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

No annotations are provided, so the description must fully disclose behavioral traits. It only states that the tool 'Returns badge details', without mentioning authentication requirements, rate limits, potential errors, or behavior when multiple IDs are passed. The comma-separated ID hint is parameter semantics, not behavioral transparency.

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

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

The description is concise and front-loaded with the API call and operation list. The structure is clear, but the opening sentence 'Call the BetaSeries "badges" API' is somewhat redundant given the tool name, and the 'Pick an operation' phrasing could be more direct. Overall, it avoids unnecessary detail while providing needed operation info.

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 cover more context like return format, error cases, or typical use cases. It does explain the only available operation's parameters, but for a tool with a single operation, it leaves gaps in behavioral expectations and does not fully compensate for the absent structured metadata.

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's 'params' field is a generic object with no specific parameter names, so the description is essential for defining 'id' and 'userId' including optionality (via '?') and the comma-separated multi-value behavior. This adds meaningful value beyond the schema, though it lacks type validation or format details for the user ID.

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 tool as an API wrapper for BetaSeries badges and lists the specific operation 'get-badges-badge' with its function ('Returns badge details'). This distinguishes it from sibling tools that target other BetaSeries resources (persons, movies, etc.), though the verb 'Call' is generic and the description could be more explicit about the tool's overall 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?

The description provides no guidance on when to use this tool versus other BetaSeries tools or alternative operations. It simply instructs the user to 'Pick an operation', but does not explain scenarios where badge details are needed or why this tool should be chosen over siblings like betaseries_episodes or betaseries_shows.

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?

The description discloses important behavioral traits such as premium feature requirements, optional vs. mandatory parameters, and value constraints (e.g., possible values for 'private'). However, it omits authentication requirements, rate limits, and response formats, leaving some behavioral aspects undisclosed.

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 lengthy but well-organized as a list of operations, each with a clear format. It avoids redundancy and front-loads the core purpose. A table could improve scannability, but the structure is effective.

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?

All eight operations and their parameters are documented, including premium flags and defaults, which is strong for operation selection. However, the lack of return value descriptions and authentication context leaves gaps, particularly with no output schema and a multi-operation surface.

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's generic 'params' object defers to the description for actual parameter names. The description thoroughly documents every operation's parameters, including optional markers, mandatory conditions, and the exact JSON structure for 'items'. This goes far beyond what the schema provides.

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 'Call the BetaSeries collections API' and lists eight specific operations with HTTP verbs, making the tool's purpose unambiguous and distinct from sibling tools focusing on other resources.

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

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

Usage is implied by the tool's name and the presence of collection-specific operations, but there is no explicit guidance on when to choose this tool over alternatives or any exclusions. The description does not mention sibling tools or alternative approaches.

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

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

No annotations are provided, so the description must convey behavior. It includes HTTP methods (GET/POST/DELETE) and verbs in operation names (retrieve, delete, add), which indicate side effects. However, it lacks details on authentication, rate limits, irreversibility of deletions, or error conditions. No contradiction with annotations exists.

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 opens with a concise instruction and then presents a logically grouped list of operations. Each line is necessary and follows a consistent format (operation name, HTTP method, path, params). The length is justified by the multi-operation nature, though plain-text formatting could be enhanced with bullet points for readability.

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 11 operations, no annotations, and no output schema, the description covers all operations and parameters comprehensively. It omits return value descriptions and error handling, but the information provided is sufficient for an agent to select and invoke operations correctly. More detail on auth and response formats would improve completeness.

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 is the definitive source for per-operation parameters, listing each parameter name, optionality (marked with '?'), and a brief semantic explanation (e.g., 'nbpp' = Number of comments per page). This adds significant meaning beyond the generic input schema, which only defines a params object. It falls short of 5 due to missing explicit value types/formats for some 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 tool calls the BetaSeries comments API and enumerates all 11 operations with their HTTP methods and paths. This leaves no doubt about the tool's purpose and distinguishes it from sibling tools (e.g., betaseries_movies, betaseries_members) by resource domain.

