get_local_demandRead which kinds of roles are hiring most in a place (city, region, country): open jobs by role category, with total open jobs, employers and sectors. When a place has too few role types it widens to the region, the country or worldwide; scope and locationLabel say which. Use it when someone does not yet know what to look for.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | ||
| limit | No | ||
| region | No | ||
| country | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent and closed-world semantics, yet the description adds genuine behavioral detail: the result silently widens from city to region, country, or worldwide when too few role types exist, and the caller can detect this via scope and locationLabel. That auto-fallback is the main thing an agent could misinterpret, and it is disclosed.
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?
Three tight sentences: what it returns, how the scope falls back, and when to reach for it. All load-bearing, front-loaded, no filler.
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?
The description names two return fields (scope, locationLabel) which partially compensates for the absent output schema, and it explains the geo-fallback logic. However, it leaves the geography parameters' interaction and the limit cap unexplained, which an agent needs to call this correctly on the first try.
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?
Schema description coverage is 0% and the description leaves semantics thin: it does not say whether city, region and country can be combined or which wins, and the limit parameter (1-12, presumably capping role categories) is only hinted at via 'too few role types'. With four undocumented parameters, this is a real gap.
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?
States a specific verb and resource: read which role categories are hiring most in a place, returning open jobs by role, totals, employers and sectors. This is clearly distinct from siblings like search_jobs (keyword lookup) and get_market_insights.
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?
Gives an explicit trigger: 'Use it when someone does not yet know what to look for', which implicitly contrasts with search_jobs that requires a known query. It stops short of naming alternatives or stating exclusions, so it is strong but not fully routing-aware.
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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