Agent skill

Apollo Lead Finder

by gooseworks-ai in gooseworks-ai/goose-skills

Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact).

MITAuto-check: notesBackend & APIs

Install Apollo Lead Finder

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill apollo-lead-finder -a claude-code

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

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills apollo-lead-finder --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/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/lead-generation/capabilities/apollo-lead-finder .claude/skills/apollo-lead-finder && 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
apollo-lead-finder
GitHub stars
1.2k
Used in
1 other repo
Token cost
~2k tokens
SKILL.md length
931 words
Files
3 (incl. scripts)
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact).

  • Works in 4 steps: Intake → Search (FREE) → Enrich (COSTS CREDITS) → …
  • Tasks that involve GraphQL
  • SKILL.md covers Prerequisites, Phase 0: Intake, Phase 1: Search (FREE) and Database Write Policy, plus 4 more sections
  • Runs Python scripts from its folder; reaches api.apollo.io; needs APOLLO_API_KEY

What it does

Apollo Lead Finder is an agent skill from gooseworks-ai/goose-skills. Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Creates Apollo lists. Deduplicates against existing contacts by LinkedIn URL.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/apollo_client.py` and `skill.meta.json`).

It sits in Backend & APIs, covering GraphQL, OSINT and Cold outreach. It works with LinkedIn. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.

When your agent uses it

  • Tasks that involve GraphQL
  • Tasks that involve OSINT
  • Tasks that involve Cold outreach

Example prompts

  • “/apollo-lead-finder”

Requirements

  • Python 3
  • A credential in APOLLO_API_KEY

Workflow steps

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

  1. Intake
  2. Search (FREE)
  3. Enrich (COSTS CREDITS)
  4. Review & Refine

What it can do on your machine

Read from SKILL.md and the folder at commit c650c6d. 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

    Ships 1 file in scripts/ (Python), which the agent can run.

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.apollo.io

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • APOLLO_API_KEY

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

Context cost

Apollo Lead Finder loads about 2k tokens when it runs. Until then it costs about 63 tokens; SKILL.md has 931 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~63
When it runs · the whole SKILL.md, loaded when a task matches
~2k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:20
    o Settings > Integrations > API. Add to `.env`:

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); the scripts in this folder are not scanned.

SKILL.md

The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 931 words, ~1,986 tokens.

Download SKILL.mdSave it as .claude/skills/apollo-lead-finder/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
apollo-lead-finder
description
Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Creates Apollo lists. Deduplicates against existing contacts by LinkedIn URL.
tags
lead-generation

Apollo Lead Finder

Two-phase Apollo.io prospecting: free People Search for lead discovery, then selective paid enrichment to reveal emails and phone numbers. Creates Apollo lists and contacts.

Key advantage: Apollo People Search is free (no credits consumed). Credits are only spent when enriching contacts to reveal email/phone. This lets you search tens of thousands of leads at zero cost, review results, then selectively enrich only the best matches.

Prerequisites

Apollo API Key

Get your API key from Apollo.io Settings > Integrations > API. Add to .env:

APOLLO_API_KEY=your-api-key-here

That's it — one env var.

Phase 0: Intake

Ask the user these questions to build the Apollo filter config:

ICP Criteria
  1. What job titles are you targeting? (e.g., "VP of Sales", "Head of Growth")
  2. What seniority levels? Options: owner, founder, c_suite, partner, vp, director, manager, senior, entry
  3. Company size (employee range)? Format: "51,200" "201,500" "501,1000" "1001,5000"
  4. Geographic regions? (e.g., "United States", "San Francisco, California")
  5. Industry/keyword tags? (e.g., "SaaS", "Software", "FinTech")
  6. Any titles to exclude? (e.g., "intern", "assistant")
  7. Should we create an Apollo list with these contacts? (default: yes)
  8. How many results do you want? (test: 100, standard: 5,000, full: 50,000)
Map Answers to Config

