email-finder-tomba

email-finder-tomba is a skill for Claude Code, Codex from gooseworks-ai/goose-skills. It costs 22 tokens per session (3,468 once invoked), scanned A, original, MIT.

An email-finding and verification tool for discovering work email addresses from company domains, LinkedIn profiles, or company searches.

In plain words
What is it for?
Use it to find prospect contacts, check email formats, verify phone numbers, and retrieve person or company details.
Why use it?
It helps determine how to contact a person or company and whether an address or domain is valid.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to find prospect contacts, check email formats, verify phone numbers, and retrieve person or company details.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gooseworks-ai/goose-skills/email-finder-tomba
About the project

Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.

gooseworks-ai/goose-skills · 1,202 stars · on GitHub · gooseworks.ai

Install

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.

Any agent
npx skills add gooseworks-ai/goose-skills --skill email-finder-tomba
Clone the repo
git clone --depth 1 https://github.com/gooseworks-ai/goose-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for email-finder-tomba

README.md
[![agentmods](https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/email-finder-tomba/github.svg)](https://agentmods.dev/skills/gooseworks-ai/goose-skills/email-finder-tomba)
Your own site
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/email-finder-tomba"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/email-finder-tomba/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.

agentmods 80×15 button for email-finder-tomba

Your own site · 80×15
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/email-finder-tomba"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/email-finder-tomba.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,468 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 6 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 12
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 14
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 15
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 18
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • medium MCP Rug Pull · line 18
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium Data Exfiltration · line 58
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.03468
Opus 5 $0.00011 $0.01734
Sonnet 5 $0.00004 $0.00694
Haiku 4.5 $0.00002 $0.00347

Measured 9d ago against content hash 4b18f82ae008, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

email-finder-tomba scanned grade A with 1 finding 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 9d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
skills/lead-generation/capabilities/email-finder-tomba/SKILL.md · 350 lines

How it starts

The opening of the file, as written. The whole thing — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tomba - Email Finding & Verification

Setup

Read your credentials from ~/.gooseworks/credentials.json:

export GOOSEWORKS_API_KEY=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json'))['api_key'])")
export GOOSEWORKS_API_BASE=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json')).get('api_base','https://api.gooseworks.ai'))")

If ~/.gooseworks/credentials.json does not exist, tell the user to run: npx gooseworks login

All endpoints use Bearer auth: -H "Authorization: Bearer $GOOSEWORKS_API_KEY"

Find and verify email addresses from domains, LinkedIn profiles, or natural language search.

Capabilities

  • Validate Phone: Validate a phone number and get carrier information
  • Domain Status: Check the status and availability of a domain
  • Email Format: Get the email format patterns used by a domain (e.g. first.last, firstlast)
  • Find Person: Get person information from an email address
  • Combined Enrichment: Get combined person and company information from an email
  • Domain Suggestions: Get domain suggestions for a company name
  • Email Count: Get the count of email addresses for a domain, broken down by department and seniority
  • Author Finder: Find the email address of a blog post author from the article URL
  • LinkedIn Finder: Find the email address from a LinkedIn profile URL
  • Technology Stack: Discover technologies used by a website
  • Verify Email: Verify the deliverability of an email address
  • Find Company: Get company information from a domain
  • Location: Get employee location distribution for a domain
  • Domain Search: Search emails based on a website domain
  • Email Enrichment: Enrich an email address with person and company data (name, location, social handles)
  • Find Phone: Find phone numbers associated with an email, domain, or LinkedIn profile
  • Similar Domains: Find domains similar to a given domain
  • Email Finder: Find the most likely email address from a domain name, first name, and last name
  • Email Sources: Find the sources where an email was found on the web
  • Search Companies: Search for companies using natural language queries or structured filters

Read the full file on GitHub · 350 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 9d ago First seen · 350 lines · 22 tokens per session scan A 4b18f82ae008

Subscribe to this mod's changes

email-finder-tomba is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 22 tokens to every session and 3,468 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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