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 mentions 'Delegate to utils.pagination.collect_all_results' which hints at pagination behavior but doesn't explain what this means operationally - whether it makes multiple API calls, handles rate limits, manages authentication, or what happens on errors. For a tool with 6 parameters and no annotation coverage, this is inadequate 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 extremely concise - a single sentence that gets straight to the point. There's no wasted words or unnecessary elaboration. However, this conciseness comes at the cost of being under-specified for a tool with significant complexity. The structure is front-loaded but lacks the necessary detail.

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

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

Given the tool's complexity (6 parameters, no output schema, no annotations, 0% schema coverage), the description is completely inadequate. It doesn't explain what the tool returns, how pagination works, what errors might occur, or how to interpret the parameters. For a general-purpose pagination collection tool that likely makes multiple API calls, this description leaves the agent with insufficient information to use it correctly.

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

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

With 0% schema description coverage and 6 parameters, the description provides absolutely no information about what the parameters mean or how to use them. It doesn't explain what 'endpoint' should contain, what 'params' or 'json_data' should include, when to use 'method' other than GET, or how 'max_pages' and 'limit' interact. The description fails to compensate for the complete lack of schema documentation.

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

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

The description states 'Delegate to utils.pagination.collect_all_results with api_client' which is a tautology - it essentially restates the tool name 'collect_all_results' with implementation details. It doesn't specify what the tool actually does (e.g., 'collects all paginated results from an API endpoint') or what resource it operates on. While it mentions 'pagination', the purpose remains vague compared to what a clear description would provide.

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. Given the sibling tools include 'paginate_results' which likely handles pagination differently, there's no indication of when to choose 'collect_all_results' over 'paginate_results' or other data retrieval tools. The description doesn't mention prerequisites, appropriate contexts, or exclusions for usage.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'pagination support', which hints at handling large datasets, but doesn't describe other critical behaviors like rate limits, authentication requirements, error handling, or what the output looks like (e.g., format, structure). For a tool with 5 parameters and no annotations, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly states what the tool does and adds a key feature ('pagination support'), making it easy to parse quickly. Every part of the sentence earns its place.

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

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

Given the complexity (5 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the tool's behavior beyond basic purpose, lacks parameter details, and offers no guidance on usage or output. For a tool that likely returns structured data (e.g., a list of studies), this leaves too many 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 schema description coverage is 0%, meaning none of the 5 parameters (page_number, page_size, sort_by, direction, limit) are documented in the schema. The description only vaguely implies pagination parameters but doesn't explain any parameters' purposes, valid values, or interactions (e.g., how 'limit' relates to 'page_size'). This fails to compensate for the lack of schema documentation.

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

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

The description clearly states the tool's purpose: 'Get a list of cancer studies in cBioPortal with pagination support.' It specifies the verb ('Get'), resource ('cancer studies'), and context ('cBioPortal'), making it easy to understand. However, it doesn't explicitly distinguish this tool from sibling tools like 'search_studies' or 'get_study_details', which would be needed for a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It mentions 'pagination support' but doesn't explain when pagination is necessary or how this differs from tools like 'search_studies' or 'paginate_results'. Without such context, an agent might struggle to choose the right tool for specific scenarios.

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 'pagination support', which is useful context, but fails to describe other key traits like whether this is a read-only operation, potential rate limits, authentication needs, or what the return format looks like. For a tool with 5 parameters and no annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence that front-loads the core purpose ('Get a list of all available cancer types in cBioPortal') and adds a key behavioral note ('with pagination support') without any wasted words. It's appropriately sized and structured for clarity.

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

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

Given the complexity (5 parameters, no annotations, no output schema), the description is incomplete. It covers the basic purpose and hints at pagination but lacks details on parameter usage, return values, error handling, or how it fits with sibling tools. This is inadequate for a tool with multiple undocumented parameters and no structured behavioral hints.

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

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

Schema description coverage is 0%, so the description must compensate by explaining parameters. It only mentions 'pagination support', which loosely relates to 'page_number' and 'page_size', but doesn't cover 'sort_by', 'direction', or 'limit', nor does it provide any syntax or format details. This adds minimal value beyond the bare schema, failing to adequately document the 5 parameters.

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

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

The description clearly states the verb ('Get') and resource ('list of all available cancer types in cBioPortal'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_cancer_studies' or 'get_study_details', which might also relate to cancer data, leaving some ambiguity about uniqueness.