Build the config JSON with Apollo's filter format:

json
{
  "client_name": "example-client",
  "search_config_name": "vp-sales-us-midmarket",
  "icp_segment": "sales-leaders",
  "apollo_filters": {
    "person_titles": ["VP of Sales", "Head of Sales", "Director of Sales"],
    "person_seniority": ["vp", "director"],
    "person_locations": ["United States"],
    "organization_num_employees_ranges": ["51,200", "201,500", "501,1000"],
    "q_organization_keyword_tags": ["SaaS", "Software"]
  },
  "enrichment_filters": {
    "exclude_titles_containing": ["intern", "assistant"]
  },
  "apollo_list_name_prefix": "example-sales-leaders",
  "create_apollo_list": true,
  "mode": "standard",
  "max_pages": 50
}

Available Apollo search filters:

  • person_titles — job title keywords (array of strings)
  • person_seniority — seniority levels: owner, founder, c_suite, partner, vp, director, manager, senior, entry
  • person_locations — geographic locations (array of strings)
  • organization_num_employees_ranges — employee count ranges, format "min,max" (e.g., "51,200")
  • q_organization_keyword_tags — company keyword tags (e.g., "SaaS", "Software")
  • person_not_titles — titles to exclude (array of strings)
  • q_organization_name — organization name search
  • organization_locations — company HQ locations

Phase 1: Search (FREE)

What the free search returns

Apollo's api_search endpoint returns limited preview data: Apollo person ID, first name, obfuscated last name, title, company name, and boolean flags (has_email, has_phone). No LinkedIn URLs, emails, or full names — those require enrichment.

Pipeline Steps

Step 1: Build Apollo search payload — Map config filters to Apollo People Search format.

Step 2: Search page 1 — Get first 100 results + total_entries for total count.

Step 3: Paginate — Fetch remaining pages (100 per page, up to mode cap). Apply title filters.

Step 4: Collect Apollo person IDs — Store the Apollo person IDs from search results for the enrich phase.

Step 5: Present preview — Show the user a sample of search results (first name, title, company) and total count. Ask for approval before enriching.

Mode Caps
ParameterTestStandardFull
Max pages150500
Max results1005,00050,000
Search credits000

Cost: FREE. People Search does not consume Apollo credits.

Database Write Policy

CRITICAL: Never export leads without explicit user approval.

The search phase is free. The enrich phase costs credits.

Required flow:

  1. Run search first (free) — review the results
  2. Present search results to the user: total matches, sample leads, title distribution
  3. Get explicit user approval before running enrich phase
  4. After enrichment, present the enriched results to the user before exporting
  5. Only export after the user confirms the results look good

Phase 2: Enrich (COSTS CREDITS)

Use the Apollo Bulk People Match API to enrich selected leads from Phase 1.

Show full SKILL.md (414 more words)Show less
Pipeline Steps

Step 1: Load search manifest — Read the manifest JSON saved by the search phase. Contains Apollo person IDs.

Step 2: Load existing contacts for dedup — If the user has a CSV of existing contacts or a previous export, load LinkedIn URLs for dedup. If no existing data, skip dedup.

Step 3: Confirm credits — Display lead count and credit cost estimate. Wait for confirmation.

Step 4: Bulk enrich — Call /people/bulk_match with Apollo person IDs in batches of 10. Each match costs 1 credit. Returns full data: email, phone, LinkedIn URL, full name, location, company details.

Step 5: Dedup against existing contacts — Filter out leads whose LinkedIn URLs already exist in the user's contact list.

Step 6: Present results to user — Show enriched sample leads (names, titles, companies, email coverage) and ask for explicit approval before writing to the database.

Step 7: Export results — Only after user approval. Save enriched leads as CSV to the current working directory, or wherever the user prefers.

Mode Caps
ParameterTestStandardFull
Max enrichments105002,500
Credits used105002,500

Cost: 1 credit per contact enriched. Always run search first, review results, then selectively enrich.

