Clinical Trials MCP Server

Server Quality Checklist

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Latest release: v1.0.1
Disambiguation4/5
Most tools have distinct purposes, such as get_study_details for specific trials versus search_by_condition for condition-based queries. However, some overlap exists between search_studies (general search) and more specific search tools like search_by_location, which could cause minor confusion in tool selection.
Naming Consistency5/5
The naming follows a highly consistent pattern with clear verb_noun structures, such as get_pediatric_studies and search_by_condition. All tools use snake_case and maintain a uniform style throughout the set, making them predictable and easy to understand.
Tool Count4/5
With 17 tools, the count is slightly high but reasonable for a clinical trials domain that requires diverse search and retrieval capabilities. It covers various aspects like demographics, conditions, and timelines without feeling excessively bloated, though it borders on being heavy.
Completeness5/5
The tool set provides comprehensive coverage for clinical trials, including detailed searches by condition, intervention, location, and more, along with retrieval of study details, timelines, and statistics. It supports full lifecycle aspects from recruiting to completed studies with results, leaving no obvious gaps for agent workflows.
Average 2.9/5 across 17 of 17 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'various filters' but doesn't describe what the search returns (list of studies? metadata?), pagination behavior beyond the pageSize parameter, rate limits, authentication requirements, or whether this is a read-only operation. For a search tool 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point. It's appropriately sized for what it communicates, though it could be more informative given the tool's complexity and sibling context. No wasted words or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, no output schema, no annotations, and 16 sibling alternatives), the description is inadequate. It doesn't explain what the search returns, how results are ordered, whether all parameters are optional, or how this differs from other search tools. The description should provide more context about this tool's specific role in the ecosystem.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly with descriptions and enums. The description adds no additional parameter semantics beyond mentioning 'various filters' which is already evident from the schema. 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search for clinical trials with various filters' clearly states the verb (search) and resource (clinical trials), but it's vague about scope and doesn't differentiate from the 16 sibling tools that also search or retrieve studies. It doesn't specify what makes this tool distinct from alternatives like search_by_condition or search_by_intervention.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 many sibling alternatives. With 16 other study-related tools, the description offers no context about when this general search is preferable to more specific searches like search_by_condition or get_recruiting_studies. There's no mention of prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'advanced search' but doesn't disclose behavioral traits like whether this is a read-only operation, potential rate limits, authentication needs, or what happens with partial criteria. The description is too minimal to provide meaningful behavioral context for a search tool with 8 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with zero waste. Every word contributes to the core message, though the message itself is under-specified. The structure is front-loaded with the essential concept.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 8 parameters, no annotations, and no output schema, the description is incomplete. It doesn't specify what resource is being searched (clinical trials/studies), what the return format looks like, or how results are structured. With many sibling tools, more context is needed to distinguish this tool's specific role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description adds no additional meaning about parameters beyond implying they relate to 'eligibility criteria'. 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Advanced search based on detailed eligibility criteria' states the general purpose (search with eligibility criteria) but is vague about what resource is being searched. It doesn't specify this searches for clinical trials/studies, nor does it distinguish from siblings like 'search_by_condition' or 'search_by_intervention' which also search studies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many sibling search tools (e.g., 'search_by_condition', 'search_by_location'), the description provides no context about when eligibility-based search is preferred over other search methods or what makes it 'advanced'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Find clinical trials' but does not specify whether this is a read-only operation, what permissions are needed, if there are rate limits, or what the output format looks like. For a tool with no annotations, 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.
Conciseness5/5
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 any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a search tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, usage guidelines, and output expectations, which are crucial for an AI agent to use the tool effectively in a context with many similar sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 documents all parameters thoroughly. The description does not add any additional meaning or context beyond what the schema provides, such as explaining how parameters interact or default behaviors. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Find' and the resource 'clinical trials specifically designed for children and adolescents', making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'search_by_condition' or 'search_by_eligibility_criteria', which could also potentially filter for pediatric studies, so it lacks full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available for searching studies, there is no indication of prerequisites, exclusions, or specific contexts where this tool is preferred over others like 'search_by_condition' or 'search_by_eligibility_criteria'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 retrieving 'contact information', which adds some context beyond a basic read, but fails to disclose critical behaviors like pagination (implied by 'pageSize' parameter), rate limits, authentication needs, or what 'currently recruiting' entails (e.g., real-time vs. cached data). This is inadequate for a tool with parameters and 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.
