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

With no annotations, the description must disclose behavior. It only mentions filtering capabilities but does not explain pagination, default sorting, genre mode matching, or that watch provider filters require region. It also does not state that this is a read-only operation or what results look like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. It efficiently lists the main filter dimensions, although it is too brief for a tool with this many parameters.

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 tool with 22 parameters, no annotations, and no output schema, this description is severely under-specified. It omits all usage context, return format, and critical behavioral constraints like the default sort or how to combine filters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only gives broad categories (e.g., 'date' could map to releaseDateFrom/To or releaseYear). It does not explain any of the 22 parameters, including nuanced ones like genreMode, keywordMode, castIds vs personIds, or watchProviderIds.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the verb 'Discovers' with the resource 'movies' and lists key filter dimensions (genre, date, rating, runtime, language, provider, sort). This clearly indicates a filtered movie listing tool, though it does not explicitly distinguish it from tmdb_search_movies or tmdb_list_movies.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use discover vs search or list. There are no references to alternatives or exclusions. The description gives no context about prerequisites or typical use cases.

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 says the tool 'discovers' TV series and mentions filter categories, but does not disclose return format, pagination, default sorting behavior, read-only nature, or any rate-limit or authentication considerations. This is insufficient for a tool with 19 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, concise sentence with no redundant words. It is front-loaded with the core action ('Discovers TV series') and lists key filters efficiently. Every word contributes to the meaning, making it appropriately sized for a high-level summary.

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 high complexity (19 parameters, no annotations, no output schema), the description is far from complete. It omits crucial details such as pagination, default values, return shape, how filters combine (e.g., genreMode, keywordMode), and any constraints or edge cases. An agent would need substantial external knowledge to use this tool 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 0%, and the description attempts to compensate by listing filter categories. However, it only covers broad areas like genre, air date, rating, runtime, language, provider, and sort, leaving many parameters (page, region, genreMode, keywordMode, minVoteCount, firstAirDateFrom/To, excludeGenres, watchMonetizationTypes, etc.) unexplained or only vaguely implied. The mapping is incomplete and ambiguous, so the description adds limited semantic value beyond the schema.

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 discovers TV series and lists the filter dimensions (genre, air date, rating, runtime, language, provider, and sort), which conveys a specific verb and resource. It falls short of explicitly differentiating from similar siblings like tmdb_search_tv or tmdb_discover_movies, but the filter list suggests a distinct discovery-oriented purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is given about when to use this tool versus alternatives such as tmdb_search_tv, tmdb_list_tv_series, or tmdb_trending_tv. The filter list implies it is for filtered discovery, but no when-to-use or when-not-to-use context is provided, leaving the agent to infer the appropriate scenario.

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 merely states the action without disclosing any behavioral traits such as return format, potential multiple results, rate limits, or the need to specify an external source. This is a minimal restatement of the tool's purpose.

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 sentence that is direct and front-loaded with the verb and resource types. It contains no fluff and each word adds value.

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?

Overall, the description is too sparse for a tool with no output schema and no annotations. It does not mention necessary details like the externalSource parameter, response structure, or any constraints. While the tool is simple, the lack of parameter context and behavioral caveats leaves meaningful 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 0%, so the description must compensate. It does not explain any of the parameters. While the parameter names and the enum for externalSource are somewhat self-explanatory, the description adds no meaning about what externalId should contain or how language affects the result.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Finds' and clearly enumerates the resource types (movies, TV series, seasons, episodes, or people). This distinguishes it from sibling tools that focus on search or retrieval by TMDB ID, making the purpose unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'from an external ID' clearly indicates the intended use case: when you have an external ID (e.g., IMDb ID) and want to find the corresponding TMDB item. However, it does not explicitly state when not to use it or mention alternatives, so it falls short of a 5.

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 discloses one behavioral trait: films are returned in release order. However, it does not mention what happens if a collection is not found, language default behavior, or auth requirements, leaving significant 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 a single, concise sentence of 12 words that front-loads the verb and resource. Every word serves a purpose, with no fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema or annotations, this terse description is insufficient. It only hints at films in release order, but does not clarify the overall response structure (e.g., collection metadata, languages, or error handling). For a tool with two parameters and no schema descriptions, it is not complete enough for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description adds zero parameter information. It does not mention collectionId or language, and gives no hint about how to specify the collection or what language options exist. The description is entirely unhelpful for understanding the parameters.

