Movies

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

With no annotations provided, the description carries full burden for behavioral disclosure. It effectively explains the tool's behavior: Pipeworx 'picks the right tool, fills the arguments, and returns the result.' This covers the automation aspect, though it doesn't mention potential limitations like rate limits, authentication needs, 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 perfectly structured: first sentence states the core purpose, second explains the automation benefit, third provides usage guidance, and final part offers concrete examples. Every sentence earns its place with zero wasted words, making it highly scannable and informative.

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-parameter tool with 100% schema coverage but no annotations or output schema, the description provides excellent context about the tool's intelligent routing behavior and appropriate use cases. The examples help clarify the scope, though additional information about return formats or error handling would make it more complete.

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

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

Schema description coverage is 100%, so the schema already documents the single 'question' parameter adequately. The description reinforces this with 'Your question or request in natural language' and provides examples, but doesn't add significant semantic value beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Ask a question in plain English and get an answer from the best available data source.' It specifies the verb ('ask'), resource ('answer'), and scope ('from the best available data source'), distinguishing it from sibling tools like search_movies or get_tv_schedule that target specific 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 explicitly states when to use this tool: 'No need to browse tools or learn schemas — just describe what you need.' It provides clear alternatives (implicitly suggesting other tools for structured queries) and includes three concrete examples to illustrate appropriate 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 effectively describes key behaviors: it's a search operation (implied read-only), returns ranked results ('most relevant'), and handles large tool sets. However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions, leaving some gaps for a tool with no annotation coverage.

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

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

The description is highly concise and well-structured in two sentences. The first sentence states the core functionality, and the second provides critical usage guidance. Every phrase adds value without redundancy, making it easy to parse and front-loaded with essential information.

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

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

Given the tool's moderate complexity (search functionality with 2 parameters), 100% schema coverage, and no output schema, the description is largely complete. It clarifies the tool's role in large catalogs and when to use it, which compensates for the lack of output schema. However, without annotations, it could benefit from more behavioral details like response format or error 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?

The schema description coverage is 100%, so the schema already fully documents both parameters. The description adds minimal parameter semantics beyond the schema—it implies the 'query' parameter should describe user needs in natural language, but this is already covered in the schema's description. No additional parameter context is provided, meeting the baseline for high schema coverage.

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

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

The description clearly states the tool's purpose with specific verbs ('search', 'returns') and resources ('Pipeworx tool catalog', 'most relevant tools with names and descriptions'). It explicitly distinguishes this tool from potential alternatives by emphasizing its role in navigating large tool catalogs (500+ tools), which is distinct from the sibling tools focused on TV/movie content.

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

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

The description provides explicit guidance on when to use this tool ('Call this FIRST when you have 500+ tools available and need to find the right ones for your task'), including a clear condition (500+ tools) and a recommended order (first). It implicitly suggests alternatives by highlighting its specialized role for large catalogs, though it doesn't name specific sibling tools as alternatives.

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 states 'Delete' implies a destructive mutation, but doesn't clarify if this is permanent, reversible, requires specific permissions, or has side effects (e.g., affecting other tools). For a deletion tool with zero annotation coverage, this is a significant gap in safety and operational context.

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

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

The description is extremely concise and front-loaded with a single, direct sentence that states the core action without any wasted words. Every part of the sentence ('Delete a stored memory by key') contributes essential information, making it 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?

Given the tool's destructive nature (deletion), lack of annotations, and no output schema, the description is incomplete. It doesn't address critical aspects like what happens after deletion (success/failure responses, error handling), confirmation requirements, or how it integrates with the memory system implied by sibling tools, leaving the agent with insufficient operational context.

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

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

The description adds minimal meaning beyond the input schema, which already has 100% coverage with a clear parameter description ('Memory key to delete'). The description restates this as 'by key' but doesn't provide additional context like key format, examples, or constraints, so it meets the baseline for high schema coverage without adding value.

