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

With no annotations provided, the description carries full burden for behavioral disclosure. It states 'Get list' which implies a read operation, but doesn't specify if it requires authentication, has rate limits, returns paginated results, or details about the format/content of the genre list. This leaves significant gaps for a tool that might interact with an external API.

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 a single, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates what the tool does without unnecessary elaboration.

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 (0 parameters, no output schema), the description is minimally adequate. However, without annotations or output schema, it doesn't provide enough context about the return value format, authentication needs, or error handling, which could be important for an AI agent to use it correctly in practice.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter information, and it correctly doesn't mention any parameters, earning a baseline score of 4 for this dimension.

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 'Get list of movie genres' clearly states the verb ('Get') and resource ('movie genres'), making the purpose immediately understandable. However, it doesn't differentiate from its sibling 'genre_tv_list' which presumably gets TV genres, so it misses full sibling distinction.

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. It doesn't mention any prerequisites, context for usage, or comparison with sibling tools like 'genre_tv_list' for TV genres or other genre-related operations.

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 carries full burden. 'Get list' implies a read-only operation, but it doesn't disclose important behavioral traits like whether this requires authentication, rate limits, what format the list returns (e.g., IDs, names, hierarchical), or if it's cached/static data. The description is too minimal for a tool with no annotation coverage.

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 perfectly concise at three words, front-loading the essential information with zero wasted language. Every word ('Get', 'list', 'TV genres') earns its place in communicating the core functionality.

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 (0 parameters) but lack of annotations and output schema, the description is insufficient. It doesn't explain what the output looks like (e.g., array of genre objects with ids/names), whether it's comprehensive or filtered, or how it relates to other TV tools. For a tool with no structured output documentation, more context is needed.

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?

With 0 parameters and 100% schema description coverage, the baseline is 4. The description appropriately doesn't discuss parameters since there are none, and the schema already documents the empty object structure completely.

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 'Get list of TV genres' clearly states the verb ('Get') and resource ('TV genres'), making the purpose immediately understandable. However, it doesn't distinguish from its sibling 'genre_movie_list' beyond the 'TV' vs 'movie' distinction, which is implicit but not explicit.

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. With sibling tools like 'tv_details' or 'tv_popular' that might also involve genres, there's no indication of when this specific genre list retrieval is appropriate versus getting genre information through other means.

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 carries the full burden of behavioral disclosure. While 'Get' implies a read operation, it doesn't mention any behavioral traits such as rate limits, authentication requirements, error handling, or what happens with invalid IDs. This leaves significant gaps for a tool that interacts with external data.

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 front-loaded with a single, clear sentence that states the core functionality. There's no wasted language, making it efficient for quick understanding.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'cast and crew' data is returned (e.g., format, fields), potential limitations, or how it differs from similar tools. For a tool with no structured output information, more context is needed to guide effective 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 description adds minimal value beyond the input schema, which has 100% coverage. It mentions 'by ID' but doesn't elaborate on the 'movie_id' parameter beyond what's in the schema ('TMDB movie ID'). With high schema coverage, the baseline is 3, as the schema already documents the parameter adequately.

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 purpose with a specific verb ('Get') and resource ('movie cast and crew'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'movie_details' or 'person_movie_credits', which might also provide related information.

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. With many sibling tools available (e.g., 'movie_details', 'person_movie_credits'), there's no indication of when this specific cast/crew retrieval is preferred, leaving the agent to guess based on 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?

No annotations are provided, so the description carries full burden. It states a read operation ('Get') but doesn't disclose behavioral traits such as rate limits, authentication needs, error handling, or what 'details' includes. This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence with no wasted words. It's front-loaded and appropriately sized for a simple tool, making it easy to parse quickly.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'details' entail, potential return values, or error cases. For a tool with rich sibling context and no structured output, more information is needed to be fully helpful.

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 100%, with the parameter 'movie_id' documented as 'TMDB movie ID'. The description adds no additional meaning beyond the schema, such as format examples or constraints, so it meets the baseline for high schema coverage.

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 verb 'Get' and resource 'movie details', specifying it's by ID. It distinguishes from siblings like movie_popular or search_movie by focusing on ID-based retrieval, though it doesn't explicitly name alternatives.

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 guidance on when to use this tool versus alternatives is provided. The description implies usage when you have a movie ID, but it doesn't mention prerequisites, exclusions, or compare to siblings like movie_credits or tv_details.

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 carries the full burden of behavioral disclosure. It states the action ('Get') but doesn't mention any behavioral traits such as rate limits, authentication needs, pagination behavior, or what the return format looks like. This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence with zero waste. It's front-loaded and directly communicates the core functionality without unnecessary elaboration, making it easy for an agent to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like response format, error handling, or usage constraints. For a tool with no structured data beyond the input schema, more context is needed to guide the agent effectively.