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 'Gets' and the resource 'movie franchise or collection', with the additional detail 'with its films in release order'. This distinguishes it from sibling tools like tmdb_search_collections (search) and tmdb_get_movie (single movie).

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 this tool is for retrieving a collection by ID, but it does not explicitly state when to use it versus alternatives like tmdb_search_collections. No exclusions or alternative tool names are mentioned, so usage context is only implied.

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?

There are no annotations, so the description must fully disclose behavior, but it only states that the tool 'gets' ratings. It does not describe the return format, what happens when region is omitted, authentication needs, or any rate-limiting or data-shape specifics.

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 sentence with no filler or redundancy. It is front-loaded with the core action and resource, making it easy to scan.

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 absence of an output schema and annotations, the one-sentence description leaves important gaps: the expected response structure, the behavior when no region is specified, and how the returned ratings are organized. This is under-specified even for a simple retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description partially compensates by clarifying mediaType as 'movie certifications' vs 'TV content ratings' and by indicating that region is optional. However, it does not define the 'id' parameter or explain the region value format beyond the schema pattern.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Gets' and identifies the exact resource ('regional movie certifications or TV content ratings'), making it clear what the tool does. This is distinct from sibling tools like tmdb_get_movie or tmdb_search_movies, which focus on other data.

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, nor are any prerequisites or exclusions mentioned. The phrase 'optionally for one region' hints at a parameter but does not explain when to use the tool or how to choose between movie and TV.

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

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

With no annotations, the description carries the full disclosure burden. It only mentions 'bounded' but does not explain the limit parameter, default behavior, error cases, or response structure. This is a significant gap for a tool with no other behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the core purpose without unnecessary words. It is appropriately sized for a tool with a clear but limited scope.

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 7-parameter tool with no annotations and no output schema, this description is severely under-specified. It does not explain how to request season/episode credits, the effect of creditType, or the response format, making it difficult to use correctly without deeper inspection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain any of the 7 parameters. It vaguely references media types but does not map them to mediaType, id, seasonNumber, episodeNumber, creditType, or limit. The 'bounded' hint is insufficient for parameter understanding.

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 identifies the action ('Gets') and the resource ('cast and crew credits') for movie, TV series, season, or episode. This distinguishes it from sibling tools like tmdb_get_movie or tmdb_get_person_credits, though it does not 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 is provided on when to use this tool over the many sibling tools. It does not mention exclusions or alternatives, leaving the agent to infer usage context 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?

With no annotations, the description carries full burden for behavioral disclosure. It states the tool 'gets' data, which implies a read-only operation, and lists the output categories. However, it does not disclose how the 'region' and 'language' parameters affect the response, nor any potential side effects or error conditions, leaving some ambiguity.

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, well-structured sentence that front-loads the main purpose ('Gets a movie's details') and then succinctly lists complementary output areas. No words are wasted; it effectively conveys the tool's scope 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?

The tool has no output schema and no annotations, so the description must convey what will be returned. It does cover the key facets (details, director, cast, trailer, watch providers), but 'details' is somewhat broad and the impact of input parameters on the output is not explicitly spelled out. Still, the description gives a solid high-level picture.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions 'regional watch providers', indirectly referencing the 'region' parameter, but does not explain the 'language' parameter at all. The meaning of 'movieId' is inferable from the resource name, but the description adds no direct parameter-level detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Gets' and identifies the resource as 'a movie', then enumerates the exact information returned (details, director, top cast, trailer, regional watch providers). This clearly distinguishes it from sibling tools like tmdb_search_movies or tmdb_discover_movies, which serve different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for fetching details about a single, known movie, but does not explicitly state when to choose this over alternatives such as search or discover. It lacks any exclusionary guidance or explicit mention of needing a movieId, relying on the schema for that cue.

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 uses 'Gets' to imply a read-only operation, but it does not mention authentication requirements, rate limits, error behavior, or the format of the 'external identity' response. The agent is left uninformed about potential side effects or prerequisites.