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

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

The description provides no guidance on when to use this tool versus alternatives, such as 'get_cancer_studies' or 'search_studies'. It mentions pagination support, which hints at usage for large datasets, but lacks explicit when/when-not instructions or prerequisites for effective tool selection.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions pagination support, which is useful, but doesn't describe authentication needs, rate limits, error conditions, or what the return format looks like. For a data retrieval tool with 7 parameters, 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 concise with two sentences that each add value. It's front-loaded with the core purpose and efficiently adds supporting details. No wasted words or redundant information.

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

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

For a tool with 7 parameters, 0% schema description coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error handling, or fully document parameter semantics. The context signals indicate high complexity that the description doesn't adequately address.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'pagination support' (hinting at page_number/page_size) and 'specific attributes or all' (hinting at attribute_ids), but doesn't explain the other 5 parameters (study_id, sort_by, direction, limit) or provide format details. This partial coverage is insufficient given the low schema coverage.

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

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

The description clearly states the tool's purpose: 'Get clinical data for patients in a study' specifies both the verb ('Get') and resource ('clinical data'), and adds scope ('for patients in a study'). However, it doesn't explicitly differentiate from sibling tools like 'get_samples_in_study' or 'get_study_details', which reduces it from a perfect score.

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

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

The description mentions 'pagination support' and 'can fetch specific attributes or all', which provides some context for usage. However, it lacks explicit guidance on when to use this tool versus alternatives like 'paginate_results' or 'collect_all_results', and doesn't specify 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 full burden. It states the tool retrieves information, implying it's a read operation, but lacks details on permissions, rate limits, error handling, or response format. For a tool with no annotations, this is insufficient behavioral disclosure.

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 directly states the tool's function. It is front-loaded with the core purpose and includes essential details without unnecessary elaboration.

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

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

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks information on parameters, behavioral traits, and return values, making it inadequate for a tool with two parameters in a complex domain like gene panels.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'specific gene panel' which hints at the 'gene_panel_id' parameter, but does not explain 'projection' or provide any details on parameter formats, constraints, or usage. This leaves key parameters undocumented.

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

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('gene panel'), specifying it provides 'detailed information' including 'the list of genes'. However, it does not explicitly differentiate from sibling tools like 'get_gene_panels_for_study', which might retrieve similar data in a different context.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or exclusions, leaving the agent to infer usage based on tool name and parameters alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'pagination support' which is useful, but doesn't describe authentication requirements, rate limits, error conditions, or what the return format looks like (e.g., structure of gene panel objects). For a tool with 6 parameters and no output schema, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place with no 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 6 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain what a 'gene panel' contains, how results are structured, or provide enough context about the parameters. For a data retrieval tool in a biomedical context, more semantic information would be helpful.

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

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

Schema description coverage is 0%, so the description must compensate. It only mentions 'pagination support' which relates to 'page_number' and 'page_size', but doesn't explain the purpose of 'study_id', 'sort_by', 'direction', or 'limit' parameters. With 6 parameters and no schema descriptions, this leaves most parameter meanings unclear.

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

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

The description clearly states the verb 'Get' and resource 'all gene panels in a specific study', making the purpose understandable. It distinguishes itself from siblings like 'get_gene_panel_details' by focusing on listing panels rather than details, but doesn't explicitly contrast with 'paginate_results' or other list tools.

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

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

No guidance is provided on when to use this tool versus alternatives like 'paginate_results' or 'get_gene_panel_details'. The description mentions pagination support but doesn't explain when this is preferable over other pagination methods or list tools available on the server.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the 'batch endpoint' which implies handling multiple genes at once, but doesn't describe rate limits, error handling for invalid IDs, response format, or whether this is a read-only operation. The description is minimal and leaves critical behavioral traits unspecified for a tool with 3 parameters.

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

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

The description is a single, efficient sentence that communicates the core functionality without unnecessary words. It's appropriately sized for a straightforward retrieval tool and front-loads the essential information about what the tool does.

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

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

For a tool with 3 parameters, 0% schema description coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain what information is returned about genes, how results are structured, error conditions, or usage constraints. The description leaves too many gaps given the tool's complexity and lack of supporting documentation.

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

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

Schema description coverage is 0%, so the description must compensate but adds minimal parameter context. It mentions 'Hugo symbol or Entrez ID' which relates to 'gene_id_type' and 'gene_ids', but doesn't explain the 'projection' parameter at all or provide format examples for gene IDs. The description doesn't adequately compensate for the complete lack of schema descriptions.