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 100% description coverage, with clear documentation for both parameters ('page' and 'region'). The description doesn't add any semantic details beyond what the schema provides, such as explaining how 'region' affects results or default behaviors. Baseline 3 is appropriate since the schema does the heavy lifting.

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 purpose with a specific verb ('Get') and resource ('now playing movies in theaters'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'movie_upcoming' or 'movie_popular', which might have overlapping scopes, so it misses the highest score.

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. With many sibling tools available (e.g., 'movie_upcoming', 'movie_popular'), there's no indication of context, exclusions, or prerequisites, leaving the agent to infer usage based on the name alone.

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 carries the full burden of behavioral disclosure. 'Get popular movies' implies a read-only operation but doesn't cover critical aspects like rate limits, authentication needs, pagination behavior, or what 'popular' entails (e.g., algorithm, time frame). This is inadequate for a tool with no annotation support.

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 with just three words, front-loaded with the core action. There's no wasted text, making it easy to parse, though this conciseness comes at the cost of detail.

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 no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what 'popular' means, how results are returned, or usage context relative to siblings. For a tool in a crowded namespace, more guidance is needed to ensure correct agent selection.

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 100%, so the schema fully documents the parameters (page and region). The description adds no additional meaning beyond what's in the schema, such as explaining how 'region' affects results or default values. Baseline 3 is appropriate when the schema does all the work.

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 'Get popular movies' clearly states the action (get) and resource (popular movies), but it's vague about what 'popular' means and doesn't differentiate from siblings like 'movie_top_rated' or 'movie_now_playing' which might overlap in purpose. It's functional but lacks specificity.

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 guidance is provided on when to use this tool versus alternatives like 'movie_top_rated', 'movie_now_playing', or 'trending_movie_day'. The description doesn't mention context, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

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 carries the full burden of behavioral disclosure. 'Get movie recommendations by ID' implies a read-only operation but doesn't specify critical traits like whether it requires authentication, rate limits, pagination behavior (beyond the 'page' parameter in schema), or what the output format looks like (e.g., list of movies with details). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, straightforward sentence ('Get movie recommendations by ID'), making it appropriately concise and front-loaded. There's no wasted verbiage, and it directly states the core function. However, it could be slightly improved by adding a bit more context without sacrificing brevity, but it's efficient as is.

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 complexity of a recommendation tool with 2 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'recommendations' entail (e.g., similar movies, user-based suggestions), how results are structured, or any behavioral aspects like error handling. For a tool that likely returns a list of movies, more context is needed to guide effective use, especially with many sibling tools that might serve similar purposes.

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 description adds minimal meaning beyond the input schema, which has 100% coverage with clear descriptions for 'movie_id' (TMDB movie ID) and 'page' (page number 1-1000). It implies that 'movie_id' is used to fetch recommendations, but doesn't elaborate on how recommendations are generated or the relationship between parameters. With high schema coverage, the baseline is 3, as the description doesn't compensate with additional insights but doesn't detract either.

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 'Get movie recommendations by ID' restates the tool name 'movie_recommendations' with minimal elaboration, making it tautological. It specifies the action ('Get') and resource ('movie recommendations') but lacks detail on what 'recommendations' entails (e.g., similar movies, personalized suggestions). Compared to siblings like 'movie_similar' or 'movie_popular', it doesn't clearly differentiate its purpose beyond the basic name.

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. With siblings like 'movie_similar' and 'movie_popular' that might overlap in functionality, it doesn't specify scenarios (e.g., use for recommendations based on a specific movie ID, not for trending or genre-based lists). There's no mention of prerequisites, exclusions, or comparative contexts, leaving usage ambiguous.

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 carries the full burden of behavioral disclosure. It mentions 'Get' but doesn't specify if this is a read-only operation, requires authentication, has rate limits, or what the output format might be. This leaves significant gaps for an agent to understand how to use it effectively.

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 with a single sentence that directly states the tool's purpose. It's front-loaded and wastes no words, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'similar movies' means (e.g., based on genre, ratings, or other criteria), the return format, or error handling, which are crucial for an agent to use this tool correctly in a movie database context.

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 100%, so the input schema already documents both parameters ('movie_id' as TMDB movie ID and 'page' as page number). The description adds no additional semantic context beyond what the schema provides, such as examples or usage tips, but it doesn't need to compensate for gaps.

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 verb 'Get' and the resource 'similar movies by ID', making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'movie_recommendations' or 'tv_similar', which might serve similar functions for different contexts.

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 'movie_recommendations' or 'tv_similar', nor does it mention prerequisites like needing a valid movie ID. It simply states the action without 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Get top rated movies', which implies a read-only operation but lacks details on rate limits, authentication needs, pagination behavior (implied by the 'page' parameter), or what 'top rated' entails (e.g., sorting criteria, data freshness). This leaves significant gaps in understanding how the tool behaves beyond basic retrieval.

