Return the full record for a single component: title, description, narrative body, the primary HTML pattern, list of slots (placeholders the model should fill), VML/responsive flags, and all code examples. Use after list_components to fetch the actual HTML pattern to paste into an email.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Component name. Get the list from list_components first. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It gives detailed transparency into the return payload, but it does not explicitly state that this is a read-only operation or mention any potential side effects, permissions, or limitations. The 'get' verb implies non-mutating behavior, but the description leaves the safety profile implicit.
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 two sentences long and front-loaded: the first sentence lists all return fields in a structured way, and the second places the tool in a workflow. There is no redundant or filler content.
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 single-parameter get operation with no output schema, the description fully enumerates the expected return fields and provides a clear usage scenario. It gives an agent enough information to know exactly what will be returned and when to call the tool, making it complete for its complexity.
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 input schema already provides 100% coverage for the single parameter 'name' with an enum and explicit guidance to 'Get the list from list_components first.' The description repeats this workflow cue but adds no new semantic detail about the parameter. With full schema coverage, a baseline 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 clearly states the tool's function with a specific verb ('Return') and resource ('full record for a single component'), and enumerates the contents (title, description, narrative body, HTML pattern, slots, VML/responsive flags, code examples). It distinguishes from sibling tools by focusing on single-component lookup and explicitly referencing list_components.
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 clear usage context: 'Use after list_components' to fetch the actual HTML pattern for an email, which indicates the immediate preceding step. However, it does not explicitly state when not to use this tool or name alternatives, so it stops short of full criterion for a 5.
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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