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talentpulse

Benchmark salaries, check remote compliance, model EOR costs, analyze skills demand and gaps, track layoffs, compare hiring costs across countries with one API.

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

Input Schema

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

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

No annotations provided, so description must carry the full behavioral burden. It mentions each endpoint's purpose and cost ($0.10) but does not disclose side effects, authentication needs, rate limits, error behavior, or return format. The read-only nature is implied 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.

Conciseness3/5

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

The description is moderately concise with a header, coverage statement, and bullet list. It front-loads the core purpose. However, each bullet repeats '$0.10' and some lines are verbose. Could be tighter without losing meaning.

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

Completeness2/5

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

Given 18 parameters with only 'action' required, the description lacks guidance on which parameters are needed per action. No output schema is provided, leaving the agent uninformed about return values. The high complexity demands more completeness than a simple endpoint list.

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 coverage is 100% with good parameter descriptions. The description does not add significant value beyond the schema; it only lists endpoints. For a high-coverage schema, baseline 3 is appropriate. No enrichment of parameter meaning or action-specific guidance.

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

Purpose4/5

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

The description clearly states it's a global workforce intelligence API and lists specific endpoints with brief explanations (e.g., salary benchmarking, remote compliance). It distinguishes itself from sibling 'pulse' tools by focusing on talent/workforce. However, the lack of a succinct single-sentence purpose and the messy bullet list slightly reduce clarity.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives among the many sibling tools. The description implies usage based on endpoint choice (e.g., use salary action for salary data) but does not provide when-not-to-use or prerequisites. Missing exclusion criteria and comparative context.

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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