Global Labor & Employment Data
Freshness
Last updated: 2026-06-24.
If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.
What This Tool Does
Access workforce and employment data for any country in the world. Look up labor force participation rates, unemployment figures, sector breakdowns, gender employment gaps, and youth employment trends. Compare workforce metrics across countries, track labor market shifts over time, and benchmark regional performance — all from a comprehensive global data set.
Product Instructions
Labor Market & Employment Data
Access comprehensive labor market and employment statistics from the World Bank's World Development Indicators database covering 200+ countries. Query labor force participation, unemployment rates, employment by sector, gender gap analysis, employment quality metrics, and regional comparisons using natural language country names.
Actions
query_labor_data
Fetch labor market and employment indicator data for a country or region.
Required Parameters:
action (string): Must be "query_labor_data"
country_or_region (string): Country or region name in plain language (e.g., "Kenya", "South Korea", "World")
Optional Parameters:
demographic_filter (string, default: null): Filter indicators by demographic category. One of:
"gender" - Male/female labor force participation and unemployment rates, plus total rates
"youth" - Youth unemployment (ages 15-24) by gender, plus total unemployment and labor force participation
"sector" - Employment by economic sector (agriculture, industry, services), plus total labor force and unemployment
"total" - Overall labor force participation, unemployment, wage/salaried workers, and vulnerable employment
null or "all" - All available labor market indicators
calculate_gender_gaps (boolean, default: true): Calculate gender gaps as male rate minus female rate for labor force participation, unemployment, and youth unemployment. Positive gap means males higher, negative means females higher.
include_sector_employment (boolean, default: true): Include employment by sector breakdown (agriculture, industry, services) even when a different demographic filter is selected
time_period (string, default: "latest"): Time period for data. Options:
"latest" - Most recent available data
"last_5_years" - Last 5 years of data
"last_10_years" - Last 10 years of data
"YYYY:YYYY" - Specific year range (e.g., "2015:2020"). Years must be between 1960 and current year.
"YYYY" - A single year (e.g., "2020")
include_regional_comparison (boolean, default: true): Include comparison data with World average, High Income countries, East Asia & Pacific, and Latin America & Caribbean
include_trends (boolean, default: true): Include trend analysis with CAGR (Compound Annual Growth Rate) calculations when historical data is available
Example - Gender-disaggregated data with gap analysis:
{
"action": "query_labor_data",
"country_or_region": "Kenya",
"demographic_filter": "gender",
"calculate_gender_gaps": true,
"time_period": "latest"
}
Example - Youth unemployment trends:
{
"action": "query_labor_data",
"country_or_region": "Spain",
"demographic_filter": "youth",
"time_period": "last_10_years",
"include_trends": true
}
Example - All labor indicators with full analysis:
{
"action": "query_labor_data",
"country_or_region": "India",
"demographic_filter": "all",
"calculate_gender_gaps": true,
"include_sector_employment": true,
"time_period": "latest",
"include_regional_comparison": true
}
Example - Sector employment breakdown:
{
"action": "query_labor_data",
"country_or_region": "Vietnam",
"demographic_filter": "sector",
"include_sector_employment": true,
"time_period": "latest"
}
Example - Regional labor market overview:
{
"action": "query_labor_data",
"country_or_region": "Sub-Saharan Africa",
"demographic_filter": "total",
"time_period": "last_5_years",
"include_regional_comparison": true
}
Supported Countries and Regions
Accepts plain-language names. Examples of supported inputs:
- Countries:
"United States", "USA", "India", "South Korea", "Nigeria", "Brazil", "Spain", "Kenya", etc. (200+ countries)
- Regions:
"Sub-Saharan Africa", "Latin America", "Middle East", "South Asia", "East Asia", "Europe"
- Income groups:
"Low Income", "Lower Middle Income", "Upper Middle Income", "High Income", "OECD"
- Global:
"World" or "Global"
- ISO3 codes: 3-letter codes like
"USA", "IND", "KOR" are also accepted
Country names support partial matching, so "UK" maps to United Kingdom and "America" maps to USA.
Available Indicators
Labor Force Participation
- Labor Force Participation Rate, Total (% of population ages 15+)
- Labor Force Participation Rate, Male (% of male population ages 15+)
- Labor Force Participation Rate, Female (% of female population ages 15+)
Unemployment
- Unemployment Rate, Total (% of total labor force)
- Unemployment Rate, Male (% of male labor force)
- Unemployment Rate, Female (% of female labor force)
- Youth Unemployment Rate (% of total labor force ages 15-24)
- Youth Unemployment Rate, Male (% ages 15-24)
- Youth Unemployment Rate, Female (% ages 15-24)
Employment by Sector
- Employment in Agriculture (% of total employment)
- Employment in Industry (% of total employment)
- Employment in Services (% of total employment)
Employment Quality
- Wage and Salaried Workers (% of total employment) -- proxy for formal employment
- Vulnerable Employment (% of total employment) -- own-account workers + contributing family workers
- Self-Employed (% of total employment)
Employment by Gender
- Employment to Population Ratio, Male (%)
- Employment to Population Ratio, Female (%)
Other
- Part-Time Employment (% of total employment)
Response Structure
Responses include:
- Indicator data with latest values, units (% of labor force, % of population ages 15+, %), year, country name, and source
- Trend analysis with absolute change, percent change, direction (increasing/decreasing/stable), data point count, and CAGR when applicable
- Gender gap analysis (when enabled): labor force participation gap, unemployment gap, and youth unemployment gap with interpretation of gap direction and magnitude
- Regional comparison benchmarked against World average, High Income countries, East Asia & Pacific, and Latin America & Caribbean
- Insights covering participation levels, unemployment severity, youth unemployment, gender gaps, sector composition (agriculture-dependent vs service-based vs industrial), vulnerable employment, formal employment levels, and SDG 8 progress
- SDG 8.5 alignment (Full and productive employment and decent work for all)
Gender Gap Analysis
When calculate_gender_gaps is true, the response includes:
- Labor force participation gap: Male rate minus female rate with interpretation
- Unemployment gap: Male rate minus female rate with interpretation
- Youth unemployment gap: Male youth rate minus female youth rate
Positive gap = males higher. Negative gap = females higher.
Workflows
- Gender Equity Assessment: Use
demographic_filter: "gender" with calculate_gender_gaps: true to analyze male-female disparities in labor force participation and unemployment
- Youth Employment Crisis: Use
demographic_filter: "youth" with time_period: "last_10_years" to track youth unemployment trends
- Economic Structure Analysis: Use
demographic_filter: "sector" to understand whether a country is agriculture-dependent, service-based, or industrial
- Job Quality Assessment: Query all indicators and review vulnerable employment and wage/salaried worker percentages as proxies for informal vs formal employment
- SDG 8 Monitoring: Query total labor indicators with regional comparison to assess progress toward decent work goals
Notes
- Data sourced from World Bank World Development Indicators
- Labor force participation = % of population ages 15+ that is economically active
- Unemployment = % of labor force without work but available and seeking employment
- Youth unemployment covers ages 15-24
- Vulnerable employment = own-account workers + contributing family workers (proxy for job insecurity)
- Wage/salaried workers serves as a proxy for formal employment
- Employment by sector percentages should sum to approximately 100% (agriculture + industry + services)
- Gender gaps are calculated as male rate minus female rate
- When
demographic_filter is unrecognized, the tool defaults to total labor force indicators
- When
include_sector_employment is true and the demographic filter is not already "sector", sector indicators are appended to the results
- Regional comparison uses lfp_total, lfp_female, unemployment_total, and unemployment_youth as key benchmarking indicators
- Data availability varies by country; some developing countries may have limited labor force survey coverage
- Most recent data is typically 1-2 years behind the current year
- Trend CAGR is only calculated for multi-year periods where both start and end values are positive
When To Use
- Use this skill for
Global Labor & Employment Data on AgentPMT.
- Use it when an agent needs this specific tool's behavior, schema, inputs, outputs, and invocation shape.
- Search and activation keywords: global labor & employment data, labor market employment, research labor force participation rates by country, compare unemployment rates across regions, analyze employment by sector breakdown, study gender gaps in workforce participation, query labor data, country or region.
- Supported action names:
query_labor_data.