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, focused sentence that directly states the tool's purpose. It lists multiple data fields without unnecessary elaboration, making it highly scannable and efficient. No filler words or redundant content are present.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple get-by-ID tool with no output schema and no annotations, the description lists several key returns, offering partial completeness. However, it omits the role of the 'language' parameter, the representation of 'external identity', and any prerequisites or authentication context. The presence of many sibling tools also leaves the description only vaguely positioned among alternatives.

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 0% description coverage for its two parameters (personId and language). The description does not mention these parameters or explain how they affect the request; it only lists output data. An agent must guess that personId is the identifier and language controls localization, but the description adds no explicit meaning.

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 that the tool gets a person's biography, known department, birthplace, profile, and external identity. This specific verb+resource combination with enumerated fields makes it distinct from sibling tools like tmdb_get_person_credits, which focuses on credit data, and tmdb_search_people, which is for searching rather than retrieving details.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. It simply describes the outputs, leaving the agent to infer usage from the field list without guidance on choosing this over tmdb_get_person_credits or tmdb_search_people.

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?

There are no annotations provided, so the description bears full responsibility for disclosing behavioral traits. It mentions 'bounded' (implying a limit) and 'filtered' (implying creditType/mediaType), but these directly restate schema parameters. It does not disclose output structure, default sorting, language behavior, or what happens with invalid inputs. The agent gains little beyond the 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 concise sentence that front-loads the action ('Gets') and packs relevant filters into a compact phrase. There is no redundant or filler content, making it extremely efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six parameters, no output schema, and no annotations, a robust description is essential. However, this description only covers two parameters conceptually, omits return value structure, default sorting/pagination behavior, and any usage prerequisites. It is too sparse for an agent to fully understand the tool's capabilities and limitations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema_description_coverage is 0%, so the description must compensate. It alludes to mediaType ('movie, TV, or combined') and creditType ('cast or crew'), but provides no explanation for personId, limit, sortBy, or language. The schema has enums and defaults, but the description does not clarify their semantics or interaction (e.g., how sortBy works, default behavior).

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 function: 'Gets a bounded movie, TV, or combined filmography filtered by cast or crew roles.' It uses a specific verb ('gets') and specifies the resource (person credits) and key filters (media type and credit type). This distinguishes it from sibling tools like tmdb_get_person (person details) and tmdb_get_credits (credits for a specific 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 implies when to use the tool (to retrieve a person's filmography) but provides no explicit exclusions or alternatives. For instance, it does not contrast with tmdb_search_people or tmdb_get_credits, leaving the agent to infer the correct context from the name and sibling list. No 'when-not-to-use' guidance is given.

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

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

With no annotations, the description carries the full burden. It discloses that this is a read operation and describes the two behavioral modes, but it does not explain pagination, language handling, response structure, or any potential limitations. It adds some context beyond the schema but leaves significant aspects unspecified.

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, concise sentence with no redundant information. It is front-loaded with the primary action and clearly mentions the default behavior. While it could be slightly more structured with separate clauses, it is efficient and easy to parse.

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 tool with 4 parameters, no output schema, and no annotations, the description is notably incomplete. It does not specify that movieId is required, how pagination works, what the response contains, or how 'similar' differs from 'recommendations' beyond 'genre-and-keyword.' The agent would need to infer many details from the schema or external knowledge.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It implicitly explains the 'kind' parameter by mentioning recommendations vs. similar, but it ignores page, movieId, and language. The parameter names are self-explanatory to some degree, but the description adds little value for the majority of parameters, leaving the agent without additional semantic guidance.

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 it gets recommendations or similar movies, with a specific verb and resource. It distinguishes the two modes (default recommendations vs. similar), though it does not explicitly name sibling tools for alternative purposes. This is clear enough for an agent to understand the tool's core function.

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 by explaining the default behavior (recommendations) and an alternative mode (similar). However, it does not provide explicit guidance on when to choose this tool over siblings like tmdb_search_movies or tmdb_discover_movies, nor does it mention exclusion criteria. This is implied rather than 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 must carry the full behavioral burden. It reveals the default recommendations mode and dissimilarity to similar-series matching, but omits critical details such as authentication requirements, return format, pagination behavior, or the read-only nature of the operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no unnecessary words. It efficiently conveys the core function while leaving room for additional useful detail without becoming verbose.

