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Company Research

Community
liangdabiao
company-research

Company, competitor, and market intelligence research using Exa or an equivalent web-search/MCP tool. Use for requests to research a company, build competitor lists, find company news, summarize financial/funding/headcount/location facts, discover public LinkedIn/people profiles, or produce cited market landscape briefs in Codex, OpenClaw, and other SKILL.md-compatible agents.

Overview

Publisherliangdabiao
Repositoryexa-research-mcp-skill
Skill namecompany-research
Stars
117
Forks
17
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by liangdabiao on GitHub. Read the source before you install it.

Installation

Install the Company Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/liangdabiao/exa-research-mcp-skill/tree/main/skills/company-research
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/liangdabiao/exa-research-mcp-skill.git /tmp/exa-research-mcp-skill
mkdir -p .claude/skills
cp -r /tmp/exa-research-mcp-skill/skills/company-research .claude/skills/company-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Company Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Company Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Company Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Company Research

Core Rules

  • Prefer Exa advanced web search when available. In Claude this is commonly mcp__exa__web_search_advanced_exa; in Codex/OpenClaw use the configured Exa MCP search tool or the host's web-search tool.
  • Do not use weaker/basic Exa search tools when an advanced Exa search tool is available.
  • Keep raw search noise out of the final answer. Work from distilled notes, merged entities, and citations.
  • Use independent research passes only when the host supports them and the user/task policy allows them; otherwise run compact searches sequentially and summarize after each batch.
  • Cite primary or high-quality sources for factual claims, especially current facts such as funding, revenue, executives, headcount, product launches, and pricing.

Research Workflow

  1. Clarify scope if needed

    • Identify target company, geography, sector, time horizon, and requested depth.
    • If the user gives an ambiguous quantity, ask for the desired number of companies or choose a reasonable default and state it.
  2. Plan query variants

    • Generate 2-3 phrasings per topic to improve coverage.
    • Include local-language terms for non-English markets.
    • Mix source intents: official company pages, news, databases, social profiles, and analyst/industry sources.
  3. Run focused searches

    • Use company category for homepages and metadata when Exa supports categories.
    • Use news for press coverage, launches, funding, earnings, partnerships, and recent events.
    • Use people for public LinkedIn-style profiles and leadership discovery.
    • Use tweet or social search only for brand/social presence when relevant.
  4. Merge and deduplicate

    • Normalize company names, domains, subsidiaries, and brands.
    • Separate confirmed facts from inference.
    • Flag uncertain or conflicting data instead of silently choosing one source.
  5. Synthesize output

    • Produce the format the user asked for: brief, table, competitor map, JSON, or full report.
    • Include citations next to key claims.
    • End with gaps, assumptions, and recommended follow-up searches when evidence is incomplete.

Dynamic Search Depth

  • "A few" / quick scan: 10-20 results total.
  • Standard competitor/company brief: 20-50 results total.
  • Comprehensive landscape: 50-100 results total across variants.
  • User-specified number: match the requested number.
  • If the search budget is constrained, prioritize official sites and recent reputable sources.

Output Patterns

Company Brief

Use this structure for single-company research:

markdown
## Company Snapshot
| Field | Finding | Sources |
|---|---|---|
| Legal/brand name | ... | ... |
| Website | ... | ... |
| HQ / locations | ... | ... |
| Employees / scale | ... | ... |
| Funding / revenue | ... | ... |
| Products | ... | ... |

## Recent Signals
- ...

## Competitors
| Company | Why comparable | Differentiator | Source |
|---|---|---|---|

## Risks / Unknowns
- ...

Competitor List

Use this structure for market discovery:

markdown
| # | Company | Website | Category | Geography | Evidence | Confidence |
|---|---|---|---|---|---|---|

Confidence levels:

  • High: official website plus an independent source.
  • Medium: one strong source or multiple weaker sources.
  • Low: partial match, outdated page, or inferred relevance.

Browser / Direct Page Fallback

Use Chrome MCP as the preferred browser fallback when the user has configured and sanitized it. Use browser or direct page access when:

  • Search snippets are insufficient.
  • Pages require JavaScript rendering.
  • Pricing, product catalogs, or reviews must be verified directly.
  • A source appears contradictory and needs manual inspection.

When using Chrome MCP, behave like a careful human browser user: record only distilled facts, page title, URL, publisher, accessed date, and confidence; do not persist cookies, credentials, private account data, or unrelated browsing history.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Company Research AI skill do?

Company, competitor, and market intelligence research using Exa or an equivalent web-search/MCP tool. Use for requests to research a company, build competitor lists, find company news, summarize financial/funding/headcount/location facts, discover public LinkedIn/people profiles, or produce cited market landscape briefs in Codex, OpenClaw, and other SKILL.md-compatible agents.

Why use Company Research on TypingMind?

Because you install it once and use it with any model. Company Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Company Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/liangdabiao/exa-research-mcp-skill/tree/main/skills/company-research. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Company Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Company Research?

As many as you like. As long as a model supports skills, you can use Company Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Company Research AI skill free?

It is published on GitHub by liangdabiao. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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