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 with 'Get top rated movies', a single sentence that front-loads the core action and resource. There is no wasted language or redundancy, making it efficient for quick comprehension. However, this conciseness comes at the cost of detail, which is reflected in lower scores for other dimensions.

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 complexity (a list retrieval with parameters), lack of annotations, and no output schema, the description is incomplete. It does not address behavioral aspects like pagination, sorting, or error handling, and fails to differentiate from sibling tools. For a tool with parameters and no structured output documentation, more context is needed to guide effective 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 100% description coverage, with clear documentation for 'page' and 'region' parameters. The description adds no additional meaning beyond the schema, as it does not explain parameter usage, defaults, or interactions. With high schema coverage, the baseline score is 3, as the description does not compensate but also does not detract from the schema's clarity.

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 'Get top rated movies' clearly states the verb ('Get') and resource ('top rated movies'), making the purpose understandable. However, it lacks specificity about what 'top rated' means (e.g., based on ratings, popularity, or a specific metric) and does not differentiate from siblings like 'movie_popular' or 'tv_top_rated', which offer similar list functionalities. This makes it vague in distinguishing its exact scope.

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. It does not mention scenarios for usage, exclusions, or comparisons to siblings such as 'movie_popular' (for popularity-based lists) or 'trending_movie_day' (for trending content). Without any context, the agent must infer usage from the tool name alone, which is insufficient for optimal selection.

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 carries the full burden of behavioral disclosure. 'Get upcoming movies' implies a read-only operation but doesn't specify authentication needs, rate limits, pagination behavior, or what 'upcoming' entails (e.g., future releases only). It lacks details on response format or error handling.

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 with a single sentence ('Get upcoming movies'), which is front-loaded and wastes no words. It efficiently communicates the core purpose without unnecessary elaboration.

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 no annotations and no output schema, the description is incomplete for a tool with 2 parameters. It doesn't explain what 'upcoming' means, how results are returned, or any behavioral traits like pagination or regional filtering. For a read operation with structured inputs, more context is needed to guide the agent effectively.

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 100%, so the schema already documents both parameters ('page' and 'region') adequately. The description adds no additional meaning beyond what the schema provides, such as explaining how 'region' affects results or default behavior when parameters are omitted. Baseline 3 is appropriate as the schema does the heavy lifting.

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 'Get upcoming movies' states a clear verb ('Get') and resource ('upcoming movies'), but it's vague about scope and doesn't distinguish from siblings like 'movie_now_playing' or 'movie_popular'. It lacks specificity about what 'upcoming' means (e.g., release dates, time frame).

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 guidance is provided on when to use this tool versus alternatives like 'movie_now_playing' or 'movie_popular'. The description doesn't mention context, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.

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 carries the full burden. It states it's a read operation ('Get'), implying no destructive effects, but doesn't disclose behavioral traits like rate limits, authentication needs, response format, or pagination. This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place without redundancy.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the return values include (e.g., video types, URLs, metadata) or address potential errors. For a tool with no structured behavioral data, more context is needed to be fully helpful.

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 description coverage is 100%, with the single parameter 'movie_id' fully documented in the schema as 'TMDB movie ID'. The description adds no additional meaning beyond implying it's used to fetch videos, which is already clear from the purpose. Baseline 3 is appropriate as the schema does the heavy lifting.

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 verb 'Get' and the resource 'movie videos (trailers, teasers, etc.) by ID', making the purpose specific and understandable. It distinguishes from siblings like movie_details or movie_credits by focusing on video content, though it doesn't explicitly contrast with tv_videos or other video-related tools.

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 guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention if this is for retrieving all videos for a movie or how it differs from movie_details (which might include videos) or tv_videos. The description lacks context about prerequisites 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 carries the full burden of behavioral disclosure. It states this is a 'Get' operation, which suggests a read-only action, but doesn't clarify if it requires authentication, has rate limits, or what happens with invalid IDs (e.g., errors vs. empty responses). For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior and constraints.

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 with a single sentence ('Get person details by ID') that front-loads the core purpose without any wasted words. Every part of the sentence earns its place by specifying the action, resource, and key input, making it efficient and easy to parse for an AI agent.

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 (1 parameter, 100% schema coverage) and lack of output schema, the description is incomplete. It doesn't explain what 'details' include (e.g., biography, filmography), potential response formats, or error handling. Without annotations or output schema, the description should provide more context to fully guide usage, but it remains minimal, leaving the agent to infer behavior from the tool name and schema alone.

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 description adds minimal meaning beyond the input schema, which has 100% coverage and fully documents the single parameter 'person_id' as a TMDB person ID. The description mentions 'by ID', aligning with the schema, but doesn't provide additional context like ID format examples or validation rules. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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') and resource ('person details by ID'), making the purpose immediately understandable. It distinguishes this tool from siblings like search_person or person_movie_credits by focusing on retrieval of details for a specific person ID rather than searching or listing credits. However, it doesn't specify what 'details' include, leaving some ambiguity about the scope of information returned.