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 says 'Pick an operation' and provides operation names, but it does not explain when to use this tool versus sibling tools nor offer criteria for choosing among the 11 operations. Usage is implied from operation names (e.g., 'delete-comments-comment') but not explicitly guided.

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 carries the behavioral disclosure burden. It does provide a concise behavioral summary for each operation (e.g., 'Remove a rating', 'Mark an episode as watched'), which is useful. However, it omits deeper context like authentication requirements, idempotency, potential side effects, or rate limits.

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 long (17 operations) but each line is informative and structured consistently (operation, HTTP method, one-line purpose, params). It front-loads the core instruction. No fluff, though the sheer volume could be overwhelming; better formatting (e.g., code blocks) would slightly improve scannability.

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 an output schema and the broad scope, the description thoroughly covers what each operation does and its parameters. It does not describe return formats or pagination details beyond parameter defaults, but for a meta-tool with many operations, it is reasonably 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?

The input schema is minimal (only operation and generic params object), but the description compensates fully by listing every parameter for each operation, including whether it's optional, format hints (e.g., Y-m-d H:i:s), and relationships between parameters (e.g., 'Optional if thetvdb_id provided'). This is far beyond the schema's 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 it calls the BetaSeries 'episodes' API and lists all available operations with their HTTP methods. It distinguishes itself from sibling tools by focusing specifically on episodes-related actions (e.g., watched, hidden, notes, rewatch).

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 alternative sibling tools (e.g., betaseries_shows, betaseries_seasons). It does not state explicit conditions, prerequisites, or exclusions; it merely lists operations without advising which operation fits a given 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?

With no annotations, the description carries the burden of behavioral disclosure. It provides HTTP methods (GET vs POST/DELETE) that imply side-effect profiles, and it gives specific behavior for get-friends-list (defaults, optional id, blocked/summary flags). However, it omits auth requirements, rate limits, error handling, and response structure, so transparency is moderate.

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 well-structured with a clear introductory instruction followed by a line-per-operation list. It is somewhat lengthy due to repeated 'Params:' phrasing, but every included detail serves a purpose and adds practical information. It could be more compact, but is not wasteful.

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 multi-operation tool with no output schema and no annotations, the description covers all operations and parameters but lacks return value details and error behavior. The complexity is high (6 operations), and while the parameter information is thorough, an agent cannot fully anticipate what the API will return or what errors may occur, leaving a notable completeness gap.

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 only defines params as a generic object of string key-value pairs, making the description the sole source of parameter meaning. Each operation lists parameter names, optionality, and semantic purpose (e.g., 'id? (Member ID to unblock)'), adding essential context beyond the schema. This is excellent 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 identifies this as the BetaSeries 'friends' API and enumerates all supported operations (delete, get, post) with specific resources and actions. It distinguishes itself from sibling tools by focusing exclusively on friends-related endpoints, leaving no ambiguity about what the tool does.

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 friend management operations but does not explicitly state when to use this tool versus alternatives. There is no mention of exclusions or conditions where another BetaSeries tool might be more appropriate, though the 'friends' naming provides some contextual 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, the description carries the full burden of behavioral disclosure. It gives one-line summaries like 'Deletes user avatar' or 'Initiates account deletion process' but does not warn about irreversible actions, authentication requirements, token invalidation, or side effects. The mutating POST/DELETE operations are not flagged as potentially destructive.

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 long due to 24 operations, but it is well-structured: a brief instruction, then a clear bullet-like list grouping operations by HTTP method. Each operation line is concise. It could be trimmed by removing redundant phrases like 'Displays' vs 'Returns', but overall it is appropriately sized for the tool's complexity.

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 or annotations, the description should cover the full operational context. It covers operation names and parameters thoroughly, but omits return value shapes, error conditions, authentication prerequisites, and rate limits. For a tool with potentially destructive actions, this incompleteness is a notable gap.

