Enrich Contact

Organization

explorium-ai

enrich-contact

Contact enrichment skill for Claude Code and Codex: look up a B2B prospect's full professional profile including work email, phone number, LinkedIn profile, title, seniority, department, and company firmographics. Provide an email, name + company, LinkedIn URL, or prospect_id. Use for contact data enrichment, email lookup, LinkedIn profile lookup, and outbound contact data workflows in Claude Code, Codex, Hermes-Agent, and other AI agents.

Overview

Publisher	explorium-ai
Repository	`gtm-skills`
Skill name	`enrich-contact`
Stars	293
Forks	3
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 explorium-ai on GitHub. Read the source before you install it.

Installation

Install the Enrich Contact AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/explorium-ai/gtm-skills/tree/main/skills/enrich-contact
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.

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/explorium-ai/gtm-skills.git /tmp/gtm-skills
mkdir -p .claude/skills
cp -r /tmp/gtm-skills/skills/enrich-contact .claude/skills/enrich-contact

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Enrich Contact 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 Enrich Contact 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 Enrich Contact 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.

Enrich Contact

Resolve one person and return their full enriched profile in a single pass.

Input

The user will supply one of:

An email address (e.g. jane@acme.com)
A full name plus a company name or domain (e.g. Jane Smith at Acme Corp)
A LinkedIn profile URL
A known Explorium prospect_id

Optional: a request for company context (firmographics on the matched employer).

Workflow

Classify the identifier. Pick exactly one resolution path: do not fan out match strategies in parallel. Use the strongest signal first and fall back only if it returns no match.
- Email present and well-formed: path A.
- LinkedIn URL: path B.
- Bare prospect_id: path D, skip resolution.
- Full name plus a company token: path C.
- Phone-only: stop and tell the user phone-only is not a supported match key.
Resolve the prospect.
- Path A: match the prospect by email.
- Path B: match the prospect by LinkedIn URL.
- Path C: if the user gave a company name, first resolve the business to get its canonical domain and business_id, then match the prospect by full name plus that company domain or id.
- Path D: use the supplied id directly.
Handle ambiguity. If matching returns zero rows:
- For path A, retry by splitting the email local-part into a name guess plus the company domain.
- For path C, retry with first/last name and the resolved business_id from a company match.
- If multiple plausible rows return, surface a candidates table and ask the user to pick. Never silently take the first row.
Enrich the prospect. Pull contacts and profile on the resolved person. Default to email-only contacts (cheaper); upgrade to email plus phone only when the user explicitly needs phone numbers (e.g. SDR dialer flows).
- Recent LinkedIn post content for an individual is not available. If the user asks for post content, surface this gap and offer the employer's LinkedIn posts via business enrichment instead.
Optional company context. If the user asked for company context (or path C resolved a business_id), enrich firmographics on the employer and surface headcount, revenue range, country, and industry.
Assemble the output. Render the card below. Omit empty fields. Always surface the prospect_id.

Output Format

[Full Name] at [Company]

Field	Value
Job Title
Job Level	display canonical (e.g. `c-suite`, `vice president`)
Job Department	fallback "Unattributed" when null
Professional Email / Personal Email / Phone
LinkedIn URL
Company / Domain / Industry
Company Size / Revenue / Country	buckets
prospect_id / business_id

If multiple candidates surfaced during resolution and the user has not yet picked, render a ### Candidates table instead, with one row per candidate (name, title, company, domain, prospect_id) and ask which to enrich.

Limitations

High-profile public execs (CEOs, founders, well-known executives) often have suppressed contact data. Professional email may be null or only a personal address. Recommend LinkedIn outreach instead of cold email for this tier.
Phone-only lookup is not a supported match key.
No per-prospect accuracy or confidence score. Treat the presence of a professional email plus phone as the practical quality signal.
No last_updated timestamp per contact field. Level and department are coarse buckets; department is null for many cross-functional senior roles (Chief X Officer, President, Founder), group under "Unattributed".
Company size and revenue are bucketed, not exact numbers.

Frequently asked questions

What does the Enrich Contact AI skill do?

Why use Enrich Contact on TypingMind?

Because you install it once and use it with any model. Enrich Contact 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 Enrich Contact in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/explorium-ai/gtm-skills/tree/main/skills/enrich-contact. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Enrich Contact?

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 Enrich Contact?

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

Is the Enrich Contact AI skill free?

Yes. It is published on GitHub by explorium-ai 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Enrich Contact

Input

Workflow

Output Format

Limitations

Frequently asked questions

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