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 tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks return-value expectations, dependency on seriesId, and comparative context with sibling tools. The only substantive addition is the recommendations/similar split, but significant gaps remain.

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 descriptions cover 0% of parameters, so the description must compensate. It provides minimal semantic value for the 'kind' parameter by distinguishing recommendations from similar-series matches, but fails to clarify seriesId, page, or language meaning beyond basic types and enums.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Gets') and clearly identifies the resource ('TV recommendations' or 'similar-series matches'), immediately distinguishing it from sibling tmdb_get_related_movies. The phrase 'by default' and 'narrower similar-series matches' further pinpoints the tool's purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to use this tool versus alternatives like tmdb_get_related_movies or tmdb_search_tv. The description only hints at internal modes ('by default', 'narrower similar-series matches') but lacks when/when-not context or alternative references.

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 is the only source. It discloses that results are paginated and that the operation is a 'gets' (read) action. However, it does not describe response structure, authentication requirements, or other limitations beyond pagination.

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 concise sentence that front-loads the verb and object. It contains no filler or 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?

The tool has 4 parameters and no output schema, and the description is brief. It covers the core purpose but leaves out details about return fields and the meaning of the language parameter. For a simple retrieval tool, this is minimally sufficient but not rich.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description is essential for parameter understanding. It implicitly explains mediaType (movie/tv) and page (paginated), but the language parameter is not mentioned, and id is only implied. The description adds some semantic context but not complete 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 tool gets paginated user reviews for a movie or TV series. It uses a specific verb and resource, and the scope distinguishes it from sibling tools like tmdb_get_movie or tmdb_get_credits.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for retrieving reviews when you have a media type and ID, but it does not explicitly mention alternatives or conditions for when not to use it. The scope is clear but no comparative guidance is given.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only says 'Gets' which implies a read-only operation, but it does not disclose any other traits such as API key requirements, rate limits, error behavior, or whether the response includes all details or a subset. The description adds minimal behavioral context beyond the name.

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 concise sentence of ten words. It is front-loaded with the action and resource, and every word contributes to the core meaning. There is no fluff or redundant phrasing, making it highly efficient.

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 to fully enable correct invocation. It lists the kinds of data returned but does not explain the required parameters, the API endpoint behavior, or any constraints. For a tool with four parameters and no other documentation, this is insufficient for an agent to use it reliably without assumptions.

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 0% description coverage, and the description does not compensate by explaining any parameters. It does not mention seriesId, seasonNumber, episodeNumber, or language, nor how they relate to the episode. The parameters are left entirely to the schema's bare names, which may not be self-explanatory to all agents.

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 gets an episode's details, directors, guest stars, and trailer, using a specific verb ('Gets') and resource ('episode'). This distinguishes it from sibling tools like tmdb_get_tv_season (season-level) and tmdb_get_tv_series (series-level), which focus on other scopes.

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 prerequisites, exclusions, or explicitly recommend using it for episode-level data. An agent would have to infer the use case solely from the tool name and description, which is insufficient given the many sibling 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, the description carries the full burden of behavioral disclosure. It only states what the tool gets, but does not disclose that it is a read-only operation, whether authentication is required, any rate limits, or what the response structure might be. There is no mention of required inputs or error conditions.

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, front-loaded sentence with no redundant information. It efficiently states the core purpose and includes a key detail ('complete episode list'). It could be considered terse, but it is concise without being vague.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only tool, the description conveys the primary function and output sufficiently. However, given the lack of annotations and output schema, the description does not fully compensate for missing usage guidance, parameter semantics, or behavioral expectations. It is minimally acceptable but with clear 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 0%, and the description adds no information about the parameters (seriesId, seasonNumber, language) beyond what the schema already provides. It does not clarify semantics such as 0-based season numbering or the optional language format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Gets') and identifies the resource ('TV season') along with a distinctive scope ('complete episode list'). It clearly differentiates from sibling tools like tmdb_get_tv_episode (single episode) and tmdb_get_tv_series (series-level data).

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 that this tool is appropriate for fetching a full season with episodes, or that tmdb_get_tv_episode should be used for a single episode. No exclusions or contextual triggers are given.