Conciseness5/5
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 complexity, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It lacks details on return values (e.g., format of contact information, result structure), error handling, or behavioral constraints like rate limits. For a tool with 4 parameters and many siblings, this leaves significant gaps for an agent to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all parameters. The description adds no additional meaning about parameters beyond implying filtering by recruitment status and contact info inclusion, which is minimal. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('currently recruiting clinical trials with contact information'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'search_by_condition' or 'search_by_location' that might also retrieve recruiting studies, missing full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools available (e.g., 'search_by_condition', 'search_by_location'), the description lacks any indication of context, prerequisites, or exclusions, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read-only search operation but doesn't disclose rate limits, authentication needs, result format, pagination behavior, or what constitutes 'similarity' beyond the parameter types. This is inadequate for a tool with potential complexity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 with zero wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a tool that performs similarity matching (which can be complex), the description is insufficient. It doesn't explain what the tool returns, how similarity is calculated, error conditions, or behavioral constraints, leaving significant gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing full parameter documentation. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how 'similarityType' affects results or provide examples of similarity matching). Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Find') and resource ('clinical trials similar to a specific study'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_by_condition' or 'search_by_intervention' that might also find similar studies through different mechanisms, missing full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid NCT ID), exclusions, or how it differs from sibling search tools that might achieve similar outcomes, leaving usage context ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 information but does not specify if it's read-only, requires authentication, has rate limits, or describes the return format. 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.
Conciseness5/5
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 any redundant or unnecessary information. It is appropriately sized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It does not explain what 'detailed information' includes, the response format, or behavioral traits like error handling. For a tool with rich sibling context and no structured support, this leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'nctId' fully documented in the schema. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 about a specific clinical trial'), making the purpose unambiguous. However, it does not explicitly differentiate from siblings like 'get_study_timeline' or 'get_trial_statistics', which might also retrieve study details, so it lacks sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or compare to sibling tools like 'get_studies_with_results' or 'search_by_condition', leaving the agent with no usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get aggregate statistics' implies a read-only operation, it doesn't specify whether this requires authentication, has rate limits, returns paginated results, or provides any information about the format or scope of the statistics returned. For a tool with no annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately front-loaded with the essential information, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of statistical aggregation, the lack of annotations, and no output schema, the description is incomplete. It doesn't explain what kind of statistics are returned (counts, averages, distributions), how results are formatted, or any limitations of the aggregation. For a tool with 2 parameters and no structured output documentation, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter information beyond what's already in the schema, which has 100% coverage with clear descriptions for both parameters. The baseline score of 3 is appropriate since the schema adequately documents the parameters, though the description could have provided additional context about how grouping and filtering work together.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get aggregate statistics') and resource ('about clinical trials'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its many sibling tools that also retrieve clinical trial information, such as 'get_study_details' or 'get_studies_with_results', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 15 sibling tools on the server, including various search and retrieval functions, the lack of any usage context leaves the agent guessing about appropriate scenarios for statistical aggregation versus other operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Search' implies a read-only operation, it doesn't specify whether this is a safe query, what permissions are needed, whether results are paginated, or what format the output takes. For a search tool with 6 parameters and no annotations, this is insufficient 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the tool's core purpose without unnecessary words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 address behavioral aspects (safety, permissions, pagination), doesn't differentiate from sibling tools, and provides no guidance on parameter interactions or result format. The 100% schema coverage helps with parameters, but other contextual gaps remain significant.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain relationships between date parameters or how condition filtering interacts with date ranges). 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.