Use Cases
- Research labor force participation rates by country
- Compare unemployment rates across regions
- Analyze employment by sector breakdown
- Study gender gaps in workforce participation
- Track youth unemployment trends
- Benchmark formal vs informal employment
- Monitor wage and labor market shifts
- Support workforce equity research
- Assess progress toward SDG 8 decent work targets
- Compare regional labor market performance
Categories And Industries
No categories or industry tags are published for this tool.
Actions And Schema
Complete generated action schema: ./schema.md.
Supported action count: 1.
x402 availability: not enabled for this product.
query_labor_data (action slug: query-labor-data): Fetch labor market and employment indicator data for a country or region, including labor force participation, unemployment rates, sector employment, gender gap analysis, and employment quality metrics. Price: 5 credits. Parameters: calculate_gender_gaps, country_or_region, demographic_filter, include_regional_comparison, include_sector_employment, include_trends, time_period.
Live Schema And Examples
Use the compact schema above for ordinary calls. Before a new production integration, or whenever parameters, enum values, nested objects, outputs, or examples are unclear, fetch live details first.
- Exact schema: call
agentpmt-tool-search-and-execution with action: "get_schema", and tool_id: "labor-market-employment".
- Detailed examples: call
agentpmt-tool-search-and-execution with action: "get_instructions" and tool_id: "labor-market-employment", or call this product with action: "get_instructions" when the product tool is already selected.
- Treat returned live schema and instructions as more specific than this generated summary.
MCP schema lookup through the main AgentPMT MCP server:
{
"method": "tools/call",
"params": {
"name": "AgentPMT-Tool-Search-and-Execution",
"arguments": {
"action": "get_schema",
"tool_id": "labor-market-employment"
}
}
}
For live examples, keep the same MCP tool and use these arguments:
{
"action": "get_instructions",
"tool_id": "labor-market-employment"
}
Authenticated AgentPMT REST schema lookup body:
{
"name": "agentpmt-tool-search-and-execution",
"parameters": {
"action": "get_schema",
"tool_id": "labor-market-employment"
}
}
Authenticated AgentPMT REST live examples body:
{
"name": "agentpmt-tool-search-and-execution",
"parameters": {
"action": "get_instructions",
"tool_id": "labor-market-employment"
}
}
Call This Tool
Product slug: labor-market-employment
Marketplace page: https://www.agentpmt.com/marketplace/labor-market-employment
- AgentPMT account route: first use
../agentpmt-account-mcp-rest-api-setup to connect the main MCP server or REST API for an Agent Group where this tool is enabled.
- x402 route: not enabled for this product.
- AgentPMT overview: use
../what-is-agentpmt for marketplace, Agent Group, workflow, MCP, REST, and payment concepts.
If those setup skills are not installed beside this product skill, use the downloads below.
Core AgentPMT setup skills:
- What AgentPMT is: ../what-is-agentpmt
- AgentPMT account MCP/REST setup: ../agentpmt-account-mcp-rest-api-setup
skills.sh install script:
npx skills add AgentPMT/agent-skills --skill what-is-agentpmt
npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup
MCP call shape after the main AgentPMT MCP server is connected:
{
"method": "tools/call",
"params": {
"name": "Global-Labor--Employment-Data",
"arguments": {
"action": "query_labor_data",
"calculate_gender_gaps": true,
"country_or_region": "example country or region",
"demographic_filter": "gender",
"include_regional_comparison": true,
"include_sector_employment": true,
"include_trends": true,
"time_period": "latest"
}
}
}
Use the exact tool name returned by tools/list; the name above is the expected readable form.
Authenticated AgentPMT REST call body:
{
"name": "labor-market-employment",
"parameters": {
"action": "query_labor_data",
"calculate_gender_gaps": true,
"country_or_region": "example country or region",
"demographic_filter": "gender",
"include_regional_comparison": true,
"include_sector_employment": true,
"include_trends": true,
"time_period": "latest"
}
}
Use the setup skill for the account connection details before making REST calls.
Response Handling
- Treat the returned JSON as the source of truth for this tool call.
- If the response includes warnings or correction targets, apply them before retrying.