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. It does reveal behavioral details beyond the title: it returns not just 'details' but also creators, top cast, trailer, and regional watch providers. This indicates the tool aggregates multiple data types. However, it does not mention authentication, rate limits, or any side effects, though 'Gets' implies a safe read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 12 words, front-loaded with the verb and resource. Every word adds specific information, with no filler or repetition. It is appropriately concise for the tool's scope.

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 output schema, the description partially compensates by listing what is returned (creators, cast, trailer, watch providers). However, it does not explain the required seriesId or language parameter, nor does it clarify that this tool is the primary aggregate series endpoint. It is sufficient for a basic understanding but leaves gaps for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description is the only source of parameter meaning. It only hints that 'regional watch providers' means the region parameter influences that part, but it does not explain seriesId, language, or the format/valid values. The description adds minimal value beyond the bare schema properties.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Gets' and names the resource ('series details') plus concrete sub-items (creators, top cast, trailer, regional watch providers). This is clearer than the title alone and distinguishes it from more granular sibling tools like tmdb_get_tv_season or tmdb_get_credits, though it does not 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?

There is no guidance on when to use this tool versus alternatives like tmdb_search_tv, tmdb_get_tv_season, or tmdb_get_credits. The description implies one should use it to retrieve the listed data, but it does not provide any exclusionary or comparative context.

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

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It accurately indicates a read-only operation ('Lists') but does not mention the effect of the optional 'language' parameter on the output, such as localized genre names. The description is truthful but minimal, lacking deeper behavioral context like potential response format or localization 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, front-loaded sentence that wastes no words. It communicates the essential purpose effectively. For such a simple tool, this level of conciseness is ideal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (one optional parameter, no output schema), and the description clarifies the core function. However, the omission of the 'language' parameter leaves a gap in understanding how output may vary, and the lack of any alternative guidance makes it less complete than it could be. It is adequate but not comprehensive.

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 describes one optional 'language' parameter with a regex pattern but no description. The tool description does not mention this parameter at all, leaving 0% schema description coverage uncompensated. Since the description adds no meaning beyond the schema, it fails to help the agent understand how to use 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 uses the specific verb 'Lists' and identifies the resource as 'movie genre names and IDs,' which clearly states what the tool does. It also distinguishes from sibling tools like tmdb_list_tv_genres by specifying 'movie.' The phrase 'for discovery filters' adds context about its role.

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 through 'for discovery filters,' suggesting this tool is intended to support discovery filtering. However, it does not explicitly state when to use this tool over alternatives (e.g., tmdb_list_tv_genres) or provide any exclusions. The usage guidance is implicit rather than explicit.

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 for behavioral disclosure. It mentions no behavior beyond listing categories, omitting important details such as pagination behavior, language/region defaults, or response structure. For a tool that likely has default sorting and paging, this is a significant gap.

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 short sentence with no filler, making it technically concise. However, it is so minimal that it borders on under-specification rather than intentional brevity, and it does not front-load key usage constraints.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With four parameters, no output schema, and no annotations, the description is far too sparse. It does not explain what the response contains, how pagination works, the effect of region/language, or the difference from similar list tools. This is insufficient for an agent to confidently select and invoke the tool 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 0%, so the description must compensate. However, it only repeats the category enum values and provides no extra meaning for page, region, or language. The behavior of these parameters is left entirely to the reader's inference, failing to add value beyond the schema's type/default definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it lists movies by category ('popular, top-rated, now-playing, or upcoming'), which specifies a concrete action and resource. It implicitly distinguishes from search/get tools by listing, but it does not explicitly contrast with sibling tools like discover or trending, so it misses some differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as discover, trending, or search. The description only states what it does, not in which scenarios it is the preferred choice.

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 the core behavior (listing TV genre names and IDs) but omits the behavior of the 'language' parameter, such as whether it localizes genre names or is optional. It also doesn't disclose any response format details beyond 'names and IDs'. This leaves meaningful gaps for a simple but parameterized tool.

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 sentence of 10 words, front-loaded with the action and resource. It is extremely concise with no wasted words, and every word contributes to the meaning. This is an example of appropriately sized brevity.

