lnd_skill_taxonomy_builder
ActiveTool of @gapup/mcp-knowledge
declared in 0.2.0
Generates a dynamic skill taxonomy for CHROs by cross-referencing patent filings (USPTO), job postings (BLS), and learning & development data (OECD). Inputs include industry codes, job roles, or skill clusters; outputs structured skill hierarchies with demand trends and competency gaps. Essential for workforce transformation, talent pipeline optimization, and future-proofing organizational capabilities. — pass async:true REQUIRED to avoid x402 timeout.
Parameters schema
{
"type": "object",
"required": [
"industry"
],
"properties": {
"async": {
"type": "boolean",
"description": "If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts."
},
"jobRole": {
"type": "string",
"description": "Target job role or occupation (e.g., 'Data Scientist')"
},
"industry": {
"type": "string",
"description": "NAICS industry code or sector name (e.g., '541511' for IT services)"
},
"timeRange": {
"enum": [
"1y",
"3y",
"5y"
],
"type": "string",
"description": "Time range for trend analysis"
},
"skillCluster": {
"type": "string",
"description": "Optional skill cluster to focus taxonomy (e.g., 'AI/ML')"
}
}
}No endpoints wrapped at confidence ≥ 0.50.
Parent server
@gapup/mcp-knowledge
https://github.com/getgapup/gapup-mcp
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