Skylv Market Pain Finder

市场调研：痛点自动挖掘分析。立项没方向？自动深挖市场痛点，一份报告帮你稳过评审 This skill should be used when the user asks about 市场调研：痛点自动挖掘分析. Keywords: 市场调研, 痛点分析, 竞品调研.

Security Scan

The skill's code, instructions, and declared requirements are consistent with its stated purpose (automated market pain discovery); it requests no credentials and has no surprising installs or network endpoints, aside from standard web searches and a local script that writes report files.

Purpose & Capability

Name/description, SKILL.md, and the included Python script all focus on collecting web data (via web_search/web_fetch), analyzing it, and writing a Markdown report—these requirements align with a market-research/pain-finding skill. Declared dependency on a 'market-researcher' skill and the listed tools (web_search, write_to_file) are appropriate.

Instruction Scope

Runtime instructions restrict activity to web_search/web_fetch, running the local script, and writing output files. The skill explicitly prohibits fabricating data and requires saving outputs. There is expected external data collection (search/fetch) but no instructions to read unrelated system files or environment variables.

Install Mechanism

No install spec is declared (instruction-only), which is low risk. SKILL.md suggests running 'pip install pandas' to satisfy the script, which is reasonable but is an external package installation step the user/agent must perform. No downloads from unknown URLs or archive extraction are present.

Credentials

The skill requests no environment variables, no credentials, and no config paths. File I/O is limited to a local data directory under the skill (../data) and explicit output paths. This is proportionate to the stated functionality.

Persistence & Privilege

always:false and no modifications to other skills or global agent settings. The skill creates and reads files only under its own data directory—no elevated persistence or cross-skill config changes are requested.

Assessment

This skill appears coherent and doesn't ask for credentials, but note: (1) it will perform web searches/fetches—confirm you are comfortable with the agent making external queries and collecting public data (and ensure you comply with target sites' terms and privacy rules); (2) SKILL.md asks you to pip install pandas before running the included script; (3) the script writes files to a local ../data directory—inspect that directory and outputs before sharing them; and (4) metadata version fields mismatch (_meta.json shows 3.0.0 while registry metadata lists 1.0.1) — a benign inconsistency but you may want to confirm you're using the intended release.

市场调研：痛点自动挖掘分析

立项没方向？自动深挖市场痛点，一份报告帮你稳过评审

前置依赖

pip install pandas

核心能力

能力1：在社交媒体/论坛检索用户讨论（web_search）

用 web_search 搜索相关信息。

能力2：提取高频痛点关键词

用 web_search 搜索行业论坛、社交媒体中的用户吐槽和需求；用 web_fetch 抓取竞品评价页面。

能力3：分析竞品优缺点

运行脚本进行数据分析处理。

能力4：生成用户需求优先级矩阵

用 write_to_file 生成文件。

能力5：输出完整市场调研报告

用 write_to_file 生成文件。

使用流程

步骤 1：收集用户需求

向用户确认以下信息（如果未主动提供）：

• 要调研哪个行业/市场？
• 关注哪个用户群体的痛点？
• 是否有特定的竞品需要分析？
• 输出形式偏好（报告/表格/脑图）

步骤 2：检索外部信息

执行以下搜索获取真实数据：

web_search("[用户主题] 竞品分析")
web_search("[用户主题] 市场规模")

确保获取到以下资源：

• 用户评论数据
• 竞品功能对比
• 痛点排名

步骤 3：运行脚本处理数据

python3 scripts/market_pain_finder_tool.py run \
  --input "用户提供的输入" \
  --output "/path/to/output_file"

读取脚本输出的结果，确认数据处理成功。

步骤 4：生成最终产出

基于脚本输出和搜索到的资源，用 write_to_file 生成以下文件：

• 市场调研报告
• 需求优先级矩阵

输出格式要求：Markdown 调研报告 + 需求矩阵

步骤 5：汇总交付

向用户展示：

1. 生成的文件路径和内容摘要
2. 搜集到的资源链接列表
3. 关键发现和建议

输出格式

# 📋 市场调研：痛点自动挖掘分析 — 执行报告

**生成时间**: YYYY-MM-DD HH:MM
**目标用户**: 产品经理、市场分析师、创业者

## 执行摘要
[基于实际执行结果的一段话摘要]

## 详细结果

### 📊 生成的文件
| 文件名 | 类型 | 说明 |
|--------|------|------|
| [文件名] | [类型] | [说明] |

### 🔗 资源链接
| 名称 | 链接 | 说明 |
|------|------|------|
| [资源] | [URL] | [说明] |

## 行动建议
[具体的下一步建议]

验收标准

• ✅ 检索了≥3个平台
• ✅ 痛点提取准确
• ✅ 竞品对比有据
• ✅ 报告可用于立项

场景化适配

根据行业（To B/To C/垂直领域）调整调研方向

依赖 Skills

本 Skill 参考以下已有 Skill 的能力进行增强：

• market-researcher

注意事项

• 所有数据必须来自 web_search / web_fetch 的真实搜索结果，严禁编造数据
• 数据缺失时标注"数据不可用"而非猜测
• 报告必须保存为文件（write_to_file），不能只在对话中输出
• 建议结合人工判断使用，AI 分析仅供参考