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 low complexity (one optional parameter, no output schema), the description provides a baseline level of completeness by stating what the tool returns. However, it is incomplete because it does not describe the language parameter's behavior or differentiate from the sibling tool for movie genres. It is a minimum viable description with clear 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 0%, and the description does not mention the 'language' parameter at all. The parameter appears only in the schema with a pattern, but the description provides no explanation of its purpose or effect. Since the description adds zero value for parameter understanding, this scores low.

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 'Lists' and the specific resource 'TV genre names and IDs', and it distinguishes itself from siblings like tmdb_list_movie_genres by explicitly saying 'TV'. The phrase 'for discovery filters' adds useful context about its intended use.

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 a use case with 'for discovery filters', but it does not explicitly state when to use this tool versus alternatives like tmdb_list_movie_genres or mention any exclusions. There is no 'instead' or 'use when' guidance, so usage is only implied.

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 says 'lists' without mentioning pagination, language parameters, response format, or any side effects. This is insufficient for an agent to understand the full behavior of the tool.

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 concise sentence that front-loads the verb and resource. It contains no filler or redundant information, earning a top score for conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, but with no output schema and no annotations, the description should provide more context. It omits usage guidance, parameter details, and behavioral notes, leaving the agent under-informed about pagination and language handling.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions the category values, but these are already present in the schema's enum. It does not explain the 'page' or 'language' parameters, leaving them undocumented even though they affect the result.

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 (lists) and the resource (TV series), and specifies the exact categories (airing-today, on-the-air, popular, top-rated). This is specific enough to distinguish from sibling tools like tmdb_search_tv or tmdb_get_tv_series.

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 the tool is used when you need a curated list of TV series by category, but it provides no explicit guidance on when to prefer it over alternatives like tmdb_trending_tv or tmdb_discover_tv. It lacks any exclusion criteria or alternative recommendations.

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 responsibility for behavioral disclosure. It states the tool lists names and IDs, which is clear for a simple read-only listing, but it omits details about how parameters affect results or any authentication/rate-limit considerations. The purpose is conveyed but not enriched beyond the basic operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that names the action, resource, and purpose with zero wasted words. It is appropriately concise for a straightforward listing 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?

For a simple listing tool with no output schema, the description adequately covers what is returned (names and IDs) and the general context. The main gap is the lack of parameter usage details, but the schema patterns provide some constraints. Overall, it is mostly complete given the tool's simplicity.

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 0% description coverage for its two parameters, and the tool description does not explain how 'region' or 'language' are used. Only the word 'regional' hints at region filtering, but language is entirely unaddressed. This falls short of compensating for the low 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 uses the specific verb 'Lists' and names the resource ('regional TV streaming-provider names and IDs') plus the intended purpose ('for discovery filters'). It clearly distinguishes this from sibling tmdb_list_watch_providers by explicitly including 'TV'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for discovery filters' gives a use context, but it does not explicitly state when to use this tool over alternatives or name any exclusions. The distinction from the sibling 'tmdb_list_watch_providers' is implied rather than stated.

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

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

With no annotations, the description carries the full burden. It conveys a read-only list operation via 'Lists' and adds regional scope, but does not disclose parameter optionality, return format details, or any potential edge cases. It is adequate for a simple list tool but lacks depth.

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 ten-word sentence with no filler. Every word serves a purpose: the verb, scope, resource, and usage context are all present 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?

For a simple listing tool with no output schema, the description adequately conveys the result contents (names and IDs) and the regional aspect. However, it omits details about how parameters affect results and the structure of the returned list, leaving minor 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?

The schema has 0% description coverage, so the description must compensate. It only hints at the 'region' parameter through 'regional' and ignores the 'language' parameter entirely. No mention of which parameters are optional or their expected formats leaves the agent under-informed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Lists') and resource ('regional movie streaming-provider names and IDs'), clearly distinguishing from the sibling 'tmdb_list_tv_watch_providers' by specifying 'movie'. It also adds the intended use case ('for discovery filters'), making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for discovery filters' implies a use case, but the description does not explicitly state when to use this tool over alternatives (e.g., the TV counterpart) or provide any exclusions. It only gives a contextual hint, not clear guidance.

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 mentions 'searches' and gives no detail about pagination, language handling, rate limits, or output structure. This leaves significant ambiguity about what the tool actually does when invoked.

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, front-loaded sentence with no filler, earning its place. However, the extreme brevity sacrifices explanatory value, making it concise but not optimally informative. It could be improved slightly without losing conciseness.

