Agent skill

Company Research

by stophobia in stophobia/deerflow2.0-enhanced

综合企业背景调研技能,用于尽职调查、合作伙伴评估、投资分析、市场研究等场景。支持公司工商信息、财务数据、法律风险、舆情分析、竞品对比等多维度调研,自动生成Markdown和HTML格式的专业调研报告。触发条件:用户提及"企业调研"、"公司背景"、"尽职调查"、"合作伙伴评估"、"投资分析"、"市场研究"等关键词。

MITAuto-check passedSales & Support

Install Company Research

skills CLI
$ npx skills add stophobia/deerflow2.0-enhanced --skill company-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install stophobia/deerflow2.0-enhanced company-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/stophobia/deerflow2.0-enhanced.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/public/company-research .claude/skills/company-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
company-research
GitHub stars
822
Token cost
~845 tokens
SKILL.md length
248 words
Files
1
Skills in repo
5
Repo updated
First seen
Licence
MIT

At a glance

综合企业背景调研技能,用于尽职调查、合作伙伴评估、投资分析、市场研究等场景。支持公司工商信息、财务数据、法律风险、舆情分析、竞品对比等多维度调研,自动生成Markdown和HTML格式的专业调研报告。触发条件:用户提及"企业调研"、"公司背景"、"尽职调查"、"合作伙伴评估"、"投资分析"、"市场研究"等关键词。

  • Works in 10 steps: 工商信息采集 → 财务状况分析 → 法律风险调查 → …
  • Tasks that involve Sales call preparation
  • SKILL.md covers 概述, 使用场景, 核心能力 and 调研方法论, plus 8 more sections
  • Calls python3

What it does

Company Research is an agent skill from stophobia/deerflow2.0-enhanced. 综合企业背景调研技能,用于尽职调查、合作伙伴评估、投资分析、市场研究等场景。支持公司工商信息、财务数据、法律风险、舆情分析、竞品对比等多维度调研,自动生成Markdown和HTML格式的专业调研报告。触发条件:用户提及"企业调研"、"公司背景"、"尽职调查"、"合作伙伴评估"、"投资分析"、"市场研究"等关键词。

Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Sales & Support, covering Sales call preparation. The repository describes itself as: DeerFlow 2.0 Enhanced - Chinese localization + New skills. The licence is MIT.

When your agent uses it

  • Tasks that involve Sales call preparation

Example prompts

  • “合作伙伴评估”
  • “/company-research”

Requirements

  • Python 3

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. 工商信息采集
  2. 财务状况分析
  3. 法律风险调查
  4. 舆情监测
  5. 竞品分析(当需要时)
  6. 行业研究(当需要时)
  7. 目标确认
  8. 信息收集
  9. 分析整理
  10. 报告生成

What it can do on your machine

Read from SKILL.md and the folder at commit 814bde3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Company Research loads about 845 tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 248 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~845

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from stophobia/deerflow2.0-enhanced at commit 814bde3, republished under its MIT licence (© stophobia). 248 words, ~845 tokens.

Download SKILL.mdSave it as .claude/skills/company-research/SKILL.md (or your agent's skills folder).
name
company-research
description
综合企业背景调研技能,用于尽职调查、合作伙伴评估、投资分析、市场研究等场景。支持公司工商信息、财务数据、法律风险、舆情分析、竞品对比等多维度调研,自动生成Markdown和HTML格式的专业调研报告。触发条件:用户提及"企业调研"、"公司背景"、"尽职调查"、"合作伙伴评估"、"投资分析"、"市场研究"等关键词。

企业综合调研技能 (Company Research)

综合多数据源的企业背景调研技能,适用于尽职调查、合作伙伴评估、投资分析、市场研究等场景。

概述

本技能通过整合多个数据源对企业进行全面调研:

  • 工商信息(注册信息、股东结构、主要人员)
  • 财务数据(融资历史、营收状况)
  • 法律风险(诉讼记录、被执行信息)
  • 舆情监测(媒体报道、社交口碑)
  • 竞品分析(市场份额、功能对比)
  • 行业趋势(市场规模、发展预测)

使用场景

当用户提及以下内容时激活:

  • "企业调研"、"公司背景调查"
  • "尽职调查"、"DD"
  • "合作伙伴评估"、"供应商审核"
  • "投资分析"、"投资尽调"
  • "市场研究"、"行业分析"
  • "竞争对手分析"、"竞品分析"
  • "背景核实"、"高管履历"

