Fonteