Meeting Brief Generator logo

Meeting Brief Generator

Organization
Varnan-Tech
meeting-brief-generator

Takes a company name and optional contact, runs targeted research via Tavily, synthesizes a 1-page pre-call brief with Gemini, and optionally saves it to Notion. Use when asked to prepare for a meeting, research a prospect before a call, generate a company brief, create a pre-call summary, or write a meeting prep doc. Trigger when a user says "prepare me for a meeting with", "research this company before my call", "generate a meeting brief for", "I have a call with X tomorrow", or "create a prospect brief for".

Overview

PublisherVarnan-Tech
Repositoryopendirectory
Skill namemeeting-brief-generator
Stars
674
Forks
74
Bundled files
3
LicenseMIT
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.

  • 3 bundled files

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

  • Open source

    Published by Varnan-Tech on GitHub. Read the source before you install it.

Installation

Install the Meeting Brief Generator 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/Varnan-Tech/opendirectory/tree/main/skills/meeting-brief-generator
  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/Varnan-Tech/opendirectory.git /tmp/opendirectory
mkdir -p .claude/skills
cp -r /tmp/opendirectory/skills/meeting-brief-generator .claude/skills/meeting-brief-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Meeting Brief Generator 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 Meeting Brief Generator 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 Meeting Brief Generator 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.

Meeting Brief Generator

Take a company name and optional contact. Research the company via Tavily. Synthesize a 1-page pre-call brief with Gemini. Optionally save to Notion.


Critical rule: DO NOT INVENT SPECIFICS. Every fact, number, and claim in the brief must come from a Tavily search result. Mark any section with no search data as "Limited public information found." Never fabricate funding amounts, employee counts, or product details.


Step 1: Setup Check

Confirm required env vars:

bash
echo "TAVILY_API_KEY: ${TAVILY_API_KEY:+set}"
echo "GEMINI_API_KEY: ${GEMINI_API_KEY:+set}"
echo "NOTION_TOKEN: ${NOTION_TOKEN:-not set}"
echo "NOTION_DATABASE_ID: ${NOTION_DATABASE_ID:-not set}"

If TAVILY_API_KEY is missing: Stop. Tell the user: "TAVILY_API_KEY is required. Get it at app.tavily.com. Add it to your .env file."

If GEMINI_API_KEY is missing: Stop. Tell the user: "GEMINI_API_KEY is required. Get it at aistudio.google.com. Add it to your .env file."

If NOTION_TOKEN or NOTION_DATABASE_ID is missing: Continue. The brief will be output as text only. Notion saving is skipped.

Confirm input is present. The user must provide at minimum a company name. If not provided, ask: "Which company are you meeting with?"


Step 2: Gather Context

Collect the following. Ask only for what is missing.

Required:

  • Company name (or domain/URL if provided)
  • Meeting date

Optional (do not block if missing):

  • Contact name and title
  • Meeting type (discovery, demo, follow-up, QBR)
  • Any specific topics or goals the user wants to cover

If the user provides a company URL or domain, use it to make Tavily queries more precise (e.g. site:example.com or include the domain in search terms).


Step 3: Research with Tavily

Run these searches in sequence. Each targets one section of the brief. Save the top results from each (title, url, content snippet, score).

Keep results with score >= 0.5. If a search returns 0 qualifying results, mark that section as "Limited public information found."

Search 1: Company overview

bash
curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "\"COMPANY\" overview founded employees headquarters",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true
  }'

Search 2: Recent news (last 30 days)

bash
curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "\"COMPANY\" news announcement",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true,
    "topic": "news",
    "time_range": "month"
  }'

Search 3: Tech stack

bash
curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "\"COMPANY\" technology stack engineering infrastructure tools",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true
  }'

Search 4: Product and pricing

bash
curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "\"COMPANY\" product features pricing use case",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true
  }'

Search 5: Competitors

bash
curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "\"COMPANY\" competitors alternatives vs",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true
  }'

Search 6: Funding and growth

bash
curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "\"COMPANY\" funding raised valuation growth",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true
  }'

If contact name is provided, run two more searches:

Search 7: Contact profile

bash
curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "\"CONTACT_NAME\" \"COMPANY\" role title",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true
  }'

Search 8: Contact background

bash
curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "\"CONTACT_NAME\" background career LinkedIn",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true
  }'

Step 4: Synthesize with Gemini

Read references/brief-format.md in full. Read references/output-template.md and use the template.