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 only defines an operation enum and a generic 'params' object, so the description is the sole source of parameter-level semantics. It lists each operation's parameter names with meaningful descriptions (e.g., 'login? (Username, minimum 2 characters. You can use % as a wildcard.)'), fully compensating for the schema's lack of 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 clearly states 'Call the BetaSeries members API' and enumerates 24 specific operations with HTTP verbs, resources, and brief action statements. This provides a specific verb+resource pairing that distinguishes it from sibling tools like betaseries_persons or betaseries_shows.

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 implicitly covers usage by listing every operation and its parameters, but it never explicitly states when to prefer this tool over siblings or when not to use it. For example, there is no mention of avoiding destructive operations unless the user has appropriate permissions. Users must infer from the name and operation list that this tool is for member-related actions.

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 discloses HTTP methods (GET/POST/DELETE), endpoint paths, and a notable side effect: deleting the first message in a discussion deletes the entire discussion. It also marks parameters as mandatory/optional, providing beyond-schema 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 front-loaded with the tool's purpose, then uses a clean bullet list for each operation. Every line provides essential information—HTTP method, endpoint, and parameters—with no redundant or filler text. The structure makes scanning for the right operation 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 tool's complexity (five operations with distinct parameter sets) and the absence of both annotations and an output schema, the description thoroughly covers all invocation details. It omits return value format, but the lack of an output schema makes this a minor gap overall; the core usage information is 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?

The input schema only has a generic 'params' object with string values and defers to the description for per-operation parameter names. The description compensates by detailing each operation's parameters, their purpose (e.g., 'to: ID of the recipient member (mandatory if first message)'), and optionality, giving full meaning 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 it calls the BetaSeries 'messages' API and enumerates five distinct operations with HTTP verbs and endpoints (e.g., 'delete-messages-message [DELETE /messages/message]'). This distinguishes it from sibling tools like betaseries_shows or betaseries_friends, which focus on other domains.

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 instructs the user to pick an operation and pass parameters in the 'params' object, and it lists the specific parameters per operation. While it does not explicitly contrast with sibling tools or state when not to use this tool, the domain-specific operation list makes the usage context clear.

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 of behavioral disclosure. It does describe each operation's effect (remove, add, retrieve) and some parameter-specific behaviors (defaults, limits, conditional requirements). However, it omits broader behavioral context such as authentication requirements, rate limits, idempotency of mutations, or error handling, 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 long, but the content is dense and structured as a bulleted list of operations with consistent formatting. Given the tool covers 21 operations, the length is justified and each line adds necessary detail. It is front-loaded with the API call instruction and organized for easy scanning.

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

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

The description covers all operations and their parameters comprehensively, but lacks overarching context such as authentication, rate limits, response format, or pagination behavior beyond parameter defaults. Without an output schema, the description does not clarify what the API returns, leaving the agent partially informed.

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 only defines a generic 'params' object, so the description is the sole source of parameter meaning. It provides exhaustive per-operation parameter names, optional markers, defaults, maximums, and format hints (e.g., 'Y-m-d H:i:s'), fully compensating for the schema's generic nature.

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 explicitly states 'Call the BetaSeries movies API' and enumerates 21 specific operations with clear verbs (delete, get, post) and resources (favorite, movie, note, etc.). It clearly distinguishes this tool from siblings by focusing exclusively on movie-related endpoints.

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 a catalog of operations but gives no guidance on when to prefer this tool over sibling tools like betaseries_shows or betaseries_seasons. It does not mention any alternatives, exclusions, or conditions for choosing this tool over others.

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 states the operation displays latest news, implying a read-only action, but it does not disclose return format, pagination, authentication requirements, or potential side effects. This is acceptable for a simple GET request 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 compact and well-structured, with a clear call to action and a single operation listed with its parameters. Every sentence contributes to understanding, with no redundant or filler content.

