which of these the user actually wants: - **analysis only**: sentiment / needs / intent / opportunity - **report prompt**: a prompt for another coding agent to generate the report - **report artifact**: a real HTML file or preview link - **Feishu workflow**: import/sync results into Feishu / Bitable - **skill/systemization**: package the whole VOC workflow into a reusable system If the user says things like: - “不要给我代码，给我链接” - “社媒助手抓完 csv 后怎么交给 Trae” - “给我老板能看的报告” then optimize for **delivery**, not code verbosity. ### Step 2: Understand the input data Identify or ask for: - CSV path or file - likely columns: comment text, username, time, likes, replies, post title, link, platform - source platform / export tool - time range / sample size if relevant If columns differ, infer the closest mapping instead of blocking on exact names. This skill has already been validated against a real 社媒助手 / 小红书 comment export structure with fields like: - 评论ID - 评论内容 - 点赞量 - 评论时间 - IP地址 - 子评论数 - 笔记ID / 笔记链接 - 用户ID / 用户链接 / 用户名称 - 一级评论ID / 一级评论内容 - 引用的评论ID / 引用的评论内容 / 引用的用户名称 ### Step 3: Analyze comments in 4 layers When doing actual VOC analysis, prefer this four-layer model: #### 1. Emotion Classify into: - 正向 - 中性 - 负向 Output: - distribution - positive highlights - negative complaints #### 2. Intent Classify into: - 咨询价格 - 咨询功能 - 咨询购买 - 使用反馈 - 吐槽抱怨 - 夸赞认可 - 对比竞品 - 无效灌水 - 其他 Output: - type distribution - representative comments - common questions #### 3. Commercial opportunity Classify into: - 高 - 中 - 低 - 无 Use these definitions: - 高：明确咨询价格、购买方式、联系方式、合作、试用、下单 - 中：明确咨询功能、效果、适用人群、区别、使用方法 - 低：普通兴趣表达、轻度认可、一般互动 - 无：灌水、无关内容、纯表情 Output: - opportunity distribution - top high-opportunity comments - conversion blockers #### 4. Need discovery Split needs into: - 已被满足的需求 - 未被满足的需求 - 潜在需求 Important: latent needs must be inferred from actual complaints, hesitation, comparisons, or repeated asks — never from pure imagination. Output: - need categories - representative comments - why each need is classified that way ### Step 4: Upgrade analysis into growth decisions Do not stop at “analysis”. Convert outputs into growth decisions: - who to prioritize, - what pain points to solve first, - what value propositions to amplify, - what content topics to create, - what sales talking points to use, - what operations team should reply to first. When appropriate, use a Kotler-flavored framing: - segmentation, - need discovery, - value proposition mapping, - conversion opportunity, - growth actions. ## Default report structure For boss/CEO-ready reports, prefer this structure: 1. 封面 / 数据概况 2. 用户情绪总览 3. 用户分群分析 4. 用户需求图谱 5. 商机与转化机会 6. 价值主张与增长建议 7. CEO Summary ## Delivery-first rule If the user wants a usable deliverable, do **not** stop at raw HTML code. Prefer to instruct the coding agent / ACP harness to: 1. generate the HTML, 2. save it to a file, 3. start a local static preview, 4. return a preview link and file path. Use language like: - “你的任务不是输出源码，而是完成交付” - “最终返回访问链接、本地文件路径、报告标题、简短说明” ## Output modes ### Mode A: Prompt pack When the user wants something to paste into Trae / Cursor / Claude Code / Codex, provide: - one consolidated instruction block, - explicit input/output contract, - delivery requirement: link > raw code. ### Mode B: Feishu workflow When the user wants Feishu integration, provide: - comment library field schema, - suggested analysis fields, - optional Bitable views, - minimal workflow from CSV/comment sync to reporting. Recommended 12-field base schema: - 平台 - 帖子标题 - 帖子链接 - 评论内容 - 评论用户 - 评论时间 - 情绪倾向 - 意图类型 - 商机等级 - 是否需要回复 - 跟进状态 - 备注 ### Mode C: Executive summary For direct advice in chat, use this order: 1. conclusion, 2. why, 3. next action. Keep it concise and business-oriented. ## Example trigger cases - “帮我把社媒助手抓下来的评论 csv 做成老板能看的报告” - “不要给我 html 代码，我要最终链接” - “帮我做小红书 voc 分析” - “把评论做成需求洞察 + 商机分析” - “给 Trae 一段完整指令，从 csv 到 html 报告链接” - “封装一个 VOC 分析 skill” ## Anti-patterns Avoid these mistakes: - stopping at sentiment only, - giving a word cloud as the main output, - dumping raw HTML when the user asked for delivery, - inventing latent needs with no textual basis, - overcomplicating the workflow before the CSV/report path is usable. ## Success standard A strong result should make it easy for the user to go from: **comment export → user insight → growth decisions → report delivery** with minimal repeated prompting. A stronger result should also be capable of producing a real executive-facing HTML demo report with sections such as: - 封面 / 数据概况 - 用户情绪总览 - 用户分群分析 - 用户需求图谱 - 商机与转化机会 - 价值主张与增长建议 - CEO Summary

