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

With no annotations, the description carries the responsibility of disclosing behavior. It states the return format ('Formatted string with movie reviews') and default parameter behaviors, but does not mention potential errors, pagination behavior beyond the page parameter, or any rate-limits. The tool is a simple read operation, so the provided info is adequate but not rich.

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 with a clear purpose, followed by a concise, well-structured Args list. Every element adds value: the purpose, the three parameters with defaults, and the return format. No unnecessary words or repetition.

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?

Given the tool's simplicity, the description covers the essential aspects: what it does, the parameters, and the return value. An output schema exists, so detailed return structure is not required here. The description is complete enough for a straightforward retrieval tool.

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 has no parameter descriptions (0% coverage), but the description compensates fully by explaining each parameter: movie_id as TMDB ID, language as language code with default en-US, and page as result page with default 1. This adds meaning beyond the raw schema types and defaults.

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 'Get the user reviews for a movie from TMDB', using a specific verb and resource. It distinguishes from siblings like tmdb_tv_reviews by specifying 'movie' and from tmdb_review_details by focusing on all reviews rather than a specific review.

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 clearly implies when to use this tool: when user reviews for a movie are needed. It does not explicitly exclude alternatives like tmdb_tv_reviews, but the resource specification makes it obvious. Default parameter values are provided, offering implicit guidance on typical usage.

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?

With no annotations, the description carries the full burden. It discloses the return type ('Formatted string with multi-search results') and lists parameters, but adds little beyond the schema. It does not mention rate limits, authentication, pagination behavior, or how results are grouped, though for a simple search tool this may be sufficient.

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 efficiently structured with an overview line, Args section, and Returns section. Every sentence is informative and there is no redundant fluff, though the format could be tighter.

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?

Given the tool's simplicity and the presence of an output schema, the description covers the core aspects: purpose, parameters, and return type. It does not explicitly explain how multi-search results are organized, but that is likely handled by the output schema, so this is acceptable.

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. It lists all four parameters with meaningful explanations ('text query to search for', 'include adult content', 'Language code', 'Page of results') and includes defaults. This adds clarity beyond the bare schema names.

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 'Multi-search for movies, TV shows, and people using the TMDB API', which specifies the verb (search), the resource (TMDB API), and the scope (multiple types). This distinguishes it from siblings like tmdb_search_movies, which likely focuses on movies only.

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 implies usage for multi-type searches but does not explicitly state when to use this tool versus alternatives like tmdb_search_movies for movie-only queries. No exclusions or conditions are provided, just the general scope.

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?

With no annotations, the description carries the full burden. It discloses that the return is a 'Formatted string with review details,' but it does not mention error handling, authentication requirements, side effects, or any other behavioral traits. This is minimal transparency beyond the obvious read 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?

The description is exceptionally concise, using a single sentence plus clearly labeled Args and Returns sections. There is no fluff, and all information is front-loaded with the primary verb and resource.

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 one-parameter retrieval tool, the description is adequate: it states purpose, describes the parameter, and mentions the return format. However, it omits usage context such as how to get a review_id, relationship to sibling review-listing tools, and potential error scenarios. Given no annotations and an output schema that may cover return details, this is a mid-level score.

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 has no property descriptions (0% coverage). The description's Args section adds 'review_id: The TMDB review ID (required).' This provides a label and indicates it is required, but the meaning is nearly tautological. It does not explain the ID's format or how to obtain one, though for a single parameter it offers some compensation.

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: 'Retrieve the details of a movie or TV show review from TMDB.' The verb is specific and the resource is well-defined. It also distinguishes itself from siblings like tmdb_movie_reviews/tmdb_tv_reviews by focusing on individual review details rather than lists.

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?

No explicit usage guidance is provided. The description does not mention when to use this tool versus alternatives, nor does it reference sibling tools or how to obtain a review_id. The intended usage is only implied by the tool's purpose.

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?

With no annotations provided, the description must carry the full burden. It does disclose the return format ('Formatted string with movie search results'), which is useful. However, it does not explicitly state that this is a read-only operation or mention any side effects, permissions, or error behavior, which is a gap given the absence of 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 concise and front-loaded with the primary purpose. The Args and Returns sections are logically structured, but it redundantly repeats defaults already present in the schema. Still, everything included serves a purpose, and it remains reasonably compact.

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?

The description covers all parameters and states the return type, but it lacks usage context such as when to choose this tool over siblings. Given the output schema exists, the minimal return description is acceptable, but the overall guidance is incomplete for an agent deciding which search tool to use.

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 has no descriptions for parameters (0% coverage), so the description's parameter explanations are essential. It lists all 7 parameters with brief meanings (e.g., 'query: The text query to search for (required)'). However, it does not clarify the distinction between 'primary_release_year' and 'year', and lacks format details for fields like language and region, so it is not fully comprehensive.

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 action ('Search for movies') and the resource (TMDB API), making the core purpose unambiguous. However, it does not explicitly distinguish itself from sibling tools like tmdb_multi_search or tmdb_trending_search, so it lacks explicit sibling differentiation.

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 no guidance on when to use this tool versus alternatives such as tmdb_multi_search or tmdb_trending_search. It only describes what the tool does without any context on selection criteria or exclusions.

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?

No annotations are provided, so the description must convey behavior. It states the return type as a 'Formatted string', which is useful, but it omits any details about authentication, rate limits, or error handling. Since this is a read-only trending operation, the lack of mutation warnings is acceptable, but the description is not rich in behavioral context.

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 extremely concise and well-structured: a one-sentence purpose, an Args section, and a Returns line. Every sentence adds value with no redundancy or filler.

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 two-parameter tool with an output schema, the description is sufficiently complete. It covers the parameters and return type. However, it lacks any reference to context like pagination or response formatting, but since an output schema exists, the description does not need to explain those details.

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 provides no descriptions (0% coverage), so the description fully compensates by explaining both parameters. It specifies the allowed values for time_window ('day' or 'week') and the default for language ('en-US'). This adds meaning far beyond the bare schema definitions.

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 'Get' and identifies the resource as 'trending movies, TV shows, and people from TMDB'. This clearly distinguishes it from sibling tools like tmdb_search_movies or tmdb_multi_search, which focus on searching rather than trending content.

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 does not provide any guidance on when to use this tool versus alternatives. Sibling tools for search and reviews are obvious alternatives, but no explicit exclusions or comparison are mentioned. The 'Args' section only explains parameters, not usage context.

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?

With no annotations, the description carries the full burden. It does mention the return format ('Formatted string') and parameter defaults, providing some behavioral insight. However, it does not disclose read-only status, rate limits, error handling, or other edge cases, which limits transparency.

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 concise and well-structured: a single-purpose sentence followed by Args and Returns sections. Every element earns its place, and the purpose is front-loaded.

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?

The tool is simple, and the description covers purpose, parameters, and return type. However, it lacks usage context (when to prefer over similar tools) and behavioral caveats (safety, errors). Given the absence of annotations, additional context would make it more 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%, so the description's parameter details are vital. It explains series_id is required, language defaults to en-US, and page defaults to 1, adding meaning beyond the raw schema types and defaults. It could be even more explicit about language code format, but it is adequate.

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 action ('Get the reviews'), the target resource ('a TV show'), and the source ('TMDB'). It also inherently distinguishes itself from the sibling tmdb_movie_reviews by explicitly targeting TV shows, not movies.

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?

There is no guidance on when to use this tool versus alternatives like tmdb_movie_reviews or tmdb_search_movies. The description simply defines what the tool does without any exclusions, prerequisites, or recommendations.

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