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 simplicity of the tool (one operation, two parameters) and no output schema, the description covers the essentials. However, it omits details about the response structure, possible error conditions, and any required authentication. It is minimally sufficient 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 description adds significant semantic value beyond the generic params object schema by detailing each parameter (number, tailored) with their meaning and defaults. The schema only defines a generic string-keyed object, so the description is essential for correct usage.

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 tool as the BetaSeries news API and specifies the exact operation (get-news-last) with its endpoint (GET /news/last), making the purpose unambiguous. It distinguishes itself from sibling tools by focusing on news functionality.

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 basic usage instructions ('Pick an operation and pass its parameters') but does not explain when to prefer this tool over alternatives like timeline or search, nor when not to use it. No exclusion criteria or alternative 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 burden. It discloses the HTTP methods (GET) and optional parameter defaults (with_user default 0), implying read-only behavior. However, it does not mention authentication, rate limits, or response format, leaving some transparency 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 well-structured with a clear lead sentence and a bulleted operation list. It is not overly verbose, but the operation list repeats some information that could be seen as slightly redundant with the schema's enum values.

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

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

The description covers all operations and parameter details, which is sufficient for basic invocation. However, with no output schema, it does not describe the response structure or error behavior, and it omits any authentication or rate-limit notes. For a simple read-only API this is acceptable but not 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?

The schema only provides a generic params object, so the description is essential. It explicitly lists each operation's parameters, marks optional ones with '?', and explains their meaning (e.g., 'with_user? Adds the connected user progression...'). This adds significant 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 it calls the BetaSeries persons API and lists specific operations with verbs like 'Display news articles' and 'Display details of the actor.' It distinguishes from siblings by resource name, but does not explicitly compare to alternative 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 tells the agent to pick an operation and pass params, implying it should be used for persons-related data, but it provides no explicit exclusions or named alternatives. Sibling tools are implicitly differentiated by resource only.

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 the endpoint paths (e.g., GET /pictures/badges) and notes optionality/defaults, but does not mention authentication requirements, response format (binary image vs. URL), error behavior, or rate limits. For a read-only image-fetching tool, the key behaviors are covered sufficiently, but not richly.

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 well-structured: a brief opening sentence, then each operation on its own line with endpoint and params. Every line conveys necessary information and there is no redundant or filler text. It is long but appropriately sized for a tool with nine distinct operations.

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 and a generic input schema, the description must provide complete context, and it does. It documents all 9 operations, their endpoints, each parameter, optionality, and defaults. An agent can invoke any operation correctly without additional external knowledge, making this description fully complete for the tool's 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 only defines a generic 'params' object with string values, so the description is the sole source of parameter meaning. It lists every parameter for each operation, indicates optionality with '?', provides defaults (e.g., width=250, height=375 for characters), and special options like 'placeholder' and 'picked'. This fully compensates for the generic 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 this tool calls the BetaSeries 'pictures' API, with each operation explicitly listing what image it returns (badge, character, episode, etc.). The verbs 'Return' and 'Get' are specific, and the resource types distinguish this tool from siblings like betaseries_movies or betaseries_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?

The description provides clear operational guidance: 'Pick an operation and pass its parameters in the params object.' It enumerates all available operations and their parameters, which tells the agent exactly what to do. It doesn't explicitly state when not to use this tool or name alternatives, but the operation names and resource types make it unambiguous which tool to select.

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 of transparency. It discloses the read-only nature via 'Display' for each operation and includes the HTTP method GET, which signals non-mutating behavior. However, it omits authentication requirements, potential errors, or pagination details, leaving 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 well-structured with a clear introductory line followed by a bulleted list of operations. Each operation is concisely summarized with endpoint, purpose, and parameters, ensuring every sentence carries useful information without unnecessary verbosity.