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

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

The description clearly states the action ('Get information') and target resource ('specific genes'), specifying the lookup method ('by their Hugo symbol or Entrez ID') and endpoint type ('batch endpoint'). It distinguishes from siblings like 'search_genes' by focusing on batch retrieval of specific identifiers rather than search functionality. However, it doesn't explicitly contrast with 'get_multiple_genes' which might be a similar batch operation.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'search_genes' or 'get_multiple_genes'. It mentions the 'batch endpoint' but doesn't explain when batch retrieval is preferable over individual queries or other methods. No exclusions, prerequisites, or comparative context 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 full burden for behavioral disclosure. It mentions 'pagination support,' which is useful, but fails to cover other critical traits like whether this is a read-only operation, potential rate limits, error handling, or what the output format looks like (e.g., list structure). For a tool with 6 parameters and no output schema, this is a significant gap.

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

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

The description is a single, efficient sentence that front-loads the core purpose ('Get a list of molecular profiles') and adds key behavioral detail ('with pagination support'). There is no wasted verbiage, making it appropriately sized 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 complexity (6 parameters, 0% schema coverage, no output schema, no annotations), the description is incomplete. It covers the basic purpose and pagination but misses details on parameter usage, output format, error conditions, and how it differs from siblings. For a data retrieval tool in a biomedical context, more context is needed to ensure correct invocation.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only implies 'study_id' is needed and mentions pagination, but doesn't explain the semantics of other parameters like 'sort_by', 'direction', or 'limit'. This leaves most parameters without meaningful context beyond their titles in 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 action ('Get a list') and resource ('molecular profiles available for a specific cancer study'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_clinical_data' or 'get_gene_panels_for_study', which might also retrieve study-specific data, leaving some ambiguity about uniqueness.

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 minimal guidance by mentioning 'for a specific cancer study,' but it lacks explicit when-to-use instructions, alternatives (e.g., vs. 'get_gene_panels_for_study'), or prerequisites. No context on when not to use this tool is given, leaving the agent to infer usage from the purpose alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions concurrent retrieval but fails to detail critical aspects such as rate limits, authentication requirements, error handling, or response format. This leaves significant gaps for an agent to understand operational 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 a single, efficient sentence that directly states the tool's purpose without unnecessary elaboration. It is front-loaded and wastes no words, making it easy to parse quickly.

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

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

Given the complexity of a batch retrieval tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It omits essential details about parameters, behavioral traits, and output expectations, failing to provide a complete operational picture.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It does not explain the meaning or usage of 'gene_ids', 'gene_id_type', or 'projection', nor does it clarify default values or acceptable inputs. This lack of semantic context hinders effective parameter selection.

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

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

The description clearly states the action ('Get information') and resource ('multiple genes'), specifying the concurrent nature of the operation. However, it does not distinguish this tool from its sibling 'get_genes' or 'search_genes', leaving ambiguity about when to use this specific tool versus alternatives.

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

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

No explicit guidance is provided on when to use this tool versus alternatives like 'get_genes' or 'search_genes'. The description implies batch processing but lacks context on prerequisites, exclusions, or comparative use cases with sibling tools.

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

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

With no annotations provided, the description carries full burden but only states the basic operation. It doesn't disclose behavioral traits like whether this is a read-only operation, rate limits, authentication requirements, error handling for invalid IDs, or what 'details' include. The mention of 'concurrently' hints at performance but lacks specifics.

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

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

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for the tool's apparent simplicity.

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

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

Given no annotations, 0% schema coverage, and no output schema, the description is inadequate. It doesn't explain what 'details' include, how results are returned, error conditions, or performance implications of 'concurrently', leaving significant gaps for a tool that presumably returns structured data.

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

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

Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'study_ids' should contain (e.g., format, source, valid ranges), leaving the single parameter undocumented beyond the schema's basic type definition.

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

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

The description clearly states the action ('Get details') and resource ('multiple studies'), specifying the concurrent nature. It distinguishes from single-study tools like 'get_study_details' by emphasizing multiple studies, though it doesn't explicitly differentiate from other multi-entity tools like 'get_multiple_genes'.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'get_study_details' for single studies or 'search_studies' for filtered searches. It mentions 'concurrently' but doesn't explain why this matters or when batch retrieval is preferable.

