GPH Intelligence — Healthcare Service Provider Finder

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

Annotations already indicate read-only, non-open-world, and idempotent behavior. The description adds value by specifying the scope of data returned (e.g., description, services, contact information, quality score, reviews), which isn't covered by annotations. It doesn't disclose additional traits like rate limits or authentication needs, but with annotations providing safety and idempotency hints, the description adds useful context without contradiction.

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 lists the key data points retrieved. It's front-loaded with the main action and resource, followed by specific details, with no redundant or unnecessary information. Every part of the sentence contributes to understanding the tool's purpose.

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

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

Given the tool's low complexity (1 required parameter), rich annotations (read-only, non-open-world, idempotent), and no output schema, the description is reasonably complete. It specifies the data returned, which compensates for the lack of output schema. However, it could be more comprehensive by addressing sibling tool differentiation or potential limitations, but it's adequate for the context.

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

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

The input schema has 100% description coverage, with the 'slug' parameter fully documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema, such as format examples or constraints. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to.

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 full profile details') and resource ('healthcare service provider'), specifying what information is retrieved (description, services, contact information, quality score, reviews). It distinguishes from sibling tools like 'search_providers' by focusing on a single provider's details rather than searching or matching. However, it doesn't explicitly contrast with 'match_practice', leaving some ambiguity.

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

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

The description implies usage when detailed information about a specific provider is needed, but it doesn't explicitly state when to use this tool versus alternatives like 'search_providers' or 'match_practice'. No guidance is provided on prerequisites, exclusions, or specific scenarios where this tool is preferred, leaving usage context somewhat inferred rather than clearly defined.

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?

Annotations indicate read-only, non-open-world, and idempotent operations, which the description doesn't contradict. The description adds valuable behavioral context by specifying it 'Returns ranked matches with quality scores,' explaining the output format and ranking behavior beyond what annotations provide. It doesn't mention rate limits or auth needs, but annotations cover core safety aspects.

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 front-loads the purpose and key criteria, with no wasted words. It efficiently communicates the tool's function and output, making it easy for an agent to parse and apply.

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, 100% schema coverage, and annotations covering safety, the description is reasonably complete. It specifies the output format ('ranked matches with quality scores'), which compensates for the lack of an output schema. However, it could better address usage relative to siblings or provide more behavioral details like match algorithm 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 100%, so all parameters are documented in the schema. The description lists key parameters (specialty, size, location, EHR system, budget) but doesn't add meaning beyond the schema's descriptions, such as explaining interactions between parameters or usage nuances. Baseline 3 is appropriate given high schema coverage.

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

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

The description clearly states the specific action ('Find the best healthcare service providers'), target resource ('for a medical practice'), and key criteria ('based on specialty, size, location, EHR system, and budget'). It distinguishes from sibling tools by specifying it returns 'ranked matches with quality scores' rather than detailed provider information or general searches.

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

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

The description implies usage context through the criteria listed, suggesting this tool is for matching providers to practice needs. However, it doesn't explicitly state when to use this versus alternatives like 'search_providers' or 'get_provider_detail', nor does it provide exclusion guidance or prerequisites for effective 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?

Annotations already declare readOnlyHint=true, openWorldHint=false, and idempotentHint=true. The description adds valuable behavioral context beyond annotations by specifying that results are 'paginated' and include 'quality scores and contact information', which helps the agent understand output format and limitations.

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 efficiently convey purpose, search criteria, and return format with zero waste. The description is front-loaded with the core functionality 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.

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

For a search tool with comprehensive annotations (read-only, closed-world, idempotent) and full schema coverage, the description provides adequate context by explaining pagination and return data. However, without an output schema, it could benefit from more detail on result structure or error conditions, though not strictly required.

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

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

Schema description coverage is 100%, so the schema fully documents all 6 parameters. The description mentions search dimensions ('category, location, and quality rating') that map to parameters but doesn't add syntax, format, or semantic details beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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

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

The description clearly states the action ('Search for healthcare service providers'), the resource ('providers'), and key search dimensions ('by category, location, and quality rating'). It distinguishes from sibling tools by focusing on search functionality rather than retrieving details (get_provider_detail) or matching practices (match_practice).

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

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

The description implies usage context through the search parameters mentioned, but doesn't explicitly state when to use this tool versus alternatives like get_provider_detail or match_practice. No guidance on prerequisites, exclusions, or specific scenarios is provided.

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