Detailed climate data for one ZIP code. Use when get_zip_profile's climate section isn't sufficient depth. Includes annual/monthly temperature averages, precipitation, humidity, and nearest weather station info.
| Name | Required | Description | Default |
|---|---|---|---|
| zip | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It describes the data returned but does not disclose behavioral traits like rate limits, authentication, data freshness, or side effects. For a read-only tool, this is adequate but not thorough.
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?
The description is two sentences: the first states the purpose, the second provides usage guidance and lists included data. It is front-loaded, efficient, and contains no extraneous words.
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, the description lists the data types included (temperature averages, precipitation, humidity, nearest weather station), which is reasonably complete. However, it does not mention limitations like geographic scope or time periods, which could be useful.
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 coverage is 0%, meaning the schema provides no parameter descriptions. The description adds meaning by stating the input is 'one ZIP code' and implies the format. This compensates for the schema gap, though it doesn't provide validation rules or examples.
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 clearly states it provides detailed climate data for one ZIP code, and distinguishes it from get_zip_profile by specifying it offers deeper depth. The verb 'get' and resource 'weather profile' are explicit.
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 explicitly states when to use this tool: 'Use when get_zip_profile's climate section isn't sufficient depth.' This guides the agent to prefer the sibling tool for basic needs and this one for deeper data, providing clear context and alternative.
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.
Every tool has a clearly distinct purpose. Domain-specific profiles (e.g., get_air_quality_profile) are explicitly for deeper dives after get_zip_profile, while search, reverse geocode, research, and methodology tools each serve unique roles with no overlap.
All tools follow a consistent verb_noun pattern: get_<domain>_profile, search_zips, reverse_geocode, compare_zips, get_research, get_methodology, etc. The naming is predictable and clear, with no mixing of conventions.
22 tools is slightly above the typical well-scoped range, but each tool addresses a specific need (12 domain profiles, search, geocoding, articles, methodology, ping). The count is appropriate for the breadth of data offered.
The tool surface covers the full workflow: discover (search_zips, get_search_fields), retrieve (get_zip_profile, domain profiles), compare (compare_zips), and ancillary (reverse_geocode, get_research, get_methodology). There are no dead ends or obvious gaps.
