Health Data

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

Annotations are absent, so the description must disclose behavioral traits. It mentions outputs but does not disclose rate limits, pagination, error handling, or data freshness. For a read operation, it lacks important context.

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

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

Two sentences, no repetition, front-loaded with the key action and output. Every word 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?

The description covers the main return fields, lacks output schema but that is acceptable. Missing details on ordering and error behavior are minor gaps given the tool's simplicity.

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

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

Schema description coverage is 100% with clear parameter descriptions. The tool description adds no additional semantic value beyond the schema, so it meets the baseline without enhancement.

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 'Search ClinVar for genetic variants associated with a gene' and lists specific outputs (clinical significance, conditions, review status). This distinguishes it from sibling tools (NIH grants, protein expression, WHO health) which are different domains.

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

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

No explicit guidance on when to use this tool vs alternatives, but sibling tools are unrelated so no confusion. No prerequisites or context for using ClinVar data are provided.

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

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

No annotations exist, so the description carries the full burden. It states the tool returns data but does not disclose behavioral traits like authentication needs, rate limits, pagination, or whether it is read-only. For a search tool, basic safety and behavior details are missing.

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

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

The description is a single focused sentence with no extraneous information. It efficiently communicates the tool's purpose and output.

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 4 parameters, no output schema, and no annotations, the description is adequate but incomplete. It mentions return fields but lacks details on response structure, limits, error handling, or advanced search features.

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

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

Schema coverage is 100% with descriptions for all 4 parameters. The description adds context about what the tool returns (award amounts, PIs, etc.) but does not enhance understanding of the parameters beyond what the schema already provides. Baseline 3 is appropriate.

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

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

The description clearly states the verb ('Search'), the specific resource ('NIH research grants'), and the database ('NIH Reporter'). It also lists returned fields (award amounts, PIs, organizations, abstracts), which distinguishes it from sibling tools about genetic variants, protein expression, and WHO health.

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

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

The description implies usage for searching NIH grants but provides no explicit guidance on when to use versus alternatives (e.g., when to prefer this over other tools). There is no mention of prerequisites, restrictions, or when not to use.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns data (RNA expression levels) and implies a read-only operation, but does not mention any restrictions, permissions, or potential side effects. This is adequate but not comprehensive.

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?

Two sentences with no wasted words. The information is front-loaded and essential.

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

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

For a simple data retrieval tool with two fully described parameters, the description is fairly complete. It explains the source and output type. Could be slightly improved by noting the data format, but it is sufficient for an agent to understand the basic behavior.

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

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

Schema coverage is 100% with both parameters described. The description adds context about tissue and brain-regional levels but does not significantly augment the parameter meanings beyond what the schema already provides.

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

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

The description clearly states it retrieves protein/gene expression data from the Human Protein Atlas and specifies it returns tissue-specific and brain-regional RNA expression levels. It distinguishes itself from sibling tools which are about genetic variants, NIH grants, and WHO health data.

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

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

No guidance on when to use this tool versus alternatives. Sibling tools are distinct but no explicit 'when-to-use' or 'when-not-to-use' instructions are provided.

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

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

No annotations provided, so the description carries full burden. It does not disclose behavioral traits such as whether the operation is read-only, destructive, or has rate limits. The description implies a read operation, but this is not explicitly stated.

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?

Two sentences, no extraneous words, but the phrase 'and other health indicators' is vague and adds little value. Could be more concise by listing a few examples and then implying more. Adequate but not excellent.

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

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

Given there is no output schema, the description should explain the return format or structure. It does not. Additionally, no details on pagination, error handling, or data freshness. For a simple data retrieval tool, it is incomplete.

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

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

Schema coverage is 100%, but the description adds value by providing examples for country (ISO3 codes) and note that indicator can be a code or search term. The default values are also mentioned implicitly (e.g., WHOSIS_000001 for life expectancy). This aids understanding beyond schema definitions.

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

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

The description clearly states the tool retrieves WHO Global Health Observatory data and lists specific indicators (life expectancy, obesity rates, etc.), providing a specific verb and resource. However, it does not differentiate from sibling tools, which are in different domains (genetics, grants, protein), so the lack of differentiation is not critical but still a minor gap.

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 on when to use this tool vs alternatives. The siblings are unrelated, but the description could benefit from stating it is for WHO health indicators only. Implicit usage is clear from the domain, but no exclusions or context for when not to use it.

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