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 'pagination support' which is helpful, but doesn't describe authentication needs, rate limits, error conditions, or what the response looks like (e.g., format, structure). For a tool with 8 parameters and no output schema, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place: 'Get mutations' (action), 'in a specific gene for a given study and sample list' (scope), 'with pagination support' (key feature). No wasted words or redundancy.

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

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

Given the complexity (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return format, error handling, or behavioral constraints. While it mentions pagination, it doesn't detail how pagination works with other parameters like 'limit'. For a data retrieval tool with multiple filtering/sorting options, more context is needed.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only mentions 'gene', 'study', 'sample list', and 'pagination', covering 3 of the 8 parameters (gene_id, study_id, sample_list_id, and implicitly page_number/page_size). It doesn't explain 'sort_by', 'direction', or 'limit', leaving most parameters without semantic context beyond their titles.

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

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

The description clearly states the tool's purpose: 'Get mutations in a specific gene for a given study and sample list, with pagination support.' It specifies the verb ('Get'), resource ('mutations'), and scope ('specific gene, study, sample list'), but doesn't explicitly differentiate from sibling tools like 'get_clinical_data' or 'get_molecular_profiles' that might also retrieve mutation-related data.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'paginate_results' (which might handle pagination generically) or 'get_multiple_genes' (which might retrieve mutations for multiple genes), nor does it specify prerequisites or exclusions for usage.

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

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

No annotations are provided, so the description carries full burden. It implies a read operation ('Get') but doesn't disclose behavioral traits like authentication needs, rate limits, error conditions, or what 'information' includes. This is inadequate for a tool with no annotation coverage.

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

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for the tool's apparent simplicity.

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

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

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain what 'sample list information' entails, return format, or error handling, leaving significant gaps for agent usage.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'study_id' and 'sample_list_id' but doesn't add meaning beyond what the schema titles provide—no format, constraints, or examples. This fails to address the coverage gap.

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

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

The description clearly states the verb 'Get' and the resource 'sample list information', specifying it's for a specific study and sample list ID. It distinguishes from siblings like 'get_samples_in_study' or 'get_study_details' by focusing on sample lists, but doesn't explicitly differentiate beyond the resource name.

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

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name and parameters alone.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions pagination support but doesn't describe what the tool returns (e.g., sample metadata, IDs), error conditions, rate limits, or authentication requirements. For a read operation with 6 parameters, 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 a single, well-structured sentence that efficiently communicates the core functionality and key feature (pagination). Every word earns its place with no 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?

For a tool with 6 parameters, 0% schema description coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'samples' contain, how results are structured, or provide enough context for the agent to understand the tool's full behavior and 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?

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only mentions 'pagination support' which relates to 'page_number' and 'page_size', but doesn't explain the purpose of 'study_id', 'sort_by', 'direction', or 'limit'. This leaves most parameters without semantic context beyond their schema titles.

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

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

The description clearly states the action ('Get a list of samples') and resource ('associated with a specific cancer study'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_sample_list_id' or 'get_clinical_data' which might also retrieve sample-related information, preventing a perfect score.

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

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

The description mentions 'with pagination support' which implies usage for large datasets, but provides no explicit guidance on when to use this tool versus alternatives like 'paginate_results' or 'collect_all_results'. There's no mention of prerequisites, exclusions, or comparison with siblings.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information' but doesn't specify what that entails (e.g., clinical data, molecular profiles, or other metadata), whether it's a read-only operation, potential rate limits, or error handling. This leaves significant gaps for a tool in a complex domain like cancer studies.

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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly, which is ideal for conciseness in this context.

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

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

Given the complexity of cancer study data and the lack of annotations or output schema, the description is insufficient. It doesn't explain what 'detailed information' includes, how it relates to sibling tools (e.g., 'get_clinical_data'), or potential behavioral aspects like data format or access constraints, leaving the agent with incomplete context for effective use.

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

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

The input schema has 1 parameter with 0% description coverage, so the schema provides no semantic context. The description implies a 'specific cancer study' is needed via 'study_id,' adding minimal meaning beyond the parameter name. However, it doesn't clarify the format or source of 'study_id' (e.g., from 'get_cancer_studies'), so it only partially compensates for the low schema coverage.

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

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

The description clearly states the verb 'Get' and resource 'detailed information for a specific cancer study,' which is specific and actionable. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_cancer_studies' or 'get_multiple_studies,' which might also retrieve study information but with different scopes or formats.