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 the multi-operation complexity, the description provides substantial context: endpoints, parameter details, and operation purposes. It stops short of covering authentication, response formats, or error handling, which would be valuable for a complete contextual 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?

The schema only provides a generic 'params' object with no property definitions, so the description is the sole source of parameter meaning. It lists each operation's parameters with names, types, defaults, and explanatory descriptions, fully compensating for the schema's opacity.

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 explicitly states it calls the BetaSeries 'planning' API and lists three specific operations with their endpoints and purposes. This clearly identifies the resource and distinguishes it from sibling tools that handle different domains (e.g., persons, badges, shows).

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 instructs 'Pick an operation' and details each operation's functionality, giving clear context on when to use each. However, it does not explicitly discuss when to choose this tool over siblings, though the unique resource name implies its niche.

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 of disclosing side effects. It does convey that delete and post operations mutate user subscriptions while get operations are read-only. However, it does not state required authentication, whether parameters like 'id' are mandatory (the '?' suggests optionality but is ambiguous), or error behavior. Thus, some important behavioral context is missing.

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 well-structured with a brief introductory line followed by a concise bulleted list of operations. Each line packs the operation name, endpoint, action, and parameters into a scannable format without unnecessary verbosity. Every sentence serves a purpose.

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 operations and a minimal schema, and the description covers all operations and their parameters comprehensively. It does not explain return values or error handling, but no output schema exists, and the description gives enough information to understand each operation's behavior. The ambiguity about required parameters slightly reduces completeness.

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 only defines 'operation' and a generic 'params' object that points to the tool description for specifics. The description compensates by naming and explaining each parameter for every operation (e.g., country, id, type). This adds meaningful value beyond the schema, though it does not specify data types or explicit requiredness.

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 tool as accessing the BetaSeries 'platforms' API and enumerates four specific operations with explicit HTTP methods, endpoints, and purposes. This makes the tool's scope unambiguous and differentiates it from sibling tools that target other BetaSeries resources like shows, episodes, or members.

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 each operation should be used by listing their actions (add, remove, display) but does not explicitly state when to prefer this tool over alternatives or when not to use it. There are no exclusions or alternative tool references, so guidance remains implicit rather than direct.

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 reveals HTTP methods (GET/POST), implying read vs write, but does not disclose side effects, authentication requirements, rate limits, or why two operations appear to have identical descriptions ('get-polls-last' and 'get-polls-target' both state 'Display the latest active poll'). This ambiguity is a transparency 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 well-organized as a bulleted list, with each operation on a separate line and front-loaded with the core instruction. It avoids unnecessary prose, though the duplicated description for 'get-polls-last' and 'get-polls-target' is redundant and could be terser.

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

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

The description covers all operation names, endpoints, and parameters, which is essential given five operations and no output schema. However, it does not describe return values (only vague 'Display ...' statements), error handling, authentication needs, or pagination behavior, leaving notable gaps for an agent to invoke the tool correctly in varied contexts.

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's 'params' object is generic (string key/value pairs), so the description provides all necessary parameter semantics per operation, including optionality markers ('?'), default values ('nbpp? Number of results per page, default 10'), and acceptable values (e.g., 'type? Target type (episode or show)'). This fully compensates for the schema's lack of specificity.

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 calls the BetaSeries 'polls' API and lists five specific operations with HTTP methods and paths (e.g., 'get-polls-last [GET /polls/last]'), making the tool's purpose unmistakable and distinguishing it from sibling tools focused on other resources.

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

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

It instructs the agent to 'Pick an operation and pass its parameters in the params object' and lists each operation with its parameters, but it does not provide guidance on when to choose one operation over another (e.g., 'get-polls-last' vs 'get-polls-target' both say 'Display the latest active poll') or mention prerequisites like authentication for write 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'connected user' for some operations but does not explain authentication requirements, rate limits, error handling, or potential side effects of POST operations. The GET vs POST methods are shown, but the consequences and prerequisites are only minimally implied.