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 when you have a specific TMDB person ID and need their details, which is clear from the phrasing 'by ID'. However, it doesn't explicitly state when not to use this tool (e.g., for searching without an ID) or name alternatives like search_person for when you don't have an ID. The context is implied but not fully articulated with exclusions or direct sibling comparisons.

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 carries full burden. It states a read operation ('Get'), but doesn't disclose behavioral traits like authentication needs, rate limits, response format, pagination, or error handling. This is a significant gap for a tool with zero annotation coverage.

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 a single, efficient sentence with zero waste. It's front-loaded with the core purpose, making it easy to scan and understand quickly.

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 no annotations, no output schema, and a single parameter with full schema coverage, the description is incomplete. It doesn't explain what 'movie credits' includes (e.g., cast/crew roles, dates) or the return format, leaving gaps for an AI agent to use it 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 description coverage is 100%, with the parameter 'person_id' documented as 'TMDB person ID'. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints. Baseline 3 is appropriate when schema does the heavy lifting.

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 verb ('Get') and resource ('person movie credits'), specifying it's by ID. It distinguishes from siblings like 'person_details' (general info) and 'person_tv_credits' (TV-specific), but doesn't explicitly differentiate from 'movie_credits' (which might be for movies rather than people).

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 guidance on when to use this tool versus alternatives like 'person_details' for general info or 'person_tv_credits' for TV credits. The description implies usage when you have a person ID and want movie credits, but lacks explicit context 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states a read operation ('Get') but doesn't mention rate limits, authentication needs, response format, pagination, or error conditions. For a tool that likely queries an external API, this leaves significant behavioral gaps.

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 at just 5 words, front-loading the essential information with zero wasted words. Every element ('Get', 'person TV credits', 'by ID') serves a clear purpose in communicating the tool's function.

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 no annotations, no output schema, and a single parameter with good schema coverage, the description is incomplete. It doesn't explain what 'TV credits' includes (e.g., acting roles, crew positions), the response format, or any limitations. For a tool that returns potentially complex data, more context is needed.

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 100% description coverage (the 'person_id' parameter is fully documented as 'TMDB person ID'), so the baseline is 3. The description adds no additional parameter information beyond what's in the schema, but doesn't need to compensate for any gaps.

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 verb ('Get') and resource ('person TV credits by ID'), making the purpose understandable. It distinguishes this tool from siblings like 'person_movie_credits' by specifying TV credits, but doesn't explicitly differentiate from 'person_details' or 'tv_credits' which might overlap in scope.

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 like 'person_movie_credits' for movie credits or 'person_details' for general person information. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.

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 carries full burden but reveals little behavior. It doesn't mention pagination behavior (implied by 'page' parameter but not explained), rate limits, authentication needs, response format, or what happens with empty results. 'Search' implies read-only, but this isn't explicitly stated.

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 at just 5 words with zero waste. It's front-loaded with the core purpose. Every word earns its place, though this conciseness comes at the cost of completeness.

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 search tool with 3 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the search returns, how results are ordered, pagination behavior, or how it differs from similar search tools. The minimal description leaves too many questions unanswered.

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 100%, so parameters are fully documented in the schema. The description adds no additional meaning about parameters beyond implying 'query' is the search term. Baseline 3 is appropriate when schema does the heavy lifting.

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 'Search for movies by query' clearly states the verb ('search') and resource ('movies'), but it's vague about scope and doesn't distinguish from siblings like 'search_multi' or 'search_tv'. It doesn't specify what kind of search this is (title, keyword, etc.) or what fields are searched.

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 guidance is provided about when to use this tool versus alternatives like 'search_multi' (which searches across movies, TV, and people) or 'search_tv'. The description doesn't mention any context, prerequisites, or exclusions for 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Search' implies a read operation, the description doesn't mention pagination behavior (implied by the page parameter), rate limits, authentication requirements, or what the response format looks like. This is inadequate for a search tool with no annotation coverage.

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 - a single sentence that communicates the core functionality without any wasted words. It's appropriately sized for a straightforward search tool and front-loads the essential information.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the search returns (e.g., combined results or separate sections), how results are ordered, or any limitations. For a multi-resource search tool in a rich API with many sibling tools, this minimal description leaves significant gaps.

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 100%, so the schema already documents all three parameters. The description doesn't add any meaningful context about parameters beyond what the schema provides, such as search scope limitations or how the 'include_adult' parameter affects results. Baseline 3 is appropriate when the schema does the heavy lifting.

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 verb ('Search') and resources ('movies, TV shows, and people'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like search_movie, search_tv, and search_person, which perform similar but more specific searches.

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. With multiple sibling search tools (search_movie, search_tv, search_person), there's no indication whether this is a combined search or when one might prefer the more specific tools.

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 carries full burden for behavioral disclosure. It fails to mention critical aspects like whether this is a read-only operation, pagination behavior beyond the schema, rate limits, authentication needs, or what the search returns. This is inadequate for a tool with parameters.

