A read-only AI agent skill to query the HugMap technology knowledge graph and explore relationships across people, companies, and technologies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install hugmap-tech-graph
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 hugmap-tech-graph 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 HugMap Tech Graph?
The HugMap Tech Graph skill brings the power of GraphRAG and technology intelligence directly to your AI agents. Built as an optimized integration for Openclaw Skills, this skill accesses HugMap (www.hugmap.com), a comprehensive tech knowledge graph that extracts entities and relations from unstructured text.
This skill allows developers to query rich metadata across eight distinct entity classes without any complex external dependencies. By invoking a single, light-weight Python script, agents can locate technical papers, track startup relations, and aggregate industry dynamics, making it one of the most versatile Openclaw Skills for technical market intelligence.
HugMap Tech Graph Use Cases
- Entity Profiling: Looking up comprehensive information on technology entities like companies, products, patents, or researchers.
- Relation Pathfinding: Discovering the shortest relationship path between two unrelated entities (e.g., mapping a researcher to a tech product).
- Sub-graph Exploration: Visualizing and exploring local neighborhoods and relationship links surrounding a central technological concept.
- Industry Dynamic Aggregation: Retrieving recent tech articles and chronological events categorized by industrial taxonomies to keep track of sector trends.
How HugMap Tech Graph Works
- Entity Identification: The agent initiates a query using search, prefix suggestion, or standard entity lookup to resolve semantic names into unique HugMap IDs.
- Detail Retrieval: Using the resolved ID, the agent queries full profiles, retrieving properties, metadata, and connected nodes.
- Graph Exploration: The agent calls pathfinding, neighborhood, or similarity subcommands to construct the structural relationship map.
- Link Enrichment: The query script automatically injects web properties (webUrl, webLabel, webSummary) for each entity, preparing highly interactive markdown responses for downstream user interaction.
HugMap Tech Graph Setup
Prerequisites
- Python 3 installed on your system (standard libraries only, no extra pip dependencies required).
Environment Variables
To customize the API endpoint, configure the following optional environment variable:
export HUGMAP_BASE_URL="https://www.hugmap.com"
CLI Execution
Execute queries directly from the CLI to test functionality:
# Query global knowledge graph statistics
python3 scripts/hugmap_query.py stats
# Search for an entity by keyword
python3 scripts/hugmap_query.py search "OpenAI" --type Company
# Find similar technologies
python3 scripts/hugmap_query.py similar tech_transformer
HugMap Tech Graph Data Schema & Taxonomy
The skill maintains a unified data structure across all query subcommands to guarantee predictability and ease of parsing inside Openclaw Skills frameworks.
Core Response Payload
| Field | Type | Description |
|---|---|---|
code |
Integer | Status code. 0 indicates execution success. |
message |
String | Informational or error message. |
data |
Object / Array | Subcommand-specific query payload. |
timestamp |
Integer | Epoch timestamp of the API response. |
Entity Categories
The knowledge graph indexes exactly 8 entity categories:
- Person: Technology pioneers, authors, and researchers.
- Company: Corporate organizations, startups, and institutions.
- Technology: Specific technologies, algorithms, and frameworks.
- Product: Tech products, APIs, and commercial offerings.
- Paper: Academic papers and scientific literature.
- Patent: Registered intellectual property and patent records.
- Article: Technology articles, blog posts, and news.
- Event: Relevant technological events and timeline milestones.
HugMap Tech Graph Advanced Features
- Automatic URL Injection: Automatically injects official website URLs (webUrl), anchor labels (webLabel), and summarized snippets (webSummary) into all query results to facilitate one-click navigation.
- Vector Similarity (Nearest Neighbors): Leverage embedded similarity algorithms (similar command) to instantly discover relevant technical alternatives and vector neighbors.
- Deep Subgraph Traversal: Fetch multi-depth transactional connections surrounding any tech entity node, giving agents complete topological awareness of specific technology ecosystems.
- Flexible Search Filtering: Fine-tune queries with domain, period, type, and pagination filters, offering highly responsive search experiences within the Openclaw Skills suite.
SKILL.md
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