list_prompts
Lists Vertex prompts matching a given display name.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| page_size | No | ||
| project_id | No | ||
| location_id | No | ||
| display_name | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Lists Vertex prompts matching a given display name.
| Name | Required | Description | Default |
|---|---|---|---|
| page_size | No | ||
| project_id | No | ||
| location_id | No | ||
| display_name | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral disclosure burden. It implies a read-only operation but does not explicitly state that it is non-destructive, nor does it mention pagination, rate limits, or authentication requirements. The page_size parameter hints at pagination, but the description does not clarify return behavior.
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 a single sentence, which is concise and front-loaded. However, it is too terse; it could include important context like pagination or parameter roles without becoming verbose. It is adequate but not excellent.
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 tool has four parameters, an output schema (not shown), and no annotations, the description is incomplete. It omits details about return format, pagination, error cases, and the roles of project_id and location_id. The output schema may cover return values, but the description still lacks needed context.
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%, so the description must compensate. It adds semantic value only for display_name, explaining it is used for filtering. However, it provides no explanation for page_size, project_id, or location_id, leaving their purpose unclear despite being declared in the schema.
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 (lists) and resource (Vertex prompts), and specifies a filtering criterion (display name). This distinguishes it from siblings like create_prompt or read_prompt. However, it does not clarify what 'matching' means (e.g., exact or partial match), so it is not fully precise.
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 provides no guidance on when to use this tool versus alternatives. For example, if a specific prompt ID is known, read_prompt would be more appropriate, but this is not mentioned. There is no mention of when not to use it or what prerequisites exist.
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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