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 appropriately structured as a bullet list of operations, each with a concise summary and parameter breakdown. It is longer due to the number of operations, but every line adds value and the general instruction is front-loaded. No filler or redundant content exists.

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 no output schema and no annotations, the description covers operation purposes and parameters well. However, it omits return value structures, authentication details beyond 'connected user', and error behaviors. Given the complexity of seven sub-operations, this is a notable gap, though the description is still sufficient for basic 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?

The schema only defines a generic 'params' object without enumerating operation-specific keys. The description compensates thoroughly by listing each operation's parameters, including optionality markers, defaults, and examples (e.g., 'answers? (Answers data of the user, JSON array like : [{question: 1, answer: 3, time: 1230}] (time is in ms))'). This adds crucial semantic detail 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 calls the BetaSeries 'quiz' API and lists specific operations like 'get-quiz-history' and 'post-quiz-answer'. This unambiguously identifies the tool's purpose and differentiates it from sibling tools that target other API resources such as polls or statistics.

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 instructs the user to 'Pick an operation and pass its parameters' and provides a list of available operations with their endpoints and purposes. It clearly implies when to use this tool (for quiz-related queries and answer submission) but does not explicitly contrast it with alternative tools or state when not 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?

No annotations are present, so the description must disclose behavioral traits. It states that operations create a report or request an update, but it does not mention side effects, authentication requirements, or rate limits. For mutation actions, this lack of transparency 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 well-structured with a clear list of operations and their parameters. It is moderately sized but every section serves a purpose, though it could be slightly more compact without losing 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?

The description covers both operations and all their parameters, which is sufficient for invoking the tool. However, it lacks details about authentication, error handling, or return values, which would be helpful given no output schema or annotations. Overall, it is largely complete for its intended 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 only defines generic 'operation' and 'params' objects, but the description enumerates each operation's parameters, including types, mandatory/optional status, and meaning. This adds crucial meaning beyond the schema and is essential for correct invocation.

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 calls the BetaSeries 'reports' API and lists two specific operations with endpoints, making it evident what the tool does. It distinguishes from sibling tools by focusing solely on reports, not other BetaSeries resources.

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 instructs the user to 'Pick an operation' and pass parameters, providing a clear context for using the tool. It does not explicitly mention alternatives or exclusions, but the operation list defines when to use it, which is sufficient for a resource-specific 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?

With no annotations, the description must disclose all behavioral traits. It documents parameter constraints, defaults, and maximums (e.g., limit default and max for shows), and states that search results are returned. However, it omits authentication requirements, rate limits, response structure, and error handling, leaving notable 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 lengthy but well-structured, with operations listed and parameters formatted consistently. It is front-loaded with the API purpose and avoids redundancy. The length is justified by the complexity of the three operations and their many filters.

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?

Despite a minimal schema and no output schema, the description thoroughly documents all operations and parameters, including constraints and defaults. It lacks an example call and explicit guidance on when to use the tool versus siblings, but provides enough information for an agent to construct valid requests in most search scenarios.

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 only defines 'operation' and a generic 'params' object. All specific parameter names, meanings, types, defaults, and allowed values are provided in the description. Without the description, an agent would have no knowledge of the actual parameters, making it the primary source of parameter semantics.

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 explicitly states 'Call the BetaSeries search API' and lists three operations (get-search-all, get-search-movies, get-search-shows) with clear scopes. This distinguishes the tool from siblings like betaseries_movies or betaseries_shows, which handle specific content types rather than aggregated 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 description provides clear context for each operation's parameters and filters, implying when to use each sub-operation. However, it does not explicitly state when to use this search tool versus sibling tools for direct lookups, nor does it mention any alternatives 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, the description carries the full burden. Each operation's effect is explicitly stated (e.g., 'Remove all episodes of a season from hidden'), and parameter optionality conditions are noted. However, it does not disclose auth requirements, error behavior, response format, or reversibility beyond the immediate action.

