get_exampleReturn one built-in example design with its blocks, part explanations and its own test, by id from list_examples. Large designs (the 0-9 counter has about 2,500 blocks, the 00-59 clock about 5,100) are long. Do not use it to show an example to the user: use show with example set.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, closed-world and non-destructive, so safety is covered; the description instead adds genuinely new behavioral context: the response is large and size scales with design complexity (2,500 vs 5,100 blocks). It stops short of saying whether such large payloads are truncated or paginated, which is the one piece of behavior an agent calling a read tool with 5,100-block responses would want.
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 sentences, front-loaded with what is returned, then a size caveat, then the exclusion. Every sentence earns its place and nothing is repeated from the schema or annotations.
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 and no parameter descriptions, the description compensates by enumerating the return contents, warning about payload size with concrete magnitudes, and routing the display use case elsewhere. An agent has everything needed to decide and call correctly.
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 coverage is 0% for the single `id` parameter, so the description must carry the meaning — and it does, identifying the id as coming 'from list_examples'. It does not state the id's format or whether an unknown id errors versus returns empty, leaving a small gap.
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?
Specific verb ('Return') plus a precisely scoped resource ('one built-in example design') and an explicit payload listing (blocks, part explanations, its own test). It also names where the id comes from (list_examples) and separates itself from show, so an agent can distinguish it from all three relevant siblings without opening a 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?
Explicit negative guidance — 'Do not use it to show an example to the user: use show with example set' — names the alternative and the condition that selects it. The id source ('from list_examples') closes the remaining workflow question of how to obtain the required parameter.
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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