Health Data

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

With no annotations, the description carries the full burden. It discloses that the tool returns clinical significance, conditions, and review status, but lacks details on pagination, error handling, rate limits, or idempotence. The behavioral profile is adequately outlined but not exhaustive.

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 concise sentence of 16 words that front-loads the action and purpose. Every word is meaningful, with no redundancy or filler.

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?

While the description gives a high-level overview of return content, it lacks explicit structure details (e.g., list format, fields per variant). Given no output schema, more detail would improve completeness, but the description is adequate for 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 coverage is 100% with all parameters described in the schema. The description adds minimal additional meaning beyond the schema, merely reiterating that the tool provides clinical significance, etc. 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?

Description clearly states the tool searches ClinVar for genetic variants associated with a gene, specifying the verb (search), resource (ClinVar variants), and data retrieved (clinical significance, conditions, review status). It is distinct from sibling tools like get_nih_grants, which are unrelated.

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

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

Usage context is implied by the description (use when needing ClinVar variant data), but no explicit guidance is given on when to use this tool versus alternatives, nor are any prerequisites or exclusions mentioned.

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

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

No annotations are provided, so the description must convey behavioral traits. It states 'Search' and 'Returns', but fails to disclose if the operation is read-only, requires authentication, has rate limits, or pagination behavior. Only a minimal behavioral sketch is given.

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 two efficient sentences with no wasted words. However, it could be more structured (e.g., separating purpose from return value details) without adding length.

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 too minimal. Missing guidance on usage, behavioral context, and parameter details beyond schema. Considerable gaps remain for an agent to correctly invoke the tool.

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% (all 4 parameters have descriptions), so the baseline is 3. The description adds no additional meaning beyond what the schema already provides, such as clarifying default behaviors or constraints like the max limit of 25.

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 specifies the verb 'Search' and resource 'NIH research grants' from the 'NIH Reporter database', and lists return fields (award amounts, PIs, organizations, abstracts). This clearly distinguishes it from sibling tools like get_genetic_variants, which target different data sources.

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. It does not specify prerequisites, limitations, or when not to use. For a search tool with clear siblings, explicit usage context is expected.

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 the burden. It explains the return type (tissue-specific and brain-regional RNA expression) but does not disclose read-only nature, rate limits, or other behavioral traits. Adequate but minimal.

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?

Single sentence that is front-loaded and contains no extraneous words. Every part 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 no output schema and simple parameters, the description is adequate but could be improved by briefly indicating the output format (e.g., list of values, single value). It covers the basic use case but lacks depth.

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

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

Schema description coverage is 100%, so the schema already documents the two parameters. The description adds marginal context by stating the nature of returned data (tissue-specific and brain-regional), but does not significantly enhance parameter meaning.

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, specifying tissue-specific and brain-regional RNA expression. This verb+resource combination is specific and distinguishes it from sibling tools like get_genetic_variants.

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 versus alternatives. Usage is implied for expression data retrieval, but there is no mention of when not to use it or alternative tools for different types of queries.

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

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

No annotations are provided, so the description must disclose behavioral traits. It does not mention that the tool is read-only, any authentication or rate limits, or data recency. The description only lists example data points, missing key 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 sentence of 21 words, efficiently summarizing the tool's purpose. No redundant or filler content.

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

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

For a tool with 3 parameters and no output schema, the description is minimally complete. It explains what data can be retrieved but omits output format, pagination, or any limitations. Given the lack of annotations, more context would be beneficial.

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%, so the description does not need to add much. It provides example indicators (life expectancy, obesity) which adds slight context beyond the schema's indicator parameter description, but no new parameter-level details.

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 health indicators (life expectancy, obesity, etc.). This verb-resource combination is distinct from sibling tools (genetic variants, NIH grants, protein expression).

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 does not explicitly state when to use this tool or provide alternatives. However, the domain differs from siblings, reducing confusion. The parameter descriptions hint at usage (ISO3 codes, indicator codes), but no direct guidance is given.

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