path: evals/evals.json
content: {
  "skill_name": "voc-growth-report",
  "evals": [
    {
      "id": 1,
      "prompt": "我已经用社媒助手抓了一批小红书评论，下载成 csv 了。帮我给 Trae 一条完整指令：读取 csv、做 VOC 分析、生成老板能看的 HTML 报告，并最终给我可打开的链接，不要只给源码。",
      "expected_output": "A consolidated ACP-style instruction that covers CSV ingestion, VOC/growth analysis, HTML report generation, file save, local preview, and final delivery link/path.",
      "files": []
    },
    {
      "id": 2,
      "prompt": "我想把评论库沉淀到飞书，先给我一个极简但正式的字段结构，重点要有情绪、意图、商机和跟进状态。",
      "expected_output": "A concise but practical Feishu/Bitable schema centered on comment operations and follow-up.",
      "files": []
    },
    {
      "id": 3,
      "prompt": "请把小红书评论分析升级成科特勒增长视角，不只是情绪分析，要能看出人群、需求、价值主张和转化机会。",
      "expected_output": "A Kotler-flavored VOC/growth analysis structure or prompt that covers segmentation, needs, value proposition, and conversion opportunity.",
      "files": []
    }
  ]
}


path: references/demo-output-summary.md
content: # Demo Output Summary

This summary can be used in listing pages, release notes, or demos to show what the skill can produce from a real CSV input.

## Example output snapshot
Using a real Xiaohongshu / 社媒助手 comment export CSV, the workflow produced a boss-ready HTML report titled:

**《小红书 VOC 洞察与增长决策报告》**

The demo report included:
- cover page with data overview,
- sentiment distribution,
- audience segmentation table,
- satisfied / unsatisfied / latent need map,
- opportunity and conversion analysis,
- growth recommendations,
- CEO summary with next-7-day actions.

## Why this matters
This demonstrates that the skill is not limited to theory, schema design, or prompt-writing. It can support the full practical path from exported comments to a stakeholder-facing report artifact.

## What the demo proves
- real CSV fields can be parsed into a usable analysis workflow,
- real comments can be converted into structured insight,
- report outputs can be shaped for founders, operators, and decision-makers,
- the workflow is suitable for delivery-oriented agent setups.


path: references/executive-report-structure.md
content: # Executive HTML Report Structure

Use this structure for a boss-ready VOC growth report.

## Required sections
1. 封面 / 数据概况
2. 用户情绪总览
3. 用户分群分析
4. 用户需求图谱
5. 商机与转化机会
6. 价值主张与增长建议
7. CEO Summary

## Guidance by section

### 1. 封面 / 数据概况
Include source, total posts, total comments, date range, and report objective.

### 2. 用户情绪总览
Show positive / neutral / negative distribution, plus top praise and complaint themes.

### 3. 用户分群分析
Segment comments into practical groups such as price-sensitive, function-driven, result-driven, beginner, high-intent, and observers.

### 4. 用户需求图谱
Separate satisfied needs, unsatisfied needs, and latent needs. Do not fabricate latent needs without textual evidence.

### 5. 商机与转化机会
Show opportunity distribution, high-intent comments, pre-conversion questions, and conversion blockers.

### 6. 价值主张与增长建议
Translate findings into value propositions, content topics, product fixes, and sales wording.

### 7. CEO Summary
Make this skimmable. It should answer:
- who to prioritize,
- what to fix first,
- what selling point to amplify,
- what the next 7-day actions should be.

## Visualization guidance
Prefer:
- summary cards,
- distribution charts,
- ranked lists,
- concise commentary.

Treat word clouds as optional decoration, not as the core artifact.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)