- If the response includes a
passed or success-style boolean, use it as the workflow gate.
- If validation fails or the response shape is unclear, call
get_schema or get_instructions before retrying.
- If
query_labor_data fails, preserve the request parameters and retry only after fixing schema, auth, or payment errors.
Security
- Do not place account secrets, wallet private keys, mnemonics, signatures, or payment headers in prompts or logs.
- Keep tool inputs scoped to the minimum content needed for the task.
- Use the setup skills for credential handling; this product skill only defines product-specific behavior.
AgentPMT Reference
1---2name: global-labor-employment-data3description: Global Labor & Employment Data: Query labor force participation, unemployment rates, sector employment breakdowns, gender gaps, and youth employment for. Use when an agent needs global labor & employment data, labor market employment, research labor force participation rates by country, compare unemployment rates across regions, analyze employment by sector breakdown, study gender gaps in workforce participation, query labor data, country or region through AgentPMT-hosted remote tool calls.4---5# Global Labor & Employment Data67## Freshness8Last updated: `2026-06-24`.910If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.1112## What This Tool Does13Access workforce and employment data for any country in the world. Look up labor force participation rates, unemployment figures, sector breakdowns, gender employment gaps, and youth employment trends. Compare workforce metrics across countries, track labor market shifts over time, and benchmark regional performance — all from a comprehensive global data set.1415## Product Instructions16### Labor Market & Employment Data1718Access comprehensive labor market and employment statistics from the World Bank's World Development Indicators database covering 200+ countries. Query labor force participation, unemployment rates, employment by sector, gender gap analysis, employment quality metrics, and regional comparisons using natural language country names.1920#### Actions2122##### query_labor_data2324Fetch labor market and employment indicator data for a country or region.2526**Required Parameters:**27- `action` (string): Must be `"query_labor_data"`28- `country_or_region` (string): Country or region name in plain language (e.g., `"Kenya"`, `"South Korea"`, `"World"`)2930**Optional Parameters:**31- `demographic_filter` (string, default: `null`): Filter indicators by demographic category. One of:32 - `"gender"` - Male/female labor force participation and unemployment rates, plus total rates33 - `"youth"` - Youth unemployment (ages 15-24) by gender, plus total unemployment and labor force participation34 - `"sector"` - Employment by economic sector (agriculture, industry, services), plus total labor force and unemployment35 - `"total"` - Overall labor force participation, unemployment, wage/salaried workers, and vulnerable employment36 - `null` or `"all"` - All available labor market indicators37- `calculate_gender_gaps` (boolean, default: `true`): Calculate gender gaps as male rate minus female rate for labor force participation, unemployment, and youth unemployment. Positive gap means males higher, negative means females higher.38- `include_sector_employment` (boolean, default: `true`): Include employment by sector breakdown (agriculture, industry, services) even when a different demographic filter is selected39- `time_period` (string, default: `"latest"`): Time period for data. Options:40 - `"latest"` - Most recent available data41 - `"last_5_years"` - Last 5 years of data42 - `"last_10_years"` - Last 10 years of data43 - `"YYYY:YYYY"` - Specific year range (e.g., `"2015:2020"`). Years must be between 1960 and current year.44 - `"YYYY"` - A single year (e.g., `"2020"`)45- `include_regional_comparison` (boolean, default: `true`): Include comparison data with World average, High Income countries, East Asia & Pacific, and Latin America & Caribbean46- `include_trends` (boolean, default: `true`): Include trend analysis with CAGR (Compound Annual Growth Rate) calculations when historical data is available4748**Example - Gender-disaggregated data with gap analysis:**49```json50{51 "action": "query_labor_data",52 "country_or_region": "Kenya",53 "demographic_filter": "gender",54 "calculate_gender_gaps": true,55 "time_period": "latest"56}57```5859**Example - Youth unemployment trends:**60```json61{62 "action": "query_labor_data",63 "country_or_region": "Spain",64 "demographic_filter": "youth",65 "time_period": "last_10_years",66 "include_trends": true67}68```6970**Example - All labor indicators with full analysis:**71```json72{73 "action": "query_labor_data",74 "country_or_region": "India",75 "demographic_filter": "all",76 "calculate_gender_gaps": true,77 "include_sector_employment": true,78 "time_period": "latest",79 "include_regional_comparison": true80}81```8283**Example - Sector employment breakdown:**84```json85{86 "action": "query_labor_data",87 "country_or_region": "Vietnam",88 "demographic_filter": "sector",89 "include_sector_employment": true,90 "time_period": "latest"91}92```9394**Example - Regional labor market overview:**95```json96{97 "action": "query_labor_data",98 "country_or_region": "Sub-Saharan Africa",99 "demographic_filter": "total",100 "time_period": "last_5_years",101 "include_regional_comparison": true102}103```104105#### Supported Countries and Regions106107Accepts plain-language names. Examples of supported inputs:108109- **Countries**: `"United States"`, `"USA"`, `"India"`, `"South Korea"`, `"Nigeria"`, `"Brazil"`, `"Spain"`, `"Kenya"`, etc. (200+ countries)110- **Regions**: `"Sub-Saharan Africa"`, `"Latin America"`, `"Middle East"`, `"South Asia"`, `"East Asia"`, `"Europe"`111- **Income groups**: `"Low Income"`, `"Lower Middle Income"`, `"Upper Middle Income"`, `"High Income"`, `"OECD"`112- **Global**: `"World"` or `"Global"`113- **ISO3 codes**: 3-letter codes like `"USA"`, `"IND"`, `"KOR"` are also accepted114115Country names support partial matching, so `"UK"` maps to United Kingdom and `"America"` maps to USA.116117#### Available Indicators118119##### Labor Force Participation120- Labor Force Participation Rate, Total (% of population ages 15+)121- Labor Force Participation Rate, Male (% of male population ages 15+)122- Labor Force Participation Rate, Female (% of female population ages 15+)123124##### Unemployment125- Unemployment Rate, Total (% of total labor force)126- Unemployment Rate, Male (% of male labor force)127- Unemployment Rate, Female (% of female labor force)128- Youth Unemployment Rate (% of total labor force ages 15-24)129- Youth Unemployment Rate, Male (% ages 15-24)130- Youth Unemployment Rate, Female (% ages 15-24)131132##### Employment by Sector133- Employment in Agriculture (% of total employment)134- Employment in Industry (% of total employment)135- Employment in Services (% of total employment)136137##### Employment Quality138- Wage and Salaried Workers (% of total employment) -- proxy for formal employment139- Vulnerable Employment (% of total employment) -- own-account workers + contributing family workers140- Self-Employed (% of total employment)141142##### Employment by Gender143- Employment to Population Ratio, Male (%)144- Employment to Population Ratio, Female (%)145146##### Other147- Part-Time Employment (% of total employment)148149#### Response Structure150151Responses include:152- **Indicator data** with latest values, units (% of labor force, % of population ages 15+, %), year, country name, and source153- **Trend analysis** with absolute change, percent change, direction (increasing/decreasing/stable), data point count, and CAGR when applicable154- **Gender gap analysis** (when enabled): labor force participation gap, unemployment gap, and youth unemployment gap with interpretation of gap direction and magnitude155- **Regional comparison** benchmarked against World average, High Income countries, East Asia & Pacific, and Latin America & Caribbean156- **Insights** covering participation levels, unemployment severity, youth unemployment, gender gaps, sector composition (agriculture-dependent vs service-based vs industrial), vulnerable employment, formal employment levels, and SDG 8 progress157- **SDG 8.5 alignment** (Full and productive employment and decent work for all)158159#### Gender Gap Analysis160161When `calculate_gender_gaps` is `true`, the response includes:162- **Labor force participation gap**: Male rate minus female rate with interpretation163- **Unemployment gap**: Male rate minus female rate with interpretation164- **Youth unemployment gap**: Male youth rate minus female youth rate165166Positive gap = males higher. Negative gap = females higher.167168#### Workflows1691701. **Gender Equity Assessment**: Use `demographic_filter: "gender"` with `calculate_gender_gaps: true` to analyze male-female disparities in labor force participation and unemployment1712. **Youth Employment Crisis**: Use `demographic_filter: "youth"` with `time_period: "last_10_years"` to track youth unemployment