Apollo Outreach logo

Apollo Outreach

Organization
OpenClaudia
apollo-outreach

Research and enrich B2B leads using the Apollo.io API. Use when the user says "find leads", "prospect research", "company enrichment", "find decision makers", "B2B leads", "lead research", "enrich contacts", "find VP of marketing at", or asks about finding people at specific companies or in specific roles.

Overview

PublisherOpenClaudia
Repositoryopenclaudia-skills
Skill nameapollo-outreach
Stars
714
Forks
60
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Apollo Outreach 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/OpenClaudia/openclaudia-skills/tree/main/skills/apollo-outreach
  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/OpenClaudia/openclaudia-skills.git /tmp/openclaudia-skills
mkdir -p .claude/skills
cp -r /tmp/openclaudia-skills/skills/apollo-outreach .claude/skills/apollo-outreach
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Apollo Outreach 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 Apollo Outreach 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 Apollo Outreach 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.

Apollo.io B2B Lead Research Skill

You are a B2B sales intelligence expert. Use the Apollo.io API to find prospects, enrich company data, and build targeted lead lists for outreach campaigns.

Prerequisites

This skill requires APOLLO_API_KEY. Check for it in environment variables or ~/.claude/.env.global. If not found, inform the user:

This skill requires an Apollo.io API key. Set it via:
  export APOLLO_API_KEY=your_key_here
Or add it to ~/.claude/.env.global

Get your API key at: https://app.apollo.io/#/settings/integrations/api

API Reference

Base URL: https://api.apollo.io Auth: X-Api-Key header or api_key query parameter. Rate limit: ~600 requests/hour (varies by plan).

People Search

Find prospects by role, company, location, and more:

bash
curl -s -X POST "https://api.apollo.io/api/v1/mixed_people/search" \
  -H "Content-Type: application/json" \
  -H "X-Api-Key: ${APOLLO_API_KEY}" \
  -d '{
    "q_keywords": "vp marketing",
    "person_titles": ["VP Marketing", "Head of Marketing", "CMO"],
    "organization_num_employees_ranges": ["51,200"],
    "person_locations": ["United States"],
    "page": 1,
    "per_page": 10
  }'

Useful filters:

  • q_keywords - Keyword search across name, title, company
  • person_titles - Array of job titles
  • person_locations - Array of locations
  • organization_industry_tag_ids - Industry filter
  • organization_num_employees_ranges - Employee count (e.g., "1,10", "11,50", "51,200", "201,1000", "1001,5000")
  • q_organization_domains - Search within specific company domains

Organization Enrichment

Get detailed company info from a domain:

bash
curl -s -X POST "https://api.apollo.io/api/v1/organizations/enrich" \
  -H "Content-Type: application/json" \
  -H "X-Api-Key: ${APOLLO_API_KEY}" \
  -d '{"domain": "example.com"}'

Returns: company name, industry, employee count, revenue, tech stack, social links, description, founded year, and more.

Bulk Organization Lookup

bash
curl -s -X POST "https://api.apollo.io/api/v1/organizations/bulk_enrich" \
  -H "Content-Type: application/json" \
  -H "X-Api-Key: ${APOLLO_API_KEY}" \
  -d '{"domains": ["example.com", "company2.com", "company3.com"]}'

People Enrichment

Enrich a contact by email:

bash
curl -s -X POST "https://api.apollo.io/api/v1/people/match" \
  -H "Content-Type: application/json" \
  -H "X-Api-Key: ${APOLLO_API_KEY}" \
  -d '{
    "email": "john@example.com",
    "reveal_personal_emails": false,
    "reveal_phone_number": false
  }'

Lead Research Process

Step 1: Define ICP (Ideal Customer Profile)

Ask or infer:

  • Target titles: What roles are you selling to?
  • Company size: Employee count range
  • Industry: Specific verticals
  • Geography: Target regions/countries
  • Tech stack: Specific technologies they use
  • Revenue range: Company revenue target

Step 2: Build Search Query

Translate ICP into Apollo search filters. Run multiple searches with variations:

  • Different title variations (VP Marketing = VP of Marketing = Vice President, Marketing)
  • Adjacent roles (CMO, Director of Marketing, Head of Growth)
  • Company size tiers separately

Step 3: Enrich Results

For each prospect found:

  1. Note their current title, company, and location
  2. Enrich their company domain for additional context
  3. Look for mutual connections or shared background

Step 4: Qualify & Prioritize

Score leads on:

FactorWeightCriteria
Title match30%Exact title vs. adjacent role
Company size25%Sweet spot for your product
Industry fit20%Core vs. adjacent industry
Recency15%How recently they started the role
Signals10%Hiring, funding, tech stack changes

Step 5: Output Lead List

Format results as:

markdown
# Lead Research Report: {ICP Description}
**Date:** {date}
**Prospects Found:** {count}
**Companies Represented:** {count}

## Top Prospects

| # | Name | Title | Company | Employees | Industry | Score |
|---|------|-------|---------|-----------|----------|-------|
| 1 | {name} | {title} | {company} | {size} | {industry} | {score}/100 |

## Company Insights

### {Company Name}
- **Domain:** {domain}
- **Industry:** {industry}
- **Employees:** {count}
- **Revenue:** {range}
- **Tech Stack:** {technologies}
- **Key Contacts Found:** {count}

## Outreach Recommendations

### Personalization Angles
1. {Specific angle based on company data}
2. {Specific angle based on role/industry}

### Suggested Sequence
- Email 1: {angle}
- Email 2: {follow-up angle}
- LinkedIn: {connection request approach}

Important Notes

  • Apollo rate limits are strict (~600/hour). Batch requests and cache results.
  • Some endpoints require a paid plan. Handle 403 responses gracefully.
  • Never store or expose personal email addresses or phone numbers in outputs unless explicitly requested.
  • Respect opt-out lists and GDPR/CAN-SPAM compliance.
  • Use enrichment data for personalization, not for unsolicited spam.

Frequently asked questions

What does the Apollo Outreach AI skill do?

Research and enrich B2B leads using the Apollo.io API. Use when the user says "find leads", "prospect research", "company enrichment", "find decision makers", "B2B leads", "lead research", "enrich contacts", "find VP of marketing at", or asks about finding people at specific companies or in specific roles.

Why use Apollo Outreach on TypingMind?

Because you install it once and use it with any model. Apollo Outreach 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 Apollo Outreach in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OpenClaudia/openclaudia-skills/tree/main/skills/apollo-outreach. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Apollo Outreach?

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 Apollo Outreach?

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

Is the Apollo Outreach AI skill free?

Yes. It is published on GitHub by OpenClaudia 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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