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 a single, efficient sentence with zero wasted words. It's appropriately sized for a simple search tool and front-loads the core purpose without unnecessary elaboration.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what the search returns, how results are structured, or behavioral traits like error handling. For a search tool with parameters, this leaves significant gaps for an AI agent.

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 100%, so the schema fully documents both parameters. The description adds no additional meaning beyond what's in the schema, such as query examples or pagination context. Baseline 3 is appropriate when the schema does the heavy lifting.

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 verb ('Search') and resource ('people'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'search_movie' or 'search_tv' beyond the resource type, which prevents a perfect score.

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 like 'search_multi' or 'person_details'. It lacks context about query types, scope, or any prerequisites, leaving the agent to infer usage from the tool name alone.

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 carries full burden. It mentions searching by query but doesn't disclose behavioral traits such as pagination behavior (implied by 'page' parameter), rate limits, authentication needs, result format, or whether it's a read-only operation. This leaves significant gaps for an agent to understand how to use it effectively.

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 a single, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple search tool, making it easy to parse quickly.

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 no annotations, no output schema, and multiple sibling tools, the description is incomplete. It doesn't explain return values, usage context, or behavioral constraints, leaving the agent with insufficient information to operate the tool effectively in a complex environment.

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 100%, so the schema fully documents parameters (query, page, include_adult). The description adds no additional meaning beyond implying a search query, which is already covered. Baseline score of 3 is appropriate as the schema does the heavy lifting.

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 verb ('Search for') and resource ('TV shows'), making the purpose immediately understandable. It distinguishes from general search tools like 'search_multi' by specifying TV shows, though it doesn't explicitly differentiate from 'search_movie' or other media-specific searches beyond the title.

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. With siblings like 'search_movie', 'search_person', 'search_multi', and various TV-specific tools (e.g., 'tv_popular', 'tv_details'), there's no indication of when a search is preferred over browsing or filtering by other criteria.

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 carries full burden of behavioral disclosure. It states what the tool does (retrieves trending content) but doesn't describe important behavioral aspects: whether this is a read-only operation, what format the results come in, whether there are rate limits, authentication requirements, or pagination behavior (despite having a 'page' parameter). For a tool with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 - a single sentence that efficiently communicates the core purpose. Every word earns its place: 'Get' (action), 'all trending' (scope), 'of the day' (timeframe), and '(movies, TV, people)' (categories). No wasted words or redundant information.

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 moderate complexity (retrieving trending content with pagination), no annotations, and no output schema, the description is minimally adequate but incomplete. It covers the 'what' but misses important context about behavior, output format, and usage constraints. For a tool that presumably returns data lists, the lack of output information is a notable gap, though the single parameter is well-documented in the schema.

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 description doesn't mention any parameters. However, with 100% schema description coverage (the 'page' parameter is fully documented in the schema with type and range constraints), the baseline is 3. The description doesn't add value beyond what the schema already provides, but doesn't need to compensate for poor schema coverage either.

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 purpose: 'Get all trending of the day (movies, TV, people)' - this specifies the verb ('Get'), resource ('trending'), and scope ('all', 'of the day', categories). It distinguishes from siblings like 'trending_all_week' by specifying 'day' timeframe, but doesn't fully differentiate from 'trending_movie_day' or 'trending_tv_day' regarding the 'all' vs category-specific distinction.

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 context through 'of the day' and 'all' (vs category-specific), suggesting this is for daily trending across all media types. However, it doesn't explicitly state when to use this vs alternatives like 'trending_all_week' (timeframe choice) or 'trending_movie_day' (category-specific vs comprehensive). No explicit when-not or prerequisite guidance is provided.

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 carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't mention any behavioral traits like pagination (despite the 'page' parameter), rate limits, authentication needs, or what 'trending' means (e.g., based on views, ratings). This leaves significant gaps for an agent to understand how to use it effectively.

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 front-loaded: 'Get all trending of the week (movies, TV, people)'. It's a single sentence that efficiently conveys the core purpose without any wasted words, making it easy for an agent to parse quickly.

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 low complexity (1 optional parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavior, usage context, or output format. Without annotations or an output schema, the agent must infer these aspects, making the description incomplete for optimal 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 100% description coverage, with the 'page' parameter documented as 'Page number (1-1000)'. The description adds no additional parameter information beyond what the schema provides. According to the rules, with high schema coverage (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 purpose: 'Get all trending of the week (movies, TV, people)'. It specifies the verb ('Get'), resource ('trending of the week'), and scope ('movies, TV, people'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from siblings like 'trending_all_day' or 'trending_movie_week', which would be needed for a perfect score.

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. It doesn't mention when to prefer this over 'trending_all_day' for daily trends or 'trending_movie_week' for movie-specific weekly trends, nor does it specify any prerequisites or exclusions. Usage is implied by the name and description but not explicitly 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Get') but lacks details on permissions, rate limits, pagination (implied by 'page' parameter but not explained), or response format. This is inadequate for a tool with potential data retrieval complexities.