Purpose4/5
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 clinical trials by start or completion date range'. It specifies the verb ('Search'), resource ('clinical trials'), and scope ('by start or completion date range'). However, it doesn't explicitly differentiate from sibling tools like 'search_by_condition' or 'search_by_intervention', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling search tools available (e.g., 'search_by_condition', 'search_by_location'), there's no indication of when date-range filtering is appropriate versus other search criteria. This leaves the agent without contextual usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'search' implies a read-only operation, the description doesn't mention any behavioral traits such as pagination behavior (implied by pageSize parameter but not explained), rate limits, authentication requirements, or what happens when no results are found. This leaves significant gaps for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 any unnecessary words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the search returns (trial names, IDs, details?), how results are structured, or any limitations beyond what's implied by parameters. The context signals indicate this tool needs more comprehensive documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema (e.g., it doesn't explain how intervention matching works or provide examples). This meets the baseline expectation when schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as searching clinical trials by intervention or treatment type, which includes a specific verb ('search') and resource ('clinical trials'). However, it doesn't explicitly differentiate from sibling tools like 'search_by_condition' or 'search_by_sponsor', which also search clinical trials but by different criteria.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling search tools available (e.g., search_by_condition, search_by_location), there's no indication of when intervention-based searching is appropriate or when other search methods might be better suited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral information. It doesn't disclose whether this is a read-only operation, what authentication might be required, rate limits, pagination behavior (beyond the pageSize parameter), or what format results will be returned in. 'Find' implies a search/read operation but lacks specifics about system behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a search tool and front-loads the essential information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 and no output schema, the description is insufficient. It doesn't explain what results look like, how pagination works (despite having a pageSize parameter), or any constraints on geographic searching. With no annotations and no output schema, the agent lacks crucial information about system behavior and response format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all 6 parameters. The description adds no parameter-specific information beyond what's in the schema. The baseline score of 3 reflects adequate parameter documentation coming entirely from the schema rather than the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Find' and resource 'clinical trials' with the geographic location constraint. It distinguishes itself from many sibling tools that search by other criteria (condition, intervention, date range, etc.), but doesn't explicitly contrast with 'search_international_studies' or 'search_studies' which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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_studies' or 'search_international_studies'. It doesn't mention prerequisites, limitations, or typical use cases. The agent must infer usage from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the search action without detailing aspects like whether it's read-only, if it requires authentication, rate limits, pagination behavior (beyond the 'pageSize' parameter), or what the output format looks like. For a search tool with no annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Search clinical trials by sponsor or organization.' It is front-loaded with the core purpose, contains no redundant information, and every word earns its place. This is an excellent example of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a search tool with 3 parameters) and lack of annotations and output schema, the description is incomplete. It does not explain return values, error conditions, or behavioral traits like pagination or authentication needs. For a tool with no structured output information, the description should provide more context to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear details for all parameters (sponsor, sponsorType, pageSize). The description adds no additional parameter semantics beyond what's in the schema. According to the rules, with high schema coverage (>80%), the baseline score is 3, as the schema adequately documents parameters without needing extra description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 clinical trials by sponsor or organization.' It specifies the verb ('search') and resource ('clinical trials'), and distinguishes the search dimension ('by sponsor or organization'). However, it does not explicitly differentiate from sibling tools like 'search_by_condition' or 'search_by_intervention,' which would be needed for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling search tools available (e.g., 'search_by_condition,' 'search_by_location'), there is no indication of when sponsor-based searching is appropriate or when other search methods might be better. This lack of context leaves the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action ('Find') without detailing aspects like pagination behavior, rate limits, authentication needs, or what happens with partial inputs. For a search tool with no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—a single sentence with no wasted words. It's front-loaded and gets straight to the point, making it easy to parse quickly. This efficiency is appropriate for a tool with a clear primary function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (6 parameters, no output schema, no annotations), the description is insufficient. It lacks details on behavioral traits, usage context, and output expectations. For a search tool with multiple filtering options and no structured output definition, more comprehensive guidance is needed to ensure effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add any parameter-specific information beyond what the input schema provides. Since schema description coverage is 100%, the baseline score is 3. The description mentions 'multi-country,' which aligns with parameters like 'minCountries,' but doesn't offer additional context or examples for parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Find multi-country international clinical trials.' It specifies the verb ('Find') and resource ('multi-country international clinical trials'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'search_by_location' or 'search_studies,' which might also involve location-based filtering.