核心能力

1. 工商信息采集
  • 企业工商注册信息查询
  • 股东结构与股权分布
  • 主要人员与组织架构
  • 变更历史记录
  • 分支机构与关联公司
2. 财务状况分析
  • 融资历史与投资方
  • 营收与盈利状况
  • 税务信息
  • 银行信用评估
  • 并购重组历史
3. 法律风险调查
  • 诉讼记录查询
  • 被执行人信息
  • 失信被执行人
  • 行政处罚记录
  • 经营异常记录
  • 股权冻结信息
4. 舆情监测
  • 媒体报道收集
  • 社交媒体口碑
  • 行业评价分析
  • 负面信息预警
  • 危机事件追踪
5. 竞品分析(当需要时)
  • 竞品识别与列表
  • 产品功能对比矩阵
  • 定价策略分析
  • 市场定位对比
  • 优劣势总结
6. 行业研究(当需要时)
  • 市场规模数据
  • 行业发展趋势
  • 政策环境分析
  • 准入壁垒评估
  • 增长驱动因素

调研方法论

Phase 1: 目标确认

明确调研目标:

  • 调研目的是什么?(投资/合作/采购/招聘...)
  • 需要调研到什么深度?
  • 有什么特定关注点?
Phase 2: 信息收集

优先级顺序:

  1. 官方数据源(工商、财报、官网)
  2. 权威第三方(天眼查、企查查、启信宝)
  3. 新闻媒体报道
  4. 行业报告
  5. 社交媒体评价
  6. 用户评价

常用数据源:

bash
# 工商信息
天眼查、企查查、国家企业信用信息公示系统

# 财务数据
年报、财报、融资披露

# 法律信息
中国裁判文书网、中国执行信息公开网

# 舆情信息
百度新闻、Google News、微博、雪球

# 行业数据
艾瑞咨询、易观分析、IDC、Gartner
Phase 3: 分析整理

对收集的信息进行分类整理:

  1. 事实性信息 - 可验证的数据
  2. 推断性信息 - 基于证据的合理推测
  3. 评估性信息 - 需要标注置信度
Phase 4: 报告生成

生成结构化调研报告,包括:

  1. 执行摘要(结论先行)
  2. 企业概况
  3. 股权结构
  4. 财务状况
  5. 法律风险评估
  6. 舆情分析
  7. 竞品/行业分析(如适用)
  8. 风险评级
  9. 调研依据
  10. 附录

报告输出格式

格式要求
  • 语言:根据 output_locale 设置(默认 zh_CN)
  • 格式:Markdown → HTML(使用 md2html.py 转换)
  • 标题:使用企业全称
  • 数据标注:所有数据必须标注来源和置信度
  • 日期:报告生成日期
置信度标注
等级标注说明
高🟢 高置信官方来源,多源验证
中🟡 中等置信可靠来源,单一验证
低🔴 低置信非官方,推测性质
风险评级
等级标注建议
低风险✅ 绿灯可正常合作
中风险⚠️ 黄灯需进一步核实
高风险🔴 红灯建议谨慎合作

数据真实性协议

严格遵守:

  • 所有数据必须有明确来源
  • 无法确认的数据标注"未确认"
  • 模拟数据标注"模拟数据"
  • 推测性内容标注"推测"
  • 禁止编造数据

使用工具

调研阶段
  • web_search - 搜索企业信息
  • web_fetch - 获取详细页面
  • feishu_search_doc_wiki - 搜索内部文档
  • feishu_bitable_app_table_record - 查询内部数据(如有)
报告阶段
  • write - 生成 Markdown 报告
  • md2html - 转换为 HTML(推荐)

输出示例

文件命名
企业名称_调研报告_YYYYMMDD.md
企业名称_调研报告_YYYYMMDD.html
报告结构
markdown
# 北京众星联恒科技有限公司综合调研报告