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 a single, efficient sentence with zero wasted words. It front-loads the core purpose ('Get trending movies of the day'), making it easy to parse quickly without unnecessary elaboration.

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 lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like pagination, error handling, or data format, which are crucial for an agent to use the tool effectively in a complex environment with many siblings.

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 100% description coverage, with the 'page' parameter documented as 'Page number (1-1000)'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without compensating value.

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 verb ('Get') and resource ('trending movies of the day'), making the purpose understandable. However, it doesn't explicitly differentiate from siblings like 'trending_movie_week' or 'trending_all_day', which would require mentioning the specific time frame ('today') more distinctly or contrasting with weekly trends.

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. With many sibling tools (e.g., 'trending_movie_week', 'movie_popular', 'trending_all_day'), there's no indication of context, prerequisites, or exclusions, leaving the agent to guess based on naming alone.

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 carries the full burden of behavioral disclosure. It only states the action ('Get') without mentioning whether this is a read-only operation, if it requires authentication, rate limits, pagination behavior, or what format the results return. For a tool with zero annotation coverage, this is insufficient.

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 a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the core functionality immediately.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'trending' means, how results are determined, the response format, or behavioral constraints. For a tool in a server with many similar alternatives, more context is needed to guide proper usage.

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 100%, so the schema fully documents the single parameter ('page'). The description adds no additional parameter information beyond what's in the schema, which meets the baseline expectation when schema coverage is high.

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 verb ('Get') and resource ('trending movies of the week'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'trending_movie_day' or 'trending_all_week', which would require more specificity for a perfect score.

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 guidance is provided on when to use this tool versus alternatives like 'trending_movie_day' or 'trending_all_week'. The description only states what it does, leaving the agent to infer usage context from the tool name alone.

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 carries full burden for behavioral disclosure. While 'Get' implies a read operation, the description doesn't mention any behavioral traits like rate limits, authentication requirements, response format, pagination behavior, or what 'trending' specifically means in this context. For a tool with no annotation coverage, this is inadequate.

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 a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information about what the tool does.

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 lack of annotations and output schema, the description should provide more context about what 'trending' means, how results are determined, what data is returned, and how to interpret the results. The current description is too minimal for a tool that presumably returns complex TV show data with ranking/trending information.

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 100% description coverage with a single parameter 'page' clearly documented. The description doesn't add any parameter information beyond what's in the schema, which is acceptable given the high schema coverage. The baseline score of 3 reflects adequate but not exceptional parameter documentation.

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 verb 'Get' and resource 'trending TV shows of the day', making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'trending_tv_week' or 'trending_all_day', which would require mentioning the specific time frame 'today' as a distinguishing factor.

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. With multiple trending tools available (trending_all_day, trending_movie_day, trending_tv_week), there's no indication of when this specific TV-focused daily trending tool is preferred over those other options.

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 carries full burden for behavioral disclosure but offers minimal information. It doesn't mention whether this is a read-only operation, what data format is returned, pagination behavior beyond the page parameter, rate limits, authentication requirements, or what 'trending' means algorithmically. The description is insufficient for a tool with behavioral implications.

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 at just 6 words, front-loading the core purpose with zero wasted words. Every element ('Get', 'trending', 'TV shows', 'of the week') contributes essential meaning without redundancy or unnecessary elaboration.

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 lack of annotations and output schema, the description is incomplete for effective tool use. While the purpose is clear, it doesn't address what data is returned, how 'trending' is determined, whether results are filtered by region/language, or other contextual factors needed for proper invocation. For a tool with potential complexity around trending algorithms and data formats, this is inadequate.

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 100% description coverage, with the single parameter 'page' clearly documented in the schema. The description adds no additional parameter information beyond what's in the schema, which is acceptable given the high schema coverage. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 verb 'Get' and resource 'trending TV shows of the week', making the purpose immediately understandable. It distinguishes from siblings like 'trending_tv_day' by specifying the weekly timeframe, though it doesn't explicitly contrast with other trending tools beyond the name.

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 like 'trending_tv_day', 'trending_all_week', or 'tv_popular'. It doesn't mention use cases, prerequisites, or contextual factors that would help an agent choose between similar trending or TV listing tools.

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 carries full burden for behavioral disclosure. It states what the tool does ('Get TV shows airing today') but doesn't describe how it behaves: no information about pagination (implied by the 'page' parameter but not explained), rate limits, authentication needs, data freshness, or what 'airing today' means temporally (timezone, broadcast vs. streaming). This leaves significant gaps for an agent.

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 at four words, front-loaded with the core action and resource. Every word earns its place with no wasted text, making it easy to parse quickly.