Phase 3: Review & Refine

Present results:

  • Total matching — how many profiles match the filters in Apollo
  • New leads found — net-new profiles (after dedup)
  • Apollo list — name and link to the list in Apollo
  • Enriched — how many have emails revealed
  • Email coverage — percentage of enriched leads with valid emails
  • Top 10 leads — name, title, company preview

Common adjustments:

  • Too broad — add more filters (seniority, employee range, keyword tags)
  • Too narrow — broaden title list, remove location filters
  • Low email coverage — some contacts genuinely have no known email; try enriching more leads
  • Wrong ICP — adjust title include/exclude lists

Example Usage

Trigger phrases:

  • "Search Apollo for [titles] at [industries]"
  • "Find leads in Apollo matching my ICP"
  • "Find VP of Sales at SaaS companies in the US"
  • "Enrich the Apollo leads from last search"

Apollo API Reference

  • People Search: POST https://api.apollo.io/api/v1/mixed_people/api_search — FREE, returns Apollo IDs + preview data (first name, title, org name, boolean flags). No LinkedIn URLs or emails.
  • People Match (enrich): POST https://api.apollo.io/api/v1/people/match — 1 credit, reveals email/phone
  • Bulk People Match: POST https://api.apollo.io/api/v1/people/bulk_match — up to 10 per request, 1 credit each
  • Create List: POST https://api.apollo.io/api/v1/labels — create a named list
  • Create Contact: POST https://api.apollo.io/api/v1/contacts — add person to Apollo CRM + optional list
  • Auth: x-api-key: {APOLLO_API_KEY} header on all requests
  • Rate limit: Varies by plan. Handle 429 with Retry-After header.
  • Search Pagination: page param (1-indexed), per_page max 100

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

Files

SKILL.md and 2 other files (scripts) in skills/lead-generation/capabilities/apollo-lead-finder of gooseworks-ai/goose-skills.

  • SKILL.md
  • scripts/apollo_client.py
  • skill.meta.json

Open the folder on GitHubat commit c650c6d

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Apollo Lead Finder 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.

Apollo Lead Finder compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Apollo Lead Finder this skillgooseworks-ai/goose-skills1.2k1 repos~2kAutomated safety check: NotesMIT
Linkedin Comment To Outreachgethouston/houston118—~2.1kAutomated safety check: PassMIT
Lead Intelligenceaffaan-m/ECC276k—~1.5kAutomated safety check: PassMIT
Lead IntelligenceaAAaqwq/AGI-Super-Team1053 repos~2.8kAutomated safety check: PassMIT
Apollo Core Workflow Ajeremylongshore/tons-of-skills-marketplace2.8k—~2.1kAutomated safety check: PassMIT
Sales OsromangojiberryAI/gojiberryai-sales-os139—~2kAutomated safety check: PassMIT

Similar skills

  • Turn a single LinkedIn post URL into a paused cold email campaign in Instantly.

    118 GitHub stars~2.1k tokensUpdated today
    Writing & ContentAuto-check passed
  • Lead Intelligence

    affaan-m/ECC

    AI原生的潜在客户情报与外联管道。取代Apollo、Clay和ZoomInfo,提供基于代理的信号评分、相互排名、温暖路径发现、来源驱动的语音建模以及跨电子邮件、LinkedIn和X的渠道特定外联。当用户想要查找、筛选并联系高价值联系人时使用。

    276k GitHub stars~1.5k tokensUpdated yesterday
    Backend & APIsAuto-check passed
  • Lead Intelligence

    aAAaqwq/AGI-Super-Team

    AI-native lead intelligence and outreach pipeline. An agent skill from aAAaqwq/AGI-Super-Team.

    105 GitHub starsUsed in 3 repos~2.8k tokens
    Backend & APIsAuto-check passed
  • Apollo Core Workflow A

    jeremylongshore/tons-of-skills-marketplace

    Implement Apollo.io lead search and enrichment workflow. An agent skill from jeremylongshore/tons-of-skills-marketplace.

    2.8k GitHub stars~2.1k tokensUpdated yesterday
    Backend & APIsAuto-check passed
  • Sales Os

    romangojiberryAI/gojiberryai-sales-os

    A complete outbound sales department in one skill. An agent skill from romangojiberryAI/gojiberryai-sales-os.

    139 GitHub stars~2k tokensUpdated 1 mo ago
    Sales & SupportAuto-check passed
  • Social Selling

    tech-leads-club/agent-skills

    When the user wants to sell through social media, optimize LinkedIn for sales, build DM sequences, or convert content engagement into pipeline.