Write the Gemini request to a temp file:

bash
cat > /tmp/meeting-brief-request.json << 'ENDJSON'
{
  "system_instruction": {
    "parts": [{
      "text": "You are a GTM research analyst preparing a 1-page pre-call brief for a sales or business development meeting. Rules: Every claim must cite a source URL from the provided research. Use the format 'Because [finding from research], mention [point] to [goal]' for talking points. No invented data. If a section has no research data, write 'Limited public information found.' No em dashes. No banned words. Under 400 words total. The brief must be scannable in 3 minutes."
    }]
  },
  "contents": [{
    "parts": [{
      "text": "RESEARCH_RESULTS_AND_INSTRUCTIONS_HERE"
    }]
  }],
  "generationConfig": {
    "temperature": 0.3,
    "maxOutputTokens": 2500
  }
}
ENDJSON
curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d @/tmp/meeting-brief-request.json \
  | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['candidates'][0]['content']['parts'][0]['text'])"

Replace RESEARCH_RESULTS_AND_INSTRUCTIONS_HERE with:

  • All Tavily search results (title, url, content snippet per result)
  • The brief template structure from output-template.md
  • The company name, contact name (if provided), meeting date, meeting type (if provided)

Step 5: Self-QA

Check before presenting:

  • No invented data. Every fact has a source URL from Tavily results.
  • Talking points use "Because [finding], mention [point] to [goal]" format
  • No em dashes in any line
  • No banned words
  • Brief is under 400 words
  • Decision Maker section says "Not specified" if no contact was provided
  • Sections with no data say "Limited public information found" rather than guessing
  • Open questions are specific to this company, not generic

Fix any violation before presenting.


Step 6: Output or Save to Notion

Present the full brief in a code block.

If NOTION_TOKEN and NOTION_DATABASE_ID are both set, ask: "Save this brief to Notion?"

On confirmation:

bash
cat > /tmp/notion-brief-payload.json << 'ENDJSON'
{
  "parent": { "database_id": "NOTION_DATABASE_ID_HERE" },
  "properties": {
    "Name": {
      "title": [{ "text": { "content": "Meeting Brief: COMPANY, DATE" } }]
    },
    "Date": {
      "date": { "start": "YYYY-MM-DD" }
    }
  },
  "children": [
    {
      "object": "block",
      "type": "paragraph",
      "paragraph": {
        "rich_text": [{ "type": "text", "text": { "content": "BRIEF_CONTENT_HERE" } }]
      }
    }
  ]
}
ENDJSON
curl -s -X POST "https://api.notion.com/v1/pages" \
  -H "Authorization: Bearer $NOTION_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Notion-Version: 2022-06-28" \
  -d @/tmp/notion-brief-payload.json

After posting: "Brief saved to Notion. Check your database."

If Notion is not configured: present the brief only. Do not mention Notion.

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 Meeting Brief Generator AI skill do?

Takes a company name and optional contact, runs targeted research via Tavily, synthesizes a 1-page pre-call brief with Gemini, and optionally saves it to Notion. Use when asked to prepare for a meeting, research a prospect before a call, generate a company brief, create a pre-call summary, or write a meeting prep doc. Trigger when a user says "prepare me for a meeting with", "research this company before my call", "generate a meeting brief for", "I have a call with X tomorrow", or "create a prospect brief for".

Why use Meeting Brief Generator on TypingMind?

Because you install it once and use it with any model. Meeting Brief Generator 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 Meeting Brief Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Varnan-Tech/opendirectory/tree/main/skills/meeting-brief-generator. 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 Meeting Brief Generator?

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 Meeting Brief Generator?

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

Is the Meeting Brief Generator AI skill free?

Yes. It is published on GitHub by Varnan-Tech under the MIT license. 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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