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 moderate complexity (fetching dynamic TV data) with no annotations, no output schema, and a simple but incomplete description, this is inadequate. The description doesn't explain what 'airing today' entails, the response format, pagination behavior, or how it differs from siblings, leaving the agent with insufficient context to use it effectively.

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 100% description coverage for its single parameter ('page'), so the schema already documents it fully. The description adds no additional parameter semantics beyond implying pagination through the verb 'Get', which doesn't compensate or clarify beyond the schema. This meets the baseline for high schema coverage.

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 'Get TV shows airing today' clearly states the verb ('Get') and resource ('TV shows airing today'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'tv_on_the_air' or 'trending_tv_day' that might have overlapping functionality, preventing a perfect score.

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 like 'tv_on_the_air' or 'trending_tv_day' from the sibling list. It lacks context about whether this shows currently airing episodes, upcoming premieres, or daily schedules, leaving the agent to guess based on tool names alone.

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 carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't cover critical aspects like rate limits, authentication needs, error handling, or the format/structure of the returned cast and crew data. For a tool with zero annotation coverage, this is a significant gap in 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 extremely concise and front-loaded with a single, direct sentence: 'Get TV show cast and crew by ID'. Every word contributes to understanding the tool's function, with no wasted verbiage or unnecessary elaboration, making it highly efficient for an AI agent.

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 lack of annotations and output schema, the description is incomplete for effective tool use. It doesn't explain what 'cast and crew' data includes (e.g., roles, departments), how results are structured, or any behavioral constraints. For a data retrieval tool with no structured output guidance, this leaves too many unknowns for the agent.

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 description adds minimal semantic value beyond the input schema. It mentions 'by ID', which aligns with the 'tv_id' parameter in the schema, but the schema already has 100% coverage with a clear description ('TMDB TV show ID'). No additional details (e.g., ID source, validation rules) are provided, so it meets the baseline for high schema coverage without compensating further.

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 purpose: 'Get TV show cast and crew by ID'. It specifies the verb ('Get'), resource ('TV show cast and crew'), and key input ('by ID'), making the function unambiguous. However, it doesn't explicitly differentiate from siblings like 'tv_details' or 'person_tv_credits', which might also provide cast/crew information, so it falls short of a perfect score.

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. It doesn't mention prerequisites (e.g., needing a TMDB ID), exclusions, or comparisons to siblings like 'tv_details' (which might include credits) or 'person_tv_credits' (which focuses on a person's TV roles). This lack of context leaves the agent to infer usage from the name alone.

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 carries full burden. It mentions 'Get' which implies a read-only operation, but doesn't disclose behavioral traits such as rate limits, authentication needs, error handling, or what details are returned (e.g., cast, ratings). For a tool with no annotations, this is a significant gap in 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 a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for a simple tool, making it easy for an agent to parse quickly.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'details' include (e.g., plot, genres, runtime) or the return format, leaving the agent uncertain about the tool's behavior. For a tool with rich sibling context, more completeness is needed.

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 100%, with the parameter 'tv_id' documented as 'TMDB TV show ID'. The description adds no additional meaning beyond the schema, such as format examples or constraints. Baseline 3 is appropriate since the schema does the heavy lifting, but no extra value is added.

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') and resource ('TV show details'), specifying it's by ID. It distinguishes from siblings like 'search_tv' or 'tv_popular' that don't retrieve by ID, though it doesn't explicitly mention these alternatives. The purpose is specific but could be more differentiated.

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 guidance is provided on when to use this tool versus alternatives like 'search_tv' for finding IDs or 'tv_similar' for related content. The description implies usage when you have a TV show ID, but it doesn't state prerequisites or exclusions, leaving the agent to infer 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?

No annotations are provided, so the description carries the full burden. It states 'Get TV shows currently on air', implying a read-only operation, but doesn't disclose any behavioral traits such as rate limits, authentication needs, pagination behavior, or what 'currently on air' means in terms of time window. This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a simple tool and earns its place by clearly stating what the tool does.

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 complexity of a tool that fetches real-time TV data, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'currently on air' entails (e.g., live vs. scheduled), how results are formatted, or any limitations, making it inadequate for an agent to use effectively without additional context.

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 description adds no parameter semantics beyond what the input schema provides. With 100% schema description coverage, the schema already documents the 'page' parameter fully. The description doesn't explain how pagination relates to 'currently on air' shows or any other contextual details, so it meets the baseline but adds no extra value.

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 'Get TV shows currently on air' clearly states the verb ('Get') and resource ('TV shows currently on air'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'tv_airing_today' or 'trending_tv_day', which might have overlapping functionality, so it doesn't reach the highest score.

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. With siblings like 'tv_airing_today', 'trending_tv_day', and 'trending_tv_week', there's no indication of how this tool differs in scope or timing, leaving the agent to guess based on the name alone.

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 carries the full burden of behavioral disclosure. It only states the action ('Get') without details on permissions, rate limits, pagination, or response format. For a tool with no annotations, this is a significant gap in 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 extremely concise at three words, with no wasted language. It's front-loaded and efficiently conveys the core purpose, though this brevity contributes to gaps in other dimensions.

