find_intermodal_hubsLook up U.S. intermodal rail hubs by city or state: which Class I railroads serve the metro, the named ramps to ask a carrier about, and notes. Leave both out to list every hub. Does not count toward the allowance.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | City or metro name, e.g. 'Houston'. Omit or null for any. | |
| state | No | Two-letter state code, e.g. 'TX'. Omit or null for any. |
Changes observed during successful MCP inspections.
Input schema / properties / city / descriptionPrevious value: -"City or metro name, e.g. 'Houston', or null."New value: +"City or metro name, e.g. 'Houston'. Omit or null for any."Input schema / properties / state / descriptionPrevious value: -"Two-letter state code, e.g. 'TX', or null."New value: +"Two-letter state code, e.g. 'TX'. Omit or null for any."Input schema / requiredRemoved value: -[
- "city",
- "state"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds a genuinely non-schema behavioral fact — 'Does not count toward the allowance' — a quota/cost disclosure that helps the agent decide how freely to call it, plus a summary of what the result contains. It stops short of richer context (e.g., completeness of coverage, freshness).
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, front-loaded with purpose, followed by the return contents and the null-case behavior. No filler or redundancy.
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 usefully enumerates the returned fields so the agent knows what it gets back. Combined with the quota note and null-case rule, it is nearly complete for a simple two-parameter lookup, though it does not state coverage scope (all U.S. hubs vs. a subset) or result-size expectations.
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 100% and the description's parameter content ('by city or state', leave both out for all) merely restates what the schema already documents. Baseline 3 applies since the schema does the heavy lifting.
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 ('look up') and resource ('U.S. intermodal rail hubs') and describes the returned content (serving Class I railroads, named ramps, notes). An agent can distinguish this from siblings like estimate_intermodal_rate or get_rail_market_outlook without opening the schema.
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?
It gives one useful usage rule — 'Leave both out to list every hub' — which tells the agent how to enumerate all hubs. However, it offers no guidance on when to prefer this over adjacent tools such as lookup_carrier, recommend_mode, or the various estimate_intermodal_* siblings. Usage is implied rather than routed.
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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