    7k GitHub stars~4.9k tokensUpdated 2 days ago
    DevelopmentAuto-check passed

More from gooseworks-ai/goose-skills

All 273 skills in this repo
  • Reddit Post Finder

    gooseworks-ai/goose-skills

    Scrape and search Reddit posts using Apify. An agent skill from gooseworks-ai/goose-skills.

    1.2k GitHub starsUsed in 1 repo~1.2k tokens
    Auto-check passed
  • Create Image Fal

    gooseworks-ai/goose-skills

    Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent.

    1.2k GitHub stars~1.3k tokensUpdated yesterday
    Auto-check passed
  • Render Hook Replacement

    gooseworks-ai/goose-skills

    Replace an existing video's opening with a supplied clip or free kinetic text hook while retaining and verifying every original body frame, audio, captions and ending.

    1.2k GitHub stars~2.3k tokensUpdated yesterday
    Auto-check passed
  • Blog Feed Monitor

    gooseworks-ai/goose-skills

    Scrape blog posts via RSS feeds (free, no API key) with Apify fallback for JS-heavy sites.

    1.2k GitHub starsUsed in 1 repo~578 tokens
    Auto-check passed
  • Competitor Post Engagers

    gooseworks-ai/goose-skills

    Find leads by scraping engagers from a competitor's top LinkedIn posts.

    1.2k GitHub starsUsed in 1 repo~1.8k tokens
    Auto-check: notes
  • Render Chatgpt Chat

    gooseworks-ai/goose-skills

    Assemble a ChatGPT chat-reveal video ad from a thread + timeline JSON — one continuous Playwright recording of a ChatGPT mobile chat (user types with the iOS keyboard up → taps send → keyboard…

    1.2k GitHub stars~2.3k tokensUpdated yesterday
    Auto-check passed

Works with

Questions about Apollo Lead Finder

What does Apollo Lead Finder do?

Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Apollo Lead Finder is an agent skill from gooseworks-ai/goose-skills.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact).

When should I use Apollo Lead Finder?

Apollo Lead Finder fits situations like: tasks that involve GraphQL; tasks that involve OSINT; tasks that involve Cold outreach.

How do I install Apollo Lead Finder in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill apollo-lead-finder -a claude-code`. Or copy the skill folder (skills/lead-generation/capabilities/apollo-lead-finder in gooseworks-ai/goose-skills) into .claude/skills/apollo-lead-finder in your project. Claude Code loads it when a task matches its description.

How do I install Apollo Lead Finder in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill apollo-lead-finder -a codex`. Or copy the skill folder (skills/lead-generation/capabilities/apollo-lead-finder in gooseworks-ai/goose-skills) into .agents/skills/apollo-lead-finder in your project. Codex loads it when a task matches its description.

Can I use Apollo Lead Finder 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 gooseworks-ai/goose-skills --skill apollo-lead-finder -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/apollo-lead-finder, .gemini/skills/apollo-lead-finder, .github/skills/apollo-lead-finder and .opencode/skills/apollo-lead-finder in your project.

What does Apollo Lead Finder need to run?

Going by SKILL.md and its folder, Apollo Lead Finder needs Python for the scripts in its folder and credentials named APOLLO_API_KEY. Our summary lists: Python 3; A credential in APOLLO_API_KEY.

Does Apollo Lead Finder access the network?

SKILL.md names 1 domain. In commands or code: api.apollo.io; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Apollo Lead Finder safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Apollo Lead Finder use?

Apollo Lead Finder 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 Apollo Lead Finder use?

About 2k tokens (SKILL.md is roughly 7.9k 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 Apollo Lead Finder?

Skills that share tags, products or a category with Apollo Lead Finder: Linkedin Comment To Outreach (gethouston/houston, 118 stars), Lead Intelligence (affaan-m/ECC, 276k stars), Lead Intelligence (aAAaqwq/AGI-Super-Team, 105 stars) and Apollo Core Workflow A (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Apollo Lead Finder?

gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.

Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.