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 lengthy but well-structured as a clear list of operations with their purposes and parameters. It is front-loaded with the main instruction, and while parameter descriptions repeat, each entry is necessary for the multi-operation 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 complex with 8 operations and multiple parameters, and no annotations or output schema. The description comprehensively covers all operations and their parameters, but lacks return value or error handling information. It is largely complete 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?

The schema only provides a generic params object, while the description lists every parameter per operation with meaningful descriptions such as 'Season number' and 'Rating assigned from 1 to 5'. This is essential and far exceeds the schema's contribution.

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 calls the BetaSeries seasons API and enumerates eight distinct operations with their HTTP methods and effects. This specific resource-level focus distinguishes it from sibling tools like betaseries_episodes or betaseries_shows.

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 instructs to pick an operation and pass parameters, and the operation list serves as internal guidance. However, it does not provide any context about when to use this tool versus alternatives, nor does it mention 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 burden. It discloses the HTTP method and a short functional summary for each operation (e.g., 'Remove a series from the member's account'), which conveys side effects. However, it does not mention authentication requirements, rate limits, or error behavior, leaving some transparency 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 front-loaded with a clear high-level instruction, but the body is an extensive, repetitive list of 34 operations with parameters. While each entry provides necessary information, the sheer length and identical phrasing patterns make it less concise than it could be, though still structurally organized.

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 and absence of an output schema, the description should explain return formats or response structures, but it does not. It also omits information about authentication, error handling, and pagination details beyond what parameter documentation hints at. The functional summaries are insufficient for an agent to fully anticipate tool behavior.

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 only defines a generic 'params' object, but the description goes far beyond by specifying exact parameter names, optionality, and semantics for every operation (e.g., 'id? (Series ID (Optional if thetvdb_id specified))'). This is essential for correct invocation and fully compensates for the schema's lack of operation-specific 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 opens with 'Call the BetaSeries "shows" API', which is a specific verb and resource clearly distinct from sibling tools focused on other domains (episodes, seasons, members, etc.). It enumerates all show-related operations, making the tool's scope 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 description provides the instruction 'Pick an operation and pass its parameters in the params object', which implies usage, but it does not explicitly state when to prefer this tool over alternatives like betaseries_seasons or betaseries_episodes. Context is clear from the operation list, but no exclusions or alternatives 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?

No annotations are provided, so the description carries the burden. It states the HTTP method (GET) and endpoint, and notes the data source (BigQuery aggregated data), which gives some context. However, it doesn't explicitly say whether authentication is required, rate limits, or response structure. For a read-only operation, this is a moderate level of 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 efficiently structured with a brief introduction followed by a bulleted list of the operation and its parameters. It avoids unnecessary words, though there is a minor typo ('data..'). The length is justified by the parameter 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?

For a single-operation wrapper with no output schema, the description covers the operation's purpose, all parameters, and their semantics. It doesn't describe the response structure, but that's not strictly necessary for selection and invocation. Given the tool's simplicity, this is nearly 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?

The description meticulously documents all parameters: name, optionality, default values, allowed values, and constraints (e.g., limit max 100). The schema only provides a generic 'params' object, so the description adds essential meaning for every parameter, making it highly informative.

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 tool as a wrapper for the BetaSeries stats API and names the specific operation (get-stats-shows-ranking) with a one-line summary of what it returns (shows ranking). While it doesn't explicitly distinguish itself from sibling tools, the 'stats' resource is unique among the siblings, so purpose is clear.

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 says to 'Pick an operation and pass its parameters,' which implies the usage pattern, but it doesn't provide when-to-use vs. alternatives or any exclusions. Sibling tools are for other resources, so using this for stats 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?

No annotations are provided, so the description carries the burden of disclosing behavior. It does note that post-subtitles-report removes subtitles from the list, indicating a side effect. However, it does not mention authentication requirements, rate limits, or response format, leaving notable 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 well-structured: a brief intro followed by a bulleted list of operations, each with endpoint and parameters. It is efficient for the number of operations, contains no filler, and front-loads the core purpose.