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

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

The description clearly states the tool's purpose with a specific verb ('Delete') and resource ('stored memory by key'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'recall' or 'remember', which likely interact with the same memory system, leaving some ambiguity about the exact relationship.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing memory key), exclusions, or how it relates to sibling tools like 'recall' (which might retrieve memories) or 'remember' (which might create them), leaving the agent to infer usage context.

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

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

No annotations are provided, so the description carries the full burden. It discloses the default behavior ('Defaults to today's US schedule'), which is useful context. However, it lacks details on behavioral traits like rate limits, authentication needs, error handling, or response format, leaving gaps for a tool with no annotations.

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

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

The description is a single, efficient sentence that front-loads the core purpose and includes essential default information. Every word earns its place with no redundancy or unnecessary details, making it highly concise and well-structured.

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

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

Given the tool's low complexity (2 optional parameters, no output schema), the description is adequate but incomplete. It covers the purpose and defaults but lacks output details (e.g., schedule format) and behavioral context (e.g., pagination, errors), which would be needed for full completeness without annotations.

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

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

Schema description coverage is 100%, so the schema fully documents the parameters (date format, country code, defaults). The description adds marginal value by reinforcing the defaults but does not provide additional semantic context beyond what the schema already specifies, aligning with the baseline for high 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 specific action ('Get the TV broadcast schedule') and resource ('for a given country and date'), with explicit scope details ('Defaults to today's US schedule'). It distinguishes from sibling tools like 'get_tv_show' (individual shows) and 'search_tv_shows' (searching rather than schedule retrieval).

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 this tool (to retrieve broadcast schedules by country/date) and implies when not to use it (e.g., for individual show details or searching). However, it does not explicitly name alternatives or state exclusions, such as when to use 'search_tv_shows' instead for non-schedule queries.

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 states it returns 'full details' and 'complete episode list', which helps, but doesn't mention response format, pagination, rate limits, authentication needs, or error behavior. For a read operation with no annotation coverage, this leaves 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, efficient sentence that front-loads the core purpose ('Get full details for a TV show') and adds necessary scope ('by its TVmaze ID, including its complete episode list'). Every word earns its place with zero 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?

Given one parameter with full schema coverage and no output schema, the description adequately covers the purpose and scope. However, as a read operation with no annotations, it should ideally mention response structure or limitations to be fully complete. It's minimally viable but has clear gaps in behavioral context.

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

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

Schema description coverage is 100%, so the schema already documents the single parameter 'id' with type and example. The description adds context that it's for 'TVmaze ID' and implies it retrieves details based on that, but doesn't provide additional syntax or format details beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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

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

The description clearly states the specific action ('Get full details'), resource ('a TV show'), and scope ('by its TVmaze ID, including its complete episode list'). It distinguishes from siblings like get_tv_schedule (schedule-based) and search_tv_shows (search-based) by specifying ID-based lookup with full details including episodes.

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

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

The description implies usage when you have a TVmaze ID and need full details with episodes, but doesn't explicitly state when to use this vs. alternatives like search_tv_shows (when you don't have an ID) or get_tv_schedule (for schedule info). No explicit exclusions or prerequisites 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's dual behavior (retrieve by key vs. list all) and persistence across sessions. However, it doesn't mention potential limitations like memory size constraints, error conditions, or performance characteristics.

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

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

The description is perfectly concise with two sentences that each serve distinct purposes: the first defines the tool's dual functionality, the second provides usage context. Every word contributes to understanding, with zero redundancy 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?

For a simple retrieval tool with no annotations and no output schema, the description provides good contextual coverage. It explains what the tool does, when to use it, and parameter semantics. The main gap is lack of information about return format (what a 'memory' contains), but given the tool's simplicity, this is a minor omission.

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

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

The schema has 100% description coverage for its single parameter, so the baseline is 3. The description adds meaningful context by explaining the semantic effect of omitting the key parameter ('omit to list all keys'), which goes beyond the schema's technical documentation. This elevates the score above baseline.

