Metrics

Overview

A metric is a measurable value returned by a Lightcast MCP tool.

Metrics define what is being counted, estimated, ranked, or analyzed. They are dataset-specific and tool-specific, meaning a metric that is valid for one dataset or tool may not be available in another.

For example:

postings.unique_postings measures unique job postings within the job_postings dataset.
profiles.unique_profiles measures unique professional profiles within the profiles dataset.
lmi.jobs measures occupied positions in a Core LMI dataset.
lmi.unemployment_rate measures the unemployment rate in the Government Unemployment dataset.

👉
Use tool_info to retrieve the supported metrics for a specific dataset and tool combination before building an analysis request.

How Metrics are Used

Different tools use metrics in different ways.

Tool	Metric Usage
`count`	Returns requested count metrics.
`distribution`	Uses a domain metric to define the distribution and optional extra metrics to describe buckets.
`estimate`	Returns requested statistical or estimated metrics.
`list`	Returns record-level fields instead of aggregated metrics.
`timeseries`	Returns metric values over time.
`top`	Ranks dimension values using the selected metric.

Job Postings Metrics

The job_postings dataset supports the following metrics.

Tool Context	Supported Metrics
Count	`postings.unique_postings`, `postings.total_postings`, `postings.duplicate_postings`, `postings.unique_companies`
Estimate	`postings.average_salary`, `postings.max_salary`, `postings.median_salary`, `postings.median_posting_duration`, `postings.min_salary`, `postings.posting_intensity`
Timeseries	`postings.unique_postings`, `postings.duplicate_postings`, `postings.total_postings`, `postings.posting_intensity`, `postings.unique_companies`, `postings.min_salary`, `postings.median_salary`, `postings.max_salary`, `postings.average_salary`
Distribution Domain	`postings.salary`, `postings.posting_duration`, `postings.min_years_experience`, `postings.max_years_experience`
Top Rank-By	`postings.unique_postings`, `postings.total_postings`, `postings.duplicate_postings`, `postings.posting_intensity`, `postings.unique_companies`

The list tool returns posting-level fields rather than aggregated metrics, including posting identifiers, dates, job descriptions, company information, locations, URLs, and salary-related attributes.

Profiles Metrics

The profiles dataset supports the following metrics.

Tool context	Supported metrics
Count	`profiles.unique_profiles`, `profiles.unique_schools`, `profiles.unique_companies`
Estimate	`profiles.median_estimated_wage`
Distribution Domain	`profiles.estimated_wage`
Distribution Extra Metrics	`profiles.unique_profiles`, `profiles.unique_schools`, `profiles.unique_companies`
Top Rank-by	`profiles.unique_profiles`, `profiles.unique_schools`, `profiles.unique_companies`, `profiles.median_estimated_wage`

Government Occupations Metrics

The government_occupations dataset supports the following metrics.

Tool Context	Supported Metrics
Estimate	`lmi.jobs`, `lmi.median_earnings`, `lmi.growth`, `lmi.replacements`, `lmi.openings`, `lmi.residence_jobs`, `lmi.created_jobs`, `lmi.destroyed_jobs`, `lmi.hires`, `lmi.separations`, `lmi.education_attainment_percent`
Timeseries	`lmi.jobs`, `lmi.median_earnings`, `lmi.growth`, `lmi.replacements`, `lmi.openings`, `lmi.residence_jobs`, `lmi.created_jobs`, `lmi.destroyed_jobs`, `lmi.hires`, `lmi.separations`, `lmi.education_attainment_percent`
Distribution Domain	`lmi.earnings`
Top Rank-by	`lmi.jobs`, `lmi.median_earnings`, `lmi.growth`, `lmi.replacements`, `lmi.openings`, `lmi.residence_jobs`, `lmi.created_jobs`, `lmi.destroyed_jobs`, `lmi.hires`, `lmi.separations`

The distribution tool uses lmi.earnings to analyze annual earnings percentiles. It supports the 10th, 25th, 50th, 75th, and 90th percentiles.

The lmi.earnings metric is available only as a distribution domain metric. Use lmi.median_earnings when you need median annual earnings.

lmi.jobs measures occupied positions, not unique workers. A person can hold more than one position.

Government Unemployment Metrics

The government_unemployment dataset supports the following metrics.

Tool Context	Supported Metrics
Estimate	`lmi.employment`, `lmi.employment_twelve_month_average`, `lmi.unemployment`, `lmi.unemployment_twelve_month_average`, `lmi.unemployment_rate`, `lmi.labor_force`, `lmi.labor_force_participation_rate`, `lmi.working_age_labor_force_participation_rate`, `lmi.labor_force_population`, `lmi.working_age_population`
Timeseries	`lmi.employment`, `lmi.employment_twelve_month_average`, `lmi.unemployment`, `lmi.unemployment_twelve_month_average`, `lmi.unemployment_rate`, `lmi.labor_force`, `lmi.labor_force_participation_rate`, `lmi.working_age_labor_force_participation_rate`, `lmi.labor_force_population`, `lmi.working_age_population`
Top Rank-by	`lmi.employment`, `lmi.unemployment`, `lmi.unemployment_rate`, `lmi.labor_force`, `lmi.labor_force_participation_rate`

The timeseries tool supports monthly and yearly intervals.

Government Industry Metrics

The government_industry dataset supports the following metrics.

Tool Context	Supported Metrics
Estimate	`lmi.jobs`, `lmi.establishments`, `lmi.wages`, `lmi.wages_per_worker`, `lmi.earnings_per_worker`, `lmi.supplements`, `lmi.supplements_per_worker`, `lmi.total_earnings`, `lmi.hires`, `lmi.separations`, `lmi.turnover_rate`, `lmi.created_jobs`, `lmi.destroyed_jobs`
Timeseries	`lmi.jobs`, `lmi.establishments`, `lmi.wages`, `lmi.wages_per_worker`, `lmi.earnings_per_worker`, `lmi.supplements`, `lmi.supplements_per_worker`, `lmi.total_earnings`, `lmi.hires`, `lmi.separations`, `lmi.turnover_rate`, `lmi.created_jobs`, `lmi.destroyed_jobs`
Top Rank-by	`lmi.jobs`, `lmi.establishments`, `lmi.wages`, `lmi.wages_per_worker`, `lmi.earnings_per_worker`, `lmi.hires`, `lmi.separations`, `lmi.turnover_rate`, `lmi.created_jobs`, `lmi.destroyed_jobs`

The wages, supplements, and total_earnings metrics represent industry-level totals. The corresponding per-worker metrics provide values relative to the number of jobs.