search_meme_templatesSearch memebo.at's catalog of 25,000+ meme templates by name, other names or topic (e.g. "drake", "distracted boyfriend", "cat"). Returns matching templates with their slug (use it with create_meme), image URL and a suggested caption count.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 10) | |
| query | Yes | Search terms, e.g. "surprised pikachu" |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Input schema / additionalPropertiesRemoved value: -falseDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral burden. It does well to disclose what comes back (slug, image URL, suggested caption count) and the catalog scale, but it never states ranking behavior, what happens on zero matches, or that the operation is a safe read — gaps that matter more without annotations.
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 sentences, zero waste. The search scope and examples come first, and the downstream handoff to create_meme follows, so the information is front-loaded exactly where an agent needs it.
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 only two parameters and no output schema, the description covers the essentials: search dimensions, return fields, and the cross-tool linkage. It stops short of the search-behavior details (fuzzy matching, ordering, empty-result handling) that an agent might want, but nothing critical 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?
Schema coverage is 100%, so the baseline is 3; the description earns more by explaining that the query field accepts names, alternate names, or topics and giving example queries ("drake", "distracted boyfriend", "cat"). The limit parameter is left to the schema, but it is fully documented there.
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 states a specific verb (search) and a specific resource (memebo.at's catalog of 25,000+ meme templates), and narrows the search dimensions to name, alternate names, or topic with concrete examples. It also distinguishes itself from create_meme by noting that the returned slug is the input for that tool, so an agent can place it in the workflow without opening any 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?
The description makes clear when this tool applies (you need to find a template) and hands off downstream by saying "use it with create_meme." It does not mention the get_meme_template sibling or say when to prefer it over this search, which is the only routing gap.
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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