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 there is no output schema and three parameters, the description omits critical context such as pagination behavior, language semantics, and what the results are used for (e.g., linking to tmdb_get_collection). An agent would need to guess or rely on external knowledge to use this tool correctly, so it is not contextually complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for parameter documentation. It only clarifies the 'query' parameter as searching 'by name', while 'page' and 'language' are completely unexplained. This partial coverage is insufficient for a 3-parameter tool.

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 (searches), resource (movie franchises/collections), and method (by name). It effectively differentiates this tool from sibling search tools like tmdb_search_movies, tmdb_search_tv, and tmdb_search_people by targeting collections/franchises specifically.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for finding collections/franchises by name but provides no explicit alternatives, exclusions, or when-to-use guidance. It relies on the resource name to convey context, which is sufficient for a basic understanding but not comprehensive.

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 mentions 'searches' which implies a read operation, but does not disclose pagination behavior, return format, or any side effects. The description adds minimal behavioral context beyond the tool's name and title.

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, concise sentence that efficiently conveys the core purpose. There is no redundant filler or repetition of structured data, making it appropriately sized for a simple search 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?

The tool is simple with only two parameters and no output schema. The description provides enough context to understand the tool's purpose and intended use in discovery workflows, but lacks details on return structure and pagination. Given the simplicity, a moderate score is appropriate; it is not fully complete but not severely deficient.

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 provides no information about the query or page parameters. Schema description coverage is 0%, so the description must compensate for the schema's minimal annotations. It does not explain what 'query' means or how to use 'page', leaving the agent without guidance beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: it searches for keyword IDs intended for movie and TV discovery. This is a specific verb+resource pattern that distinguishes it from sibling search tools like tmdb_search_movies or tmdb_search_people, which search for different entity types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide any guidance on when to use this tool versus alternatives, such as tmdb_search_movies or tmdb_discover_movies. It only states what it does, leaving the agent to infer usage context without explicit when-to-use or exclusion 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?

No annotations are provided, so the description carries the full burden. It adds one behavioral detail—that matching occurs across multiple title types—but does not disclose whether the operation is read-only, how results are paginated, or any other side effects. This is insufficient for a safe and predictable usage.

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, focused sentence that is front-loaded and contains no filler. It effectively communicates the core purpose without any waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 6 parameters, no annotations, and no output schema. The description is too brief to cover essential context such as the response format, pagination behavior, or how the optional filters (year, region, language) affect results. It is incomplete for a tool with this complexity.

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 zero descriptions for all 6 parameters. The description only clarifies the 'query' parameter by specifying it matches original, translated, and alternative titles. It provides no meaning for 'page', 'year', 'region', 'language', or 'includeAdult'.

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 ('searches'), the resource ('movies'), and the specific scope ('by original, translated, and alternative titles'). This distinguishes it from sibling tools like tmdb_search_tv or tmdb_search_collections.

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 when to use the tool (when searching for movies by title) but does not explicitly mention alternatives or exclusions. There is no guidance on when to use tmdb_discover_movies versus this search tool.

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 and scope without revealing pagination behavior, language/adult filtering defaults, rate limits, or that it is a read-only operation. The description is too minimal to adequately disclose 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 sentence and is structurally clean, but it is under-specified for the tool's complexity. It does not provide enough information to be considered 'appropriately sized'—it sacrifices necessary detail for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has four parameters, no output schema, no annotations, and a minimal one-line description. It lacks context about return values, parameter usage, pagination, or any operational behavior, making it severely incomplete for an agent to invoke 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 0%, and the description does not explain any of the four parameters (query, page, language, includeAdult). With no parameter documentation in either the schema or the description, the agent cannot infer parameter semantics beyond names/types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Searches') and clearly identifies the resource scope ('movies, TV series, and people in one request'). This distinguishes it from sibling tools like tmdb_search_movies, tmdb_search_tv, and tmdb_search_people by emphasizing the combined multi-type search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'in one request' implies the tool is used when searching across multiple content types simultaneously, but it does not explicitly state when to prefer this over individual searches or mention any exclusions. No alternatives are named, so usage context is present but not fully elaborated.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only mentions that search is performed 'by name,' but omits details such as pagination behavior, language support, adult content filtering, or return format. This is insufficient for a search tool without additional 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 concise sentence, front-loaded with the main action. It is not verbose, but it is perhaps too terse, omitting useful context that could be added without becoming unwieldy. Still, it earns its place with no fluff.

