Memegician

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations already declare this as a read-only, non-open-world operation, and the description adds useful behavioral context by listing what is returned and its role as a prerequisite to render_meme. It does not describe error behavior for invalid or missing template IDs, but that is a relatively minor gap given the 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?

The description is two efficient sentences with the return contents front-loaded and the workflow instruction clearly separated. The parenthetical clarification about ordered caption slots is useful and no wording is wasted.

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 parameter and no output schema, the description covers the key returned information and the render_meme prerequisite. The main missing piece is guidance on sourcing or validating template_id, which would make it fully complete.

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%, and the single template_id parameter has no description or constraints in the schema. The description only implies that template_id selects a template; it does not explain how to obtain a valid ID, whether it comes from search or trending tools, or what happens if it is invalid.

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 template's text slots") and clarifies what the returned content includes, such as ordered caption slots, description, usage notes, and examples. It distinguishes itself from search/trending siblings only implicitly by saying "one template," rather than naming them.

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 explicitly states the workflow condition "Call this before render_meme," which gives an agent clear guidance on sequencing. It does not specify when to use get_trending_meme_templates or search_meme_templates instead, so alternatives remain implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the read-only and closed-world safety profile. The description adds valuable context about the data source and time window (US Google search volume, this month) and notes biggest risers, but it does not clarify ordering, default limit behavior, or the shape of the returned lists.

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 definition is two short sentences with the main resource and scope front-loaded. There is no redundant or filler wording, and the use-case sentence follows naturally.

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 this is close to sufficient, but the description leaves out limit semantics and does not explain the return structure beyond mentioning two categories. With no output schema, an agent has to infer whether the response is two lists, a combined ranking, or how many items are returned.

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%, and the single optional parameter, limit (1-25), is never mentioned in the description. The description therefore adds no meaning about what limit controls or whether it applies to both ranked lists or only one.

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 resource and scope: meme templates ranked by current-month US Google search volume, plus biggest risers. This distinguishes it from search_meme_templates and get_meme_template, though it does not explicitly name those siblings.

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 phrase 'Useful for picking a timely format' implies a use case but gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives such as search_meme_templates for keyword-based discovery.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare a non-read-only, non-destructive, closed-world write, so the safety profile is covered. The description adds real value beyond them by disclosing that the call persists a permanent URL (a durable side effect) and that captions map positionally to text slots with "" as an empty-slot sentinel. It omits rate limits or per-template slot-count constraints, which are discoverable only by trial.

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 tight sentences: the outcome is front-loaded, then the parameter convention follows. No filler, no restating of the title, and every clause carries information the schema does not.

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, the description correctly discloses what comes back (image plus permanent URL), and the caption-slot rule covers the trickiest required parameter. The gap is template_id acquisition and aspect_ratio behavior, both of which matter for correct invocation.

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 and it only partly does: it explains captions as one entry per slot in slot order with "" for empty, which the schema cannot convey. template_id's provenance and aspect_ratio's effect (crop, pad, or letterbox) are left entirely unexplained despite the enum.

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?

States a specific verb (draw captions onto a template), the resource (meme template), and the result (finished image plus permanent URL). This clearly separates it from all three siblings, which are read-only template discovery tools (get/search/trending).

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 caption-slot rule is a usage convention, but there is no explicit when-to-use vs. alternatives guidance and no pointer telling the agent to obtain template_id from search_meme_templates or get_meme_template first. The workflow context is implied rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description earns some credit by listing the return payload (template ids, names, slot counts, blank image URLs), which matters since there is no output schema, but it says nothing about result ordering, relevance ranking, or what an empty result looks like.

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, no filler, and the core capability is front-loaded ahead of the return-value detail. The parenthetical examples are the most efficient part of the text and directly aid query formulation.

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 two-parameter read-only search with no output schema, the definition covers purpose, query intent, and return shape, which is close to sufficient. The remaining gap is behavioral detail on `limit` and result ordering, which an agent would need to page or size results deliberately.

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 schema contributes only min/max constraints and no meaning. The description compensates well for `query` by characterizing it as an emotion, situation, or name with examples, but the `limit` parameter is never mentioned and no default or result-count behavior is given.

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 and resource ("find meme templates") and qualifies the search dimension as an emotion, situation, or name, with three concrete example queries. It does not explicitly distinguish itself from sibling get_meme_template (lookup by id) or get_trending_meme_templates, so it falls just short of a 5.

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?

Usage is implied rather than stated: an agent can infer this is the keyword-discovery entry point before calling get_meme_template or render_meme, but the description never says so. There are no exclusions or prerequisites, and no mention of when to prefer the trending sibling instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.