trends1723. **Economic Structure Analysis**: Use `demographic_filter: "sector"` to understand whether a country is agriculture-dependent, service-based, or industrial1734. **Job Quality Assessment**: Query all indicators and review vulnerable employment and wage/salaried worker percentages as proxies for informal vs formal employment1745. **SDG 8 Monitoring**: Query total labor indicators with regional comparison to assess progress toward decent work goals175176#### Notes177178- Data sourced from World Bank World Development Indicators179- Labor force participation = % of population ages 15+ that is economically active180- Unemployment = % of labor force without work but available and seeking employment181- Youth unemployment covers ages 15-24182- Vulnerable employment = own-account workers + contributing family workers (proxy for job insecurity)183- Wage/salaried workers serves as a proxy for formal employment184- Employment by sector percentages should sum to approximately 100% (agriculture + industry + services)185- Gender gaps are calculated as male rate minus female rate186- When `demographic_filter` is unrecognized, the tool defaults to total labor force indicators187- When `include_sector_employment` is `true` and the demographic filter is not already `"sector"`, sector indicators are appended to the results188- Regional comparison uses lfp_total, lfp_female, unemployment_total, and unemployment_youth as key benchmarking indicators189- Data availability varies by country; some developing countries may have limited labor force survey coverage190- Most recent data is typically 1-2 years behind the current year191- Trend CAGR is only calculated for multi-year periods where both start and end values are positive192193## When To Use194- Use this skill for `Global Labor & Employment Data` on AgentPMT.195- Use it when an agent needs this specific tool's behavior, schema, inputs, outputs, and invocation shape.196- Search and activation keywords: global labor & employment data, labor market employment, research labor force participation rates by country, compare unemployment rates across regions, analyze employment by sector breakdown, study gender gaps in workforce participation, query labor data, country or region.197- Supported action names: `query_labor_data`.198199## Use Cases200- Research labor force participation rates by country201- Compare unemployment rates across regions202- Analyze employment by sector breakdown203- Study gender gaps in workforce participation204- Track youth unemployment trends205- Benchmark formal vs informal employment206- Monitor wage and labor market shifts207- Support workforce equity research208- Assess progress toward SDG 8 decent work targets209- Compare regional labor market performance210211## Categories And Industries212No categories or industry tags are published for this tool.213214## Actions And Schema215Complete generated action schema: `./schema.md`.216Supported action count: `1`.217x402 availability: not enabled for this product.218219- `query_labor_data` (action slug: `query-labor-data`): Fetch labor market and employment indicator data for a country or region, including labor force participation, unemployment rates, sector employment, gender gap analysis, and employment quality metrics. Price: `5` credits. Parameters: `calculate_gender_gaps`, `country_or_region`, `demographic_filter`, `include_regional_comparison`, `include_sector_employment`, `include_trends`, `time_period`.220221## Live Schema And Examples222Use the compact schema above for ordinary calls. Before a new production integration, or whenever parameters, enum values, nested objects, outputs, or examples are unclear, fetch live details first.223224- Exact schema: call `agentpmt-tool-search-and-execution` with `action: "get_schema"`, and `tool_id: "labor-market-employment"`.225- Detailed examples: call `agentpmt-tool-search-and-execution` with `action: "get_instructions"` and `tool_id: "labor-market-employment"`, or call this product with `action: "get_instructions"` when the product tool is already selected.226- Treat returned live schema and instructions as more specific than this generated summary.227228MCP schema lookup through the main AgentPMT MCP server:229230```json231{232 "method": "tools/call",233 "params": {234 "name": "AgentPMT-Tool-Search-and-Execution",235 "arguments": {236 "action": "get_schema",237 "tool_id": "labor-market-employment"238 }239 }240}241```242243For live examples, keep the same MCP tool and use these arguments:244245```json246{247 "action": "get_instructions",248 "tool_id": "labor-market-employment"249}250```251252Authenticated AgentPMT REST schema lookup body:253254```json255{256 "name": "agentpmt-tool-search-and-execution",257 "parameters": {258 "action": "get_schema",259 "tool_id": "labor-market-employment"260 }261}262```263264Authenticated AgentPMT REST live examples body:265266```json267{268 "name": "agentpmt-tool-search-and-execution",269 "parameters": {270 "action": "get_instructions",271 "tool_id": "labor-market-employment"272 }273}274```275276## Call This Tool277Product slug: `labor-market-employment`278279Marketplace page: https://www.agentpmt.com/marketplace/labor-market-employment280281- AgentPMT account route: first use `../agentpmt-account-mcp-rest-api-setup` to connect the main MCP server or REST API for an Agent Group where this tool is enabled.282- x402 route: not enabled for this product.283- AgentPMT overview: use `../what-is-agentpmt` for marketplace, Agent Group, workflow, MCP, REST, and payment concepts.284285If those setup skills are not installed beside this product skill, use the downloads below.286287Core AgentPMT setup skills:288- What AgentPMT is: ../what-is-agentpmt289 - ClawHub page: https://clawhub.ai/agentpmt/what-is-agentpmt290 - OpenClaw install: `openclaw skills install what-is-agentpmt`291 - skills.sh install: `npx skills add AgentPMT/agent-skills --skill what-is-agentpmt`292- AgentPMT account MCP/REST setup: ../agentpmt-account-mcp-rest-api-setup293 - ClawHub page: https://clawhub.ai/agentpmt/agentpmt-account-mcp-rest-api-setup294 - OpenClaw install: `openclaw skills install agentpmt-account-mcp-rest-api-setup`295 - skills.sh install: `npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup`296297skills.sh install script:298299```bash300npx skills add AgentPMT/agent-skills --skill what-is-agentpmt301npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup302```303304MCP call shape after the main AgentPMT MCP server is connected:305306```json307{308 "method": "tools/call",309 "params": {310 "name": "Global-Labor--Employment-Data",311 "arguments": {312 "action": "query_labor_data",313 "calculate_gender_gaps": true,314 "country_or_region": "example country or region",315 "demographic_filter": "gender",316 "include_regional_comparison": true,317 "include_sector_employment": true,318 "include_trends": true,319 "time_period": "latest"320 }321 }322}323```324325Use the exact tool name returned by `tools/list`; the name above is the expected readable form.326327Authenticated AgentPMT REST call body:328329```json330{331 "name": "labor-market-employment",332 "parameters": {333 "action": "query_labor_data",334 "calculate_gender_gaps": true,335 "country_or_region": "example country or region",336 "demographic_filter": "gender",337 "include_regional_comparison": true,338 "include_sector_employment": true,339 "include_trends": true,340 "time_period": "latest"341 }342}343```344345Use the setup skill for the account connection details before making REST calls.346347## Response Handling348- Treat the returned JSON as the source of truth for this tool call.349- If the response includes warnings or correction targets, apply them before retrying.350- If the response includes a `passed` or success-style boolean, use it as the workflow gate.351- If validation fails or the response shape is unclear, call `get_schema` or `get_instructions` before retrying.352- If `query_labor_data` fails, preserve the request parameters and retry only after fixing schema, auth, or payment errors.353354## Security355- Do not place account secrets, wallet private keys, mnemonics, signatures, or payment headers in prompts or logs.356- Keep tool inputs scoped to the minimum content needed for the task.357- Use the setup skills for credential handling; this product skill only defines product-specific behavior.358359## AgentPMT Reference360- What AgentPMT is: ../what-is-agentpmt (ClawHub: `what-is-agentpmt`, page: https://clawhub.ai/agentpmt/what-is-agentpmt; skills.sh: `npx skills add AgentPMT/agent-skills --skill what-is-agentpmt`)361- AgentPMT account MCP/REST setup: ../agentpmt-account-mcp-rest-api-setup (ClawHub: `agentpmt-account-mcp-rest-api-setup`, page: https://clawhub.ai/agentpmt/agentpmt-account-mcp-rest-api-setup; skills.sh: `npx skills add AgentPMT/agent-skills --skill agentpmt-account-mcp-rest-api-setup`)362- Marketplace product: https://www.agentpmt.com/marketplace/labor-market-employment363- AgentPMT main MCP server: https://api.agentpmt.com/mcp/364- AgentPMT REST invoke endpoint: https://api.agentpmt.com/products/purchase