Detailed public transit data for one ZIP code. Use when get_zip_profile's transit section isn't sufficient depth. Includes bus stop count, subway station count, rail station count, light rail count, ferry terminal count, total transit stops, transit commute percentage, and nearest subway/rail distances.
| Name | Required | Description | Default |
|---|---|---|---|
| zip | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description lists included data fields but does not disclose behavioral traits such as read-only nature, rate limits, or authentication needs. For a simple read tool, this is acceptable but minimal.
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?
Extremely concise: one sentence for purpose, one for usage guidance, and a list of specific data fields. No waste, front-loaded with key information.
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 one parameter, no output schema, and low complexity, the description lists 9 specific data fields, providing sufficient completeness for a data retrieval tool. Minor gaps like output format or distance units prevent a perfect score.
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 has one parameter 'zip' with 0% description coverage. Description only mentions 'one ZIP code' without specifying format, valid range, or examples, failing to compensate for lack of schema details.
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?
Clearly states it provides 'detailed public transit data for one ZIP code' and explicitly distinguishes from sibling 'get_zip_profile' by noting usage when its transit section is insufficient.
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?
Explicitly states 'Use when get_zip_profile's transit section isn't sufficient depth', providing clear when-to-use and direct 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.
