Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add openteams-lab/openteams --skill apollo-automationgit clone --depth 1 https://github.com/openteams-lab/openteamsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/openteams-lab/openteams/apollo-automation)<a href="https://agentmods.dev/skills/openteams-lab/openteams/apollo-automation"><img src="https://agentmods.dev/badge/skills/openteams-lab/openteams/apollo-automation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/openteams-lab/openteams/apollo-automation"><img src="https://agentmods.dev/badge/skills/openteams-lab/openteams/apollo-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.01770 |
| Opus 5 | $0.00020 | $0.00885 |
| Sonnet 5 | $0.00008 | $0.00354 |
| Haiku 4.5 | $0.00004 | $0.00177 |
Grade A, and why
Apollo Automation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
3 near-identical copies found in the catalogue:
- Apollo Automation — 100% identical, 0 lines differ
- apollo-automation — 100% identical, 2 lines differ
- Apollo Automation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apollo Automation
Supercharge your sales prospecting with Apollo.io -- search companies, discover decision-makers, enrich contact data with emails and phone numbers, and manage your sales pipeline stages -- all through natural language commands.
Toolkit docs: composio.dev/toolkits/apollo
Setup
- Add the Composio MCP server to your client configuration:
https://rube.app/mcp - Connect your Apollo.io account when prompted (API key authentication).
- Start issuing natural language commands to prospect and enrich leads.
Core Workflows
1. Search Organizations
Find target companies using filters like name, location, employee count, and industry keywords.
Tool: APOLLO_ORGANIZATION_SEARCH
Example prompt:
"Find SaaS companies in Texas with 50-500 employees on Apollo"
Key parameters:
q_organization_name-- Partial name match (e.g., "Apollo" matches "Apollo Inc.")organization_locations-- HQ locations to include (e.g., "texas", "tokyo")organization_not_locations-- HQ locations to excludeorganization_num_employees_ranges-- Employee ranges in "min,max" format (e.g., "50,500")q_organization_keyword_tags-- Industry keywords (e.g., "software", "healthcare")page/per_page-- Pagination (max 100 per page, max 500 pages)
2. Discover People at Companies
Search Apollo's contact database for people matching title, seniority, location, and company criteria.
Tool: APOLLO_PEOPLE_SEARCH
Example prompt:
"Find VPs of Sales at microsoft.com and apollo.io"
Key parameters:
person_titles-- Job titles (e.g., "VP of Sales", "CTO")person_seniorities-- Seniority levels (e.g., "director", "vp", "senior")person_locations-- Geographic locations of peopleq_organization_domains-- Company domains (e.g., "apollo.io" -- exclude "www.")organization_ids-- Apollo company IDs from Organization Searchcontact_email_status-- Filter by email status: "verified", "unverified", "likely to engage"page/per_page-- Pagination (max 100 per page)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 166 lines · 41 tokens per session scan A 8ebd4d46135e
Apollo Automation is a skill published in the GitHub repository openteams-lab/openteams (612 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 1,770 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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