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

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

The description clearly states the tool's purpose with specific verbs ('retrieve', 'list') and resources ('previously stored memory', 'all stored memories'). It distinguishes from siblings like 'remember' (store) and 'forget' (delete) by focusing on retrieval operations.

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 explicit usage guidance: 'Use this to retrieve context you saved earlier in the session or in previous sessions' establishes the primary use case. It also specifies when to omit the key parameter ('omit key to list all keys'), creating clear alternatives within the same 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 provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool performs a write operation (storage), has persistence characteristics (authenticated users get persistent memory, anonymous sessions last 24 hours), and operates across tool calls. However, it doesn't mention potential limitations like storage capacity or key constraints.

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

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

The description is appropriately sized and front-loaded, with the core purpose stated first followed by usage guidance and behavioral context. Both sentences earn their place by providing essential information without redundancy or unnecessary elaboration.

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

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

Given the tool's moderate complexity (write operation with persistence implications), no annotations, and no output schema, the description does well by explaining the storage function, usage scenarios, and persistence behavior. However, it doesn't specify what happens on success/failure or potential error conditions, 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?

Schema description coverage is 100%, so the schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for adequate but not enhanced 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 clearly states the tool's purpose with specific verbs ('store a key-value pair') and resource ('in your session memory'), distinguishing it from siblings like 'recall' (retrieval) and 'forget' (deletion). It explicitly identifies the action and target resource.

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 explicit guidance on when to use this tool ('to save intermediate findings, user preferences, or context across tool calls') and distinguishes it from alternatives by specifying its storage function. It also clarifies usage contexts for authenticated vs. anonymous users.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the return fields but doesn't cover critical aspects like rate limits, authentication needs, error handling, or pagination. For a search tool with no annotations, this leaves significant gaps in understanding its operational 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 concise and front-loaded, stating the core purpose in the first sentence and listing return fields efficiently. It avoids redundancy, but the list of return fields could be slightly streamlined (e.g., grouped). Overall, it's well-structured with no wasted words.

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

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

Given the tool's moderate complexity (search function with 2 parameters) and lack of annotations or output schema, the description is partially complete. It covers the purpose and return fields but misses behavioral details and usage guidelines. It's adequate for basic understanding but has clear gaps for effective agent use.

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

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

The description adds minimal value beyond the input schema, which has 100% coverage. It mentions searching 'by title or keyword,' aligning with the 'query' parameter description, but doesn't provide additional context like search algorithms or result ordering. With high schema coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Search for movies by title or keyword.' It specifies the verb ('Search') and resource ('movies'), and distinguishes it from sibling tools focused on TV content. However, it doesn't explicitly contrast with 'search_tv_shows' beyond the resource type, missing a direct sibling differentiation.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose it over 'search_tv_shows' or other siblings, nor does it specify prerequisites or exclusions. Usage is implied by the resource type 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 full burden. It mentions the return fields (show name, genres, dates, rating, summary, image), which is helpful, but doesn't disclose behavioral traits like pagination, rate limits, authentication needs, or error handling. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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

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

The description is appropriately sized and front-loaded: the first sentence states the core purpose, and the second adds return value details. Every sentence earns its place with zero waste, making it 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?

Given the tool's moderate complexity (search function with 1 parameter) and no annotations or output schema, the description is partially complete. It covers purpose and return fields but lacks behavioral context (e.g., result limits, sorting) and doesn't fully compensate for the absence of structured data. Adequate 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 100%, with the single parameter 'query' documented as 'TV show name or keyword to search for'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or search behavior details. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Search for TV shows by name' (verb+resource). It distinguishes from sibling 'search_movies' by specifying TV shows, but doesn't differentiate from 'get_tv_show' which might retrieve specific shows. The description is specific but could better clarify sibling distinctions.

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

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

The description implies usage context (searching by name/keyword) but doesn't explicitly state when to use this tool versus alternatives like 'get_tv_show' (which might retrieve specific shows) or 'search_movies'. No guidance on when-not-to-use or prerequisites is provided, leaving usage somewhat ambiguous.

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