Lists known journeys, optionally filtered by ticket ID, to verify travel details before preparing a DSB compensation claim; travel is not inferred from a purchase alone.
List known journeys, optionally for a ticket. Never infer travel from a purchase alone.
| Name | Required | Description | Default |
|---|---|---|---|
| ticket_id | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds crucial conceptual context by stating journeys are 'known' and cannot be inferred from a purchase. This behavioral constraint goes beyond standard operational hints like 'readOnlyHint' and helps manage agent expectations regarding data completeness.
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 highly concise, using only two sentences to convey the tool's function, constraints, and usage boundaries without any filler. The key pieces of information are immediately front-loaded in the first clause.
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 the low complexity (one optional parameter) and the comprehensive nature of the provided annotations, the description is robust. It successfully frames the tool's scope and limitations, which is the most important context for an AI agent.
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?
With 0% schema description coverage, the description provides necessary semantic value by explicitly defining the parameter's role as optional and tied to an identifier ('optionally for a ticket'). This clarifies that 'ticket_id' acts as a lookup mechanism for known data.
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 the action (List), the resource (known journeys), and the optional constraint (optionally for a ticket). This distinction helps the AI understand that the tool retrieves existing data rather than creating or updating it.
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 tool includes a vital negative constraint: 'Never infer travel from a purchase alone.' This provides strong guidance on when the tool should and should not be used, preventing logical misuse by the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.