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Enrich Lead

Official
anthropics·vlatest·marketing·Apache-2.0

Enrich Lead identifies and expands upon user-provided information to generate more detailed and insightful responses, boosting knowledge and understanding.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add anthropics/knowledge-work-plugins --skill enrich-lead -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

anthropics

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned anthropics/knowledge-work-plugins at da38ec1ee8.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
da38ec1ee8
Manifest
partner-built/apollo/skills/enrich-lead/SKILL.md
Scanned
1 file, 81 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The enrich-lead skill allows AI agents to retrieve and expand raw contact information into comprehensive profiles. It connects with external data sources to fill gaps in names, titles, company details, and professional backgrounds. This capability transforms basic leads into actionable insights for sales and marketing workflows.

When to use it

  • Converting cold outreach lists by adding missing context about potential clients.
  • Preparing personalized email campaigns by verifying job titles and current roles.
  • Enriching CRM entries with real-time professional history before a sales call.
  • Validating lead accuracy against public databases to ensure up-to-date contact details.

Key capabilities

  • Fetches missing fields from external knowledge bases or APIs.
  • Aggregates data points like company size, industry, and tenure.
  • Updates raw input records with verified professional attributes.
  • Integrates seamlessly into existing agent workflows for immediate data augmentation.

Example prompts

  • "Enrich this list of 50 leads from our CSV file by adding their current job titles and LinkedIn profiles."
  • "Look up the full professional background for these three prospects, including their previous companies and education."
  • "Take these raw email addresses and return a structured profile with company name, industry sector, and estimated seniority level."

Tips & gotchas

Ensure your input data includes at least one unique identifier (like an email or company name) to guarantee accurate matching. Be aware that external data sources may have latency; results reflect the most recent available information rather than real-time changes.