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 has 4 parameters, no annotations, no output schema, and 0% schema description coverage, the description is far from complete. It does not cover pagination, language rules, adult content, or return behavior. A search tool with this level of ambiguity would leave an agent uncertain about 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 schema has 4 parameters and 0% description coverage. The description implies the 'query' parameter through 'by name,' but the other parameters (page, language, includeAdult) are not explained. The description adds minimal meaning beyond the schema's property names and insufficiently compensates for the lack of schema 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 tool searches people by name and enumerates the types of people (actors, directors, writers, crew). This is a specific verb+resource combination that is easy to understand, though it does not explicitly differentiate from sibling tools like tmdb_search_multi or tmdb_get_person.

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. There is no mention of prerequisites, exclusions, or direction to other tools like tmdb_get_person for fetching details after a search. The description only states what it does, not when to use it.

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

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

With no annotations, the description carries the burden for behavioral disclosure. It adds useful detail about searching original, translated, and alternative names, but does not disclose behavior related to pagination, language handling, or response structure. This is limited but not misleading.

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?

A single, front-loaded sentence: 'Searches TV series by original, translated, and alternative names.' Every word is useful, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 5 parameters, no output schema, and no annotation coverage. The description only addresses the query concept and resource type, omitting optional parameters, return format, and any caveats. For a search tool of this complexity, the description is under-specified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It clarifies that the query parameter searches by original, translated, and alternative names, which adds meaning beyond the schema's bare type definition. However, it does not describe page, language, firstAirYear, or includeAdult parameters, leaving significant 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?

Clearly states it searches TV series by original, translated, and alternative names, specifying both the resource (TV series) and the scope (name fields). This distinguishes it from sibling search tools like tmdb_search_movies and tmdb_search_multi.

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 this tool is for searching TV series by name, but it does not explicitly state when to use it over alternatives like tmdb_search_multi, nor does it mention exclusions or prerequisite conditions. Usage context is implicit rather than explicit.

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

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

With no annotations, the description carries the full burden for behavioral transparency. It indicates a read-only list operation and the day/week window, but it does not disclose response format, pagination, language default behavior, or any rate-limit/authentication details. This is minimal 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 concise sentence that gets straight to the point. It contains no filler, but it is arguably too terse given the missing parameter semantics and behavioral details.

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?

There is no output schema and no annotations, so the description needs to explain return values and usage context more fully. It only covers the trending time window, leaving language parameter effects, response structure, and other important behavioral details unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no descriptions for its 0% coverage, so the description must compensate. It adds 'day or week' for the timeWindow parameter, but this repeats the schema enum. The language parameter is entirely undocumented in both the schema and the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Lists') and a clear resource ('movies trending over the current day or week'). It distinguishes this tool from the sibling tmdb_trending_tv by specifying 'movies', and from search/discover tools by focusing on trending data.

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 this tool should be used when the agent needs currently trending movies, but it does not explicitly state when to use it versus search, discover, or list alternatives. No exclusions or alternative recommendations are 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 behavioral burden. It discloses that the tool lists trending TV series over a day or week, but it does not explain response format, pagination, or how the language parameter affects results. This is minimal but honest.

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, direct sentence that conveys the core functionality without unnecessary words. It is appropriately concise and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema and minimal description, the tool does not convey return structure or filter behavior fully. However, for a simple trending list tool with two optional parameters, the essential purpose is covered, though it could benefit from specifying typical response fields.

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 0% description coverage for parameters. The description mentions 'day or week' which aligns with the timeWindow enum, but it does not explain the language parameter or its behavior. Thus, it adds little meaning beyond what the schema already exposes.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Lists TV series trending over the current day or week.' It specifies the verb (lists), resource (TV series), and scope (trending), which distinguishes it from the sibling tool tmdb_trending_movies.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this tool is for retrieving trending TV series, but it does not explicitly mention alternatives or when not to use it. No exclusions or alternative tool references are provided, so the usage context is only implied.

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