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talentpulse

Get global workforce intelligence: salary benchmarks, remote compliance, skills demand, visa pathways, and hiring cost models for any role and location.

Instructions

TalentPulse: Global workforce intelligence API — salary benchmarks, remote compliance, EOR cost models, skills demand, work visas, talent market analysis, executive compensation, layoff tracking, skills gap analys

Coverage: Global

Endpoints: • salary ($0.15): Salary benchmarking — any role, any location globally • remote-compliance ($0.20): Remote work compliance — jurisdiction-specific legal intelligence • employer-of-record ($0.20): Employer of record cost model — full employer cost breakdown by country • skills-demand ($0.12): Skills demand intelligence — real-time market signal for any skill or role globally • visa ($0.15): Work visa intelligence — all pathways for any nationality/destination pair • talent-market ($0.15): Talent market intelligence — supply/demand dynamics, hubs, and competitive landscape • compensation ($0.25): Executive compensation benchmarking — total comp for senior and C-suite roles globally • layoffs ($0.10): Layoff tracker — real-time workforce reduction intelligence • skills-gap ($0.15): Skills gap intelligence — where employer demand outpaces supply, with reskilling pathways • cost-comparison ($0.20): Multi-country hiring cost comparison — CFO-grade employer cost model across countries

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoResponse language: en | es | fr | de | ja | zh | ko | pt | ar | hi (default: en)
roleNoJob title e.g. Software Engineer | Data Scientist | Product Manager | Registered Nurse
levelNoLevel: C-suite | VP | Director | Senior Director | SVP (default: VP)
actionYesWhich endpoint to call. Options: salary | remote-compliance | employer-of-record | skills-demand | visa | talent-market | compensation | layoffs | skills-gap | cost-comparison
regionNoGeographic focus e.g. Southeast Asia | Europe | North America | MENA | Latin America | Global (default: Global)
salaryNoAnnual gross salary in local currency (optional, for cost model)
sectorNoIndustry sector e.g. SaaS | fintech | healthcare | manufacturing | consulting (default: technology)
skillsNoSkills or role e.g. machine learning | React | Kubernetes | product management
countryNoCountry name — optional, inferred from location if omitted
currencyNoPreferred currency code e.g. USD | GBP | EUR | SGD | INR | AUD | CAD
industryNoIndustry sector e.g. tech | finance | retail | healthcare | media | logistics (default: tech)
locationNoCity or region e.g. London | Singapore | São Paulo | Dubai | Bangalore | Toronto
countriesNoComma-separated list of countries (min 2) e.g. USA,India,Poland,Colombia
experienceNoExperience filter (default: all)
destinationNoCountry where they want to work e.g. Canada | Germany | UAE | Australia | UK | Singapore
nationalityNoNationality of the remote employee (optional)
company_sizeNostartup | series-b | mid-market | large-cap | public (optional)
company_countryNoWhere the employer entity is based (optional, affects PE analysis)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description should disclose behavioral traits. It lists endpoint costs but omits details on authentication, rate limits, data freshness, or side effects. The tool is likely read-only, but not stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a summary and bulleted endpoints, but it is relatively long. It front-loads the purpose and uses clear formatting, though some repetition exists.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 18 parameters and no output schema, the description adequately covers the endpoint purposes and required parameters. However, it lacks details on return values or how to interpret results, which would aid agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 18 parameters. The description adds no additional parameter context or meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a global workforce intelligence API, lists 10 specific endpoints with their purposes and costs, and distinguishes itself from siblings by being focused on workforce data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by describing each endpoint's function, but does not explicitly guide when to use this tool versus sibling tools or when not to use it. There is no exclusion or alternative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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