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 complexity of a TV data tool with no annotations, no output schema, and many sibling tools, the description is incomplete. It lacks details on behavior, usage context, and output, making it insufficient for an agent to fully understand how to invoke it effectively.

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 100% description coverage, with the 'page' parameter fully documented. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without compensating value.

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 'Get popular TV shows' states the basic purpose with a verb ('Get') and resource ('popular TV shows'), but it's vague about what 'popular' means (e.g., by what metric or time frame) and doesn't distinguish it from similar sibling tools like 'tv_top_rated' or 'trending_tv_week'. It's adequate but lacks specificity.

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 guidance is provided on when to use this tool versus alternatives. With many sibling tools for TV content (e.g., 'tv_top_rated', 'trending_tv_week'), the description doesn't indicate context, exclusions, or comparisons, leaving the agent to infer usage based on tool names alone.

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 carries full burden. It mentions nothing about behavioral traits: no information on rate limits, authentication needs, pagination behavior (despite a 'page' parameter), what 'similar' means algorithmically, or the response format. This is inadequate for a tool with parameters and no output schema.

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 a single, efficient sentence with zero waste—it directly states the tool's purpose without fluff. It's appropriately sized for a simple lookup tool.

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 no annotations, no output schema, and a parameterized tool, the description is incomplete. It lacks crucial context: what 'similar' entails, pagination details, response structure, or error handling. This leaves significant gaps for an agent to use the tool effectively.

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 100%, with clear parameter descriptions in the schema. The description adds no additional meaning beyond implying 'tv_id' is used to find similar shows and 'page' is for pagination, which is already covered. Baseline 3 is appropriate as the schema does the heavy lifting.

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 verb ('Get') and resource ('similar TV shows'), specifying it operates 'by ID'. It distinguishes from siblings like 'tv_details' (which gets details) and 'tv_popular' (which gets popular shows), but doesn't explicitly contrast with 'movie_similar' (which does the same for movies) or explain why to use this over other recommendation tools.

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 like 'movie_similar' (for movies), 'tv_recommendations' (if available as a sibling, though not listed), or other TV show discovery tools (e.g., 'tv_popular'). It only states what it does, not when it's appropriate.

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 carries the full burden of behavioral disclosure. 'Get' implies a read-only operation, but it doesn't cover rate limits, authentication needs, pagination behavior (hinted by the 'page' parameter but not explained), or what the return format looks like. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence with no wasted words, making it appropriately sized. However, it's under-specified rather than concise—it could benefit from more detail without becoming verbose. It's front-loaded but lacks depth, so it earns a 4 for brevity but not full clarity.

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 complexity of a data-fetching tool with no annotations, no output schema, and multiple siblings, the description is incomplete. It doesn't explain the return values, how 'top rated' is determined, or usage context. For a tool in a rich ecosystem, more information is needed to ensure the agent can use it 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 description coverage is 100%, with the single parameter 'page' documented as 'Page number (1-1000)'. The description adds no additional meaning beyond this, as it doesn't mention pagination or how results are structured. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 'Get top rated TV shows' clearly states the action (get) and resource (top rated TV shows), but it's vague about scope and doesn't differentiate from siblings like 'tv_popular' or 'movie_top_rated'. It specifies the resource type (TV shows vs movies) but lacks detail about what 'top rated' means (e.g., by ratings, votes, or time period).

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 guidance is provided on when to use this tool versus alternatives. With siblings like 'tv_popular', 'tv_airing_today', and 'movie_top_rated', the description doesn't explain when 'top rated' is preferred (e.g., for critically acclaimed shows vs trending ones) or any prerequisites. Usage is implied but not explicitly 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?

With no annotations, the description carries full burden but only states the basic action without disclosing behavioral traits such as rate limits, authentication needs, error handling, or what 'videos' entails (e.g., trailers, clips). It's minimal and lacks critical operational 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 a single, efficient sentence with zero waste, front-loaded with the core action. It's appropriately sized for a simple tool, earning its place without redundancy.

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 no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what 'videos' includes, potential response formats, or any constraints, leaving gaps for a tool that likely returns structured data.

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 100%, with the parameter 'tv_id' documented as 'TMDB TV show ID'. The description adds no additional meaning beyond this, as it only restates 'by ID'. Baseline 3 is appropriate since the schema fully covers the parameter.

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') and resource ('TV show videos'), specifying retrieval by ID. It distinguishes from siblings like 'tv_details' or 'movie_videos' by focusing on videos specifically, though it doesn't explicitly contrast with 'tv_credits' or other video-related tools.

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 guidance is provided on when to use this tool versus alternatives like 'tv_details' (which might include videos) or 'movie_videos' (for movies). The description implies usage when needing videos for a TV show by ID, but lacks explicit context or exclusions.

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