## 执行摘要
[结论先行,1-2段概括]

## 一、企业概况
### 1.1 基本信息
[工商信息]

### 1.2 发展历程
[关键里程碑]

## 二、股权结构
### 2.1 股东构成
[股东列表及持股比例]

### 2.2 关联公司
[母公司/子公司/兄弟公司]

## 三、财务状况
### 3.1 融资历史
[历次融资]

### 3.2 营收状况
[营收数据]

## 四、法律风险评估
### 4.1 诉讼记录
### 4.2 被执行信息
### 4.3 行政处罚

## 五、舆情分析
### 5.1 媒体评价
### 5.2 用户口碑
### 5.3 负面预警

## 六、风险综合评级
[雷达图/评分卡]

## 七、调研依据
[数据来源列表]

## 八、附录
[原始数据/补充材料]

HTML 报告生成

完成 Markdown 报告后,推荐转换为 HTML:

bash
python3 /root/.openclaw/workspace/deer-flow/skills/public/github-deep-research/scripts/md2html.py <报告文件>.md

HTML 特性:

  • 专业排版和清晰布局
  • 代码块高亮、表格样式、引用块样式
  • 响应式设计
  • 打印友好样式

注意事项

  1. 数据优先 - 优先使用官方和权威数据源
  2. 标注来源 - 每个数据点标注来源
  3. 标注置信度 - 区分高/中/低置信度
  4. 区分事实与推测 - 不混淆两者
  5. 中立客观 - 不带感情色彩,客观呈现正负面
  6. 及时更新 - 标注数据时效性
  7. 法律合规 - 不使用非法获取的数据
  8. 保护隐私 - 不涉及个人隐私信息(除公开的高管信息)

质量检查清单

生成报告前检查:

  • 调研目标明确
  • 主要数据源已覆盖
  • 正负面信息均有呈现
  • 风险评级有依据
  • 所有数据标注来源
  • 区分事实与推测
  • 结论有数据支撑

输出

最终交付:

  1. Markdown 格式调研报告(.md)
  2. HTML 格式调研报告(.html,推荐)

© stophobia, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/public/company-research of stophobia/deerflow2.0-enhanced.

Open the folder on GitHubat commit 814bde3

Compare with similar skills

Company Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Meeting Prep BriefBrianRWagner/ai-marketing-claude-code-skills441—~922Automated safety check: PassNone
SdtStopDisTrain/sdt-skills309—~535Automated safety check: PassMIT
Account Researchextruct-ai/gtm-skills109—~1.6kAutomated safety check: PassNone
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Categories

Questions about Company Research

What does Company Research do?

综合企业背景调研技能,用于尽职调查、合作伙伴评估、投资分析、市场研究等场景。支持公司工商信息、财务数据、法律风险、舆情分析、竞品对比等多维度调研,自动生成Markdown和HTML格式的专业调研报告。触发条件:用户提及"企业调研"、"公司背景"、"尽职调查"、"合作伙伴评估"、"投资分析"、"市场研究"等关键词。. 0-enhanced.

When should I use Company Research?

Company Research fits situations like: tasks that involve Sales call preparation.

How do I install Company Research in Claude Code?

Run `npx skills add stophobia/deerflow2.0-enhanced --skill company-research -a claude-code`. Or copy the skill folder (skills/public/company-research in stophobia/deerflow2.0-enhanced) into .claude/skills/company-research in your project. Claude Code loads it when a task matches its description.

How do I install Company Research in Codex?

Run `npx skills add stophobia/deerflow2.0-enhanced --skill company-research -a codex`. Or copy the skill folder (skills/public/company-research in stophobia/deerflow2.0-enhanced) into .agents/skills/company-research in your project. Codex loads it when a task matches its description.

Can I use Company Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add stophobia/deerflow2.0-enhanced --skill company-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/company-research, .gemini/skills/company-research, .github/skills/company-research and .opencode/skills/company-research in your project.

What does Company Research need to run?

Going by SKILL.md and its folder, Company Research needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Company Research access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Company Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Company Research use?

Company Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Company Research use?

About 845 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Company Research?

Skills that share tags, products or a category with Company Research: Luopan Company Research (zhangxiaoqiang1991/luopan, 389 stars), Meeting Prep Brief (BrianRWagner/ai-marketing-claude-code-skills, 441 stars), Sdt (StopDisTrain/sdt-skills, 309 stars) and Account Research (extruct-ai/gtm-skills, 109 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Company Research?

stophobia (a GitHub user) maintains it in stophobia/deerflow2.0-enhanced, which has 822 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on March 23, 2026.

Source: stophobia/deerflow2.0-enhanced on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.