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

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_cancer_studies' (likely for listing studies) and 'get_multiple_studies' (likely for batch retrieval), there's no indication of context, prerequisites, or exclusions, leaving the agent to infer usage based on tool names alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails completely. It doesn't indicate whether this is a read or write operation, what permissions might be required, whether it makes network calls, what happens on errors, or any rate limiting considerations. The implementation detail about 'utils.pagination.paginate_results' doesn't help the agent understand the tool's 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 extremely concise - just one sentence. However, this conciseness comes at the cost of being severely under-specified. While it's not verbose or repetitive, it fails to provide essential information that would help the agent use the tool effectively.

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 5 parameters, 0% schema description coverage, no annotations, no output schema, and 15 sibling tools, this description is completely inadequate. It provides no information about what the tool does, when to use it, how parameters work, or what behavior to expect, making it essentially useless for an AI agent.

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

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

With 0% schema description coverage and 5 parameters (endpoint, params, method, json_data, max_pages), the description provides absolutely no information about what these parameters mean or how to use them. The description doesn't mention any parameters at all, leaving all 5 completely undocumented.

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 'Delegate to utils.pagination.paginate_results with api_client' is tautological - it essentially restates the tool name 'paginate_results' and provides implementation details rather than explaining what the tool does. It doesn't specify what resources it paginates or what problem it solves, making the purpose vague and unclear.

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

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

No guidance is provided about when to use this tool versus the 15 sibling tools listed. The description doesn't mention any context, prerequisites, or alternatives, leaving the agent with no information about appropriate usage scenarios.

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 pagination support but doesn't describe the return format, error conditions, rate limits, authentication requirements, or what happens when no matches are found. For a search tool with 6 parameters, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that front-loads the core functionality. Every word earns its place: 'Search for genes' establishes the action and resource, 'by keyword in their symbol or name' specifies the search scope, and 'with pagination support' adds a crucial behavioral constraint.

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

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

For a search tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (gene objects? IDs?), how results are structured, error handling, or the relationship between the various pagination/sorting parameters. The agent would need to guess about important behavioral aspects.

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

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

With 0% schema description coverage for all 6 parameters, the description must compensate but only mentions 'keyword' and 'pagination support' (which implies page_number/page_size). It doesn't explain the meaning of 'sort_by', 'direction', or 'limit' parameters, nor does it clarify the relationship between pagination parameters and the limit parameter.

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

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

The description clearly states the tool's purpose: searching for genes by keyword in symbol or name with pagination support. It specifies the resource (genes), verb (search), and scope (keyword matching in symbol/name). However, it doesn't explicitly distinguish this from sibling tools like 'get_genes' or 'get_multiple_genes', which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools like 'get_genes', 'get_multiple_genes', and 'paginate_results', there's no indication of when this keyword-based search is preferred over other gene retrieval methods or how it relates to the general pagination 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 full burden for behavioral disclosure. It mentions 'pagination support' which is useful context, but doesn't describe what the tool returns (study objects, IDs, summaries?), error conditions, rate limits, authentication requirements, or whether it's a read-only operation. For a search tool with 6 parameters, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place - 'search for cancer studies' establishes the action, 'by keyword in their name or description' specifies the search scope, and 'with pagination support' adds important behavioral context without redundancy.

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

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

For a search tool with 6 parameters, 0% schema description coverage, no annotations, and no output schema, the description is insufficient. It doesn't explain return values, error handling, or fully document parameters. While concise, it doesn't provide enough context for an agent to use the tool effectively without additional documentation.

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

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

Schema description coverage is 0%, so the description must compensate for all 6 parameters. It only mentions 'keyword' and implies pagination (covering 'page_number', 'page_size'), but doesn't explain 'sort_by', 'direction', or 'limit' parameters. The description adds some meaning for 2-3 parameters but leaves others completely undocumented.

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

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

The description clearly states the tool searches for cancer studies by keyword in name or description with pagination support, providing a specific verb ('search') and resource ('cancer studies'). It distinguishes from siblings like 'get_cancer_studies' by specifying keyword-based search, though it doesn't explicitly contrast with 'search_genes' or 'paginate_results'.

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 mentions 'pagination support' which implies usage for large result sets, but provides no explicit guidance on when to use this tool versus alternatives like 'get_cancer_studies' (which might retrieve specific studies) or 'paginate_results' (which might handle pagination differently). No when-not-to-use or prerequisite information is included.

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