A strategic lead generation skill that builds high-intent company lists using the Extruct API and specialized search methodologies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install extruct-list-building
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install extruct-list-building using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is List Building?
The List Building skill is a sophisticated tool within the Openclaw Skills ecosystem designed to automate and optimize the process of identifying target accounts. It acts as a strategic layer over the Extruct API, utilizing a logic-driven decision tree to determine whether a lookalike search, semantic search, or deep search is most appropriate for a given campaign. By analyzing company context, ICP profiles, and historical win cases, it ensures that every generated prospect list is grounded in data and aligned with specific business goals.
This skill goes beyond simple database queries by employing advanced research techniques. It handles the 'what' and 'why' of prospecting—designing multi-angle queries and qualifying criteria—while delegating technical execution to the underlying API infrastructure. This results in a feedback loop where enrichment insights constantly refine the list building parameters, ensuring high-conversion potential for outbound teams.
List Building Use Cases
- Building targeted prospect lists for cold outbound campaigns based on Ideal Customer Profiles (ICP).
- Discovering market segments and competitive landscapes through semantic company search.
- Creating target account lists using seed domains from existing high-value customers via lookalike search.
- Conducting deep, qualified research to score companies against specific technical or business criteria.
- Scaling lead generation from initial exploration (50 companies) to full-scale campaigns (2000+ companies).
How List Building Works
- Context Analysis: The skill reads local context files to extract ICP definitions, previous win cases, and Do Not Contact (DNC) lists.
- Strategic Selection: It applies a decision tree to choose between Method 1 (Lookalike), Method 2 (Semantic), or Method 3 (Deep Search) based on available data.
- Query Engineering: For the chosen method, it drafts targeted queries (3-5 for broad search or detailed job-description style queries for deep search).
- API Delegation: It passes the generated queries to the extruct-api to execute the actual search operations.
- Data Refinement: Results are collected, deduplicated by domain, and filtered against the DNC list to ensure compliance.
- Table Integration: The final list is uploaded to an Extruct company table where it is automatically enriched with full company profiles.
List Building Setup
To use this skill within the Openclaw Skills framework, ensure your environment is configured with the necessary context files and the extruct-api skill is available.
# Ensure the company context exists
mkdir -p claude-code-gtm/context/
touch claude-code-gtm/context/{your_company}_context.md
# The skill will automatically trigger on commands like:
# "Find companies similar to stripe.com"
# "Build a list of Series A fintech startups in London"
List Building Data Schema & Taxonomy
The skill organizes lead data into a structured format that facilitates easy export and enrichment.
| Data Type | Source | Purpose |
|---|---|---|
| ICP Profiles | context.md | Guides query design and filtering |
| Win Cases | context.md | Provides seed domains for lookalike searches |
| DNC List | context.md | List of domains to exclude from final results |
| Company Table | Extruct API | Centralized database of discovered prospects |
| Agent Columns | User Defined | Custom research fields for specific qualifications |
List Building Advanced Features
- Decision Tree Logic: Automatically pivots between search methods based on the maturity of your dataset.
- Recursive Refinement: Uses insights from list-enrichment to create new Deep Search criteria, improving lead quality over time.
- Hypothesis Integration: Automatically pulls search angles from vertical-specific hypothesis sets to address niche pain points.
- Automated Deduplication: Ensures no overlapping domains exist between semantic and deep search runs to maximize reach.
- Lookalike Scaling: Supports multiple seed company inputs to broaden the lookalike search radius without losing relevance.
SKILL.md
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