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available (e.g., 'search_by_location,' 'search_studies'), there's no indication of specific use cases, prerequisites, or exclusions. This lack of context could lead to confusion in tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'search' but doesn't clarify if this is a read-only operation, whether it requires authentication, what the output format looks like, or any rate limits. For a search tool with no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Search clinical trials for rare diseases and orphan conditions.' It's front-loaded with the core purpose and contains no unnecessary words or redundancy, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a search tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., list of trials, details), how results are formatted, or any behavioral traits like pagination or error handling. This leaves critical gaps for an agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 all parameters (rareDisease, recruitmentStatus, pageSize). The description doesn't add any semantic details beyond what's in the schema, such as examples of rare disease names or how recruitment status affects results. With high schema coverage, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 clinical trials for rare diseases and orphan conditions.' It specifies the verb ('search') and resource ('clinical trials') with a clear scope ('rare diseases and orphan conditions'). However, it doesn't explicitly differentiate from sibling tools like 'search_by_condition' or 'search_studies,' which might overlap in functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling search tools (e.g., 'search_by_condition,' 'search_studies'), there's no indication of whether this tool is specialized for rare diseases, how it differs from general searches, or any prerequisites for use. This leaves the agent to guess based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'detailed timeline and milestone information' but doesn't specify what that includes (e.g., dates, statuses, events), whether it's read-only (implied by 'Get'), any rate limits, authentication needs, or pagination behavior beyond the 'pageSize' parameter in the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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. Every part of it ('Get detailed timeline and milestone information for studies') contributes directly to understanding the tool's function, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is minimally adequate for a read operation but leaves gaps. It doesn't explain the return format (e.g., what 'detailed timeline' entails), error conditions, or how it integrates with sibling tools. For a tool with 5 parameters and no structured output documentation, more context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what's already in the input schema, which has 100% coverage with clear descriptions and enums for parameters like 'phase' and 'timelineType'. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate with additional context or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('detailed timeline and milestone information for studies'), making it easy to understand what it does. However, it doesn't explicitly differentiate from siblings like 'get_study_details' or 'search_by_date_range', which might also provide timeline-related information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools focused on studies (e.g., 'get_study_details', 'search_by_date_range'), there's no indication of whether this tool is for comprehensive timeline analysis, filtered views, or how it differs from other study-related queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 is a search operation, implying it's likely read-only and non-destructive, but doesn't confirm this or detail other behaviors like rate limits, authentication needs, pagination (beyond the 'pageSize' parameter), or error handling. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 ('Search for clinical trials') and the key filter ('focusing on specific medical conditions'), 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, 1 required), 100% schema coverage, and no output schema, the description is minimally adequate. It clarifies the tool's focus but lacks context on behavioral traits (due to no annotations), usage guidelines, or output details. For a search tool, this leaves the agent to rely heavily on the schema, resulting in a baseline completeness score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters are well-documented in the input schema itself (e.g., 'condition' as 'Medical condition, disease, or syndrome'). The description adds no additional parameter semantics beyond implying a focus on 'medical conditions,' which aligns with the schema. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 clinical trials focusing on specific medical conditions.' It specifies the verb ('Search') and resource ('clinical trials'), and the qualifier 'focusing on specific medical conditions' distinguishes it from general search tools. However, it doesn't explicitly differentiate from all sibling tools like 'search_by_intervention' or 'search_by_sponsor,' which also search clinical trials but with different filters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'search_by_intervention' for drug-based searches or 'search_by_location' for geographic filters, nor does it specify prerequisites or exclusions. The agent must 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.
Behavior2/5
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 it's a search tool, implying read-only behavior, but doesn't mention any constraints like rate limits, authentication requirements, result format, pagination beyond the schema's 'pageSize,' or whether it's a real-time or cached search. For a search tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is minimally adequate. It states the purpose but lacks behavioral details and usage context. Without an output schema, it doesn't describe return values, which is a gap, but the schema coverage helps compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any meaning beyond what's in the schema (e.g., it doesn't explain what 'primary outcome measures' entail or provide examples). 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.
Purpose4/5
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 clinical trials by primary outcome measures or endpoints.' It specifies the verb ('search'), resource ('clinical trials'), and search criteria ('primary outcome measures or endpoints'). However, it doesn't explicitly differentiate from sibling tools like 'search_by_condition' or 'search_by_intervention,' which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling search tools (e.g., 'search_by_condition,' 'search_by_intervention'), there's no indication of when this specific outcome-based search is preferred or what distinguishes it from other search methods.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 that the tool finds 'completed clinical trials that have published results,' which implies read-only behavior and a focus on finalized data, but it doesn't disclose details like rate limits, authentication needs, pagination behavior, or what 'published results' entails (e.g., format, availability). This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Find completed clinical trials that have published results') with zero waste. It's appropriately sized for the tool's complexity, making it easy to understand quickly without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is minimally adequate. It clearly states the purpose but lacks details on behavioral traits (e.g., pagination, error handling) and output format. With no output schema, the description should ideally hint at return values, but it doesn't, leaving gaps in completeness for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for all four parameters (e.g., 'Medical condition to filter by,' 'Find studies completed after this date (YYYY-MM-DD)'). The description doesn't add any parameter-specific semantics beyond what the schema provides, such as explaining how filters combine or default behaviors. Baseline score of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('Find') and resources ('completed clinical trials that have published results'). It distinguishes from siblings like 'get_recruiting_studies' (which finds ongoing trials) and 'get_study_details' (which provides details on a specific study) by focusing on completed trials with published results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by specifying 'completed clinical trials that have published results,' suggesting it's for finding finalized studies with available outcomes. However, it doesn't explicitly state when to use this tool versus alternatives like 'search_by_condition' or 'get_study_details,' nor does it mention prerequisites or exclusions, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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