market_statsAggregate market overview: total active jobs, posting velocity (24h / 7d), and breakdowns by sector, employment type, work arrangement, and country.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| response_generated_at | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description goes beyond this by detailing the exact metrics and breakdowns returned, giving the agent a clear picture of the tool's behavior without exceeding its scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, tightly packed sentence that front-loads the key concept ('Aggregate market overview') and then enumerates specific outputs. No wasted words; every phrase adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple, parameterless nature and the presence of an output schema, the description fully covers the tool's purpose and content. No important details are missing, and the agent has enough information to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description fully explains what the tool does, making the absence of parameters completely unambiguous. No additional parameter information is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource: 'Aggregate market overview' clearly defines it as a summary/stats tool. It lists concrete outputs (total active jobs, posting velocity, breakdowns) which distinguishes it from sibling tools like get_job, list_companies, and search_jobs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly conveys the tool's context: use it for market-level aggregate statistics. It does not explicitly mention alternatives or exclusions, but the 'aggregate' framing inherently contrasts with the more specific sibling tools, providing clear context without needing to name them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource or action: companies, jobs, locations, sectors, market stats, and search. There is no overlap in purpose, and the descriptions clarify what each tool returns.
Most tools follow a clear verb_noun pattern (get_company, list_companies, search_jobs). market_stats is a noun phrase, which deviates slightly, but the overall naming style is consistent and predictable.
Seven tools is well-scoped for a recruiter job board. Each tool serves a clear function, and the count is neither too thin nor excessive.
The domain is browsing and searching recruiter job listings. The surface covers listing, searching, fetching details, and market overview, with no obvious gaps for a read-only job board.