Get one preference section by ID, including its topics. Use this when you already know which section you need; list_preference_sections returns every section with its topics in one call.
| Name | Required | Description | Default |
|---|---|---|---|
| section_id | Yes | Id of the preference section |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already establishes safety, and the description adds useful behavioral context by stating that the response includes topics and that the list variant returns everything at once. It does not discuss error cases or pagination, but these are not critical for a simple single-get operation.
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?
Two concise sentences with the core action front-loaded and the alternative explanation placed second. Every word earns its place, and there is no redundant restatement of the title or annotation.
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?
For a simple read-only tool with one well-described parameter, the description is complete: it states the resource, the ID lookup behavior, the included topics, and how to choose between this and the sibling list tool. No critical information is missing.
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?
The schema already provides 100% coverage for the single section_id parameter with a clear description. The tool description reinforces that lookup is by ID but does not add new parameter-level semantics, so the baseline score of 3 is appropriate.
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 uses a specific verb and resource ('Get one preference section by ID') and explicitly distinguishes itself from list_preference_sections, so an agent knows exactly what this tool retrieves and how it differs from the closest sibling.
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 provides a clear when-to-use condition ('when you already know which section you need') and names the alternative for the opposite case (list_preference_sections returns every section in one call). This leaves no ambiguity about tool selection.
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.
