get_healthcare_job_marketHow many healthcare jobs are open right now, how many were first listed in the last 7 days and how many are listed per week, with the open jobs by kind of job, by US state and by employer (with each employer's slug for the other tools).
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Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds nothing about data freshness, source, or snapshot semantics, and only incidentally covers the return shape because no output schema exists.
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 dense sentence with no wasted filler, and the most important figure (open jobs right now) is front-loaded. It is a run-on construction, but every clause carries distinct informational content.
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?
With no output schema and no parameters, the description must explain what comes back — and it does, listing all the aggregates and breakdowns. Only the granularity/format of the per-week and per-kind figures is left unspecified.
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 takes zero parameters, so the schema-side baseline of 4 applies. There is nothing parameter-related the description needs to compensate for.
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 enumerates the exact content returned — open job counts, new-in-7-days counts, weekly listing rate, and breakdowns by job kind, US state, and employer. This clearly separates it from siblings like search_healthcare_jobs and get_healthcare_jobs_by_state, though it phrases the purpose as a list of questions rather than stating the verb ('returns aggregate healthcare job market statistics').
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?
No statement of when to call this versus the sibling tools. The only routing hint is the parenthetical that employer slugs are provided 'for the other tools', which implies this is an entry point, but no explicit when/when-not or alternative is named.
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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