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

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

The description fully covers all five operations and their parameters, which is the essential information for invoking the tool. It lacks return-value details and error handling, but given the absence of an output schema and the multi-operation nature, it is reasonably 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?

The input schema's params object is a generic string map, so it provides no specific parameter names or values. The description is the sole source of parameter semantics, listing exactly which parameters each operation accepts (e.g., id, language, season, number) and their allowed values, adding far more meaning than 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 it calls the BetaSeries 'subtitles' API and enumerates five specific operations with their endpoints, distinguishing it from sibling tools like betaseries_shows or betaseries_episodes. Each operation is explicitly named, making the tool's 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 description provides clear context for when to use each operation (episode, last, season, show, report) by outlining their specific use cases. It does not explicitly contrast with sibling tools, but the resource-specific scope makes the appropriate usage obvious.

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 burden. It discloses that delete-tags-tag and post-tags-tag modify data and get-tags-list reads, and mentions the 'connected member' scope. But it omits response formats, error behavior, and idempotency details, which are important for a mutation 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 compact and front-loaded with the usage pattern, followed by a structured bullet list of three operations. Each line is informational, with no filler, and the format allows quick scanning and accurate selection.

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

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

The description fully specifies operations and parameters but lacks information about API responses, success/error conditions, and authentication requirements beyond 'connected member'. Since there is no output schema, the missing return-value documentation leaves a notable gap for an agent to anticipate tool output.

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's params property is a generic key/value object that explicitly refers to the tool description for actual parameter names. The description compensates fully by listing show_id, movie_id, tag, and type per operation, with optional markers and human-readable explanations. This is essential semantic coverage beyond what the structured schema provides.

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 calls the BetaSeries 'tags' API and enumerates three specific operations (delete-tags-tag, get-tags-list, post-tags-tag) with HTTP methods, paths, and actions. This makes the tool's purpose unambiguous and distinguishes it from sibling tools that handle different resources.

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 opening instruction tells the agent to pick an operation and pass parameters in the params object, and each operation entry lists its specific parameters. However, it does not explicitly compare against alternative tools or state when tags are preferable to other betaseries tools, though sibling names suggest distinct domains.

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 implies read-only via 'Display' and hints at authentication with 'identified member' and 'connected member' for some operations. However, it does not explicitly state authentication requirements, rate limits, or response format. The two nearly identical descriptions for get-timeline-feed and get-timeline-friends add ambiguity. This is adequate but not richly transparent.

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 long but necessarily so for six operations. It is front-loaded with an instruction and uses a consistent, scannable format (operation [endpoint]: purpose, Params: list). Some repetition in parameter definitions (e.g., nbpp, since_id) is present but acceptable for standalone operation reference. No 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?

For a multi-operation tool with no output schema, the description covers all operation purposes and parameters thoroughly. It lacks explicit details on authentication, response structure, or error behavior, which are important for a tool requiring an identified user for several operations. However, given the scope, it is mostly 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?

The schema only defines operation (enum) and a generic params object without property specifics, so the description is the sole source of parameter meaning. It lists every parameter per operation with explanations (e.g., 'id (ID of the event)', 'nbpp? (Number of events per page, maximum 100)') and marks optional ones with '?'. This far exceeds the schema's 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 this tool calls the BetaSeries 'timeline' API and lists six distinct operations, each with a specific verb and resource (e.g., 'Display a particular event', 'Display the latest events of the friends of the identified member'). This differentiates the operations within the tool and the timeline resource from sibling 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 clear context for selecting operations by detailing what each returns (event vs. friends' feed vs. site-wide events) and notes optional parameters like pagination. It does not explicitly reference sibling tools or when to avoid this tool, but the operation-level guidance is solid. Lacks explicit exclusions or alternatives, so not a 5.

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