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Startup Jobs

by io.github.killbridge

Salary benchmarks

salary_benchmarks
Read-onlyIdempotent

Salary benchmarks (yearly, USD) computed from startup.jobs listings that disclose compensation, optionally filtered by role and/or country. The free tier returns an aggregate over the last 12 months; full access unlocks the monthly time series and company-level benchmarks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleNoRole slug from list_roles (specific roles only, not top-level categories)
monthsNoHow many months of history (default 12, full access only)
companyNoCompany slug (full access only)
countryNoTwo-letter ISO country code

TDQS

A4.4/5.0
Behavior4/5

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

The description adds context beyond the readOnly/idempotent annotations by specifying the data source, the free tier 12-month aggregate, and full access unlocking time series and company-level benchmarks. No contradictions with annotations.

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

Conciseness5/5

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

Two concise, well-structured sentences cover purpose, source, filters, and tier differences with no redundant text, making it highly scannable for an agent.

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

Completeness4/5

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

For a read-only benchmark tool with no required parameters, the description covers essential aspects: data source, units, filters, and access tiers. It doesn't detail return format, but annotations and schema compensate adequately.

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

Parameters4/5

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

The schema already documents all 4 parameters with descriptions (100% coverage), but the description adds meaning by stating the output is yearly USD and clarifying the free tier vs full access constraints for months/company parameters, which goes beyond the schema.

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 the tool computes yearly USD salary benchmarks from startup.jobs listings, with optional filters by role and/or country. This makes it distinct from siblings like job_trends and search_jobs, which focus on other aspects.

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

Usage Guidelines4/5

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

The description conveys when to use the tool for compensation benchmarks and clarifies the free vs full access tiers, providing clear context. However, it does not explicitly mention alternatives or exclusion cases, so it stops short of full 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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: company lookup, company-specific jobs, individual job details, job search, trends, salary data, and taxonomy lookups. Even though get_company_jobs and search_jobs both return job summaries, one is scoped to a single company while the other is a global search, making confusion unlikely.

Naming Consistency4/5

Most tools follow a verb_noun pattern (get_company, get_company_jobs, get_job, list_countries, list_roles, search_jobs), but job_trends and salary_benchmarks are noun compounds without a verb. This is a minor deviation and still predictable, so it's mostly consistent.

Tool Count5/5

With 8 tools, the set is well-scoped for a job data server. It covers retrieval, search, analytics, and reference data without unnecessary bloat or missing essential operations. This is well within the ideal range.

Completeness4/5

The core workflows—search jobs, get details, company info, trends, salary benchmarks, and filters—are well covered. A notable gap is the lack of a way to discover companies by listing them or searching them, which would make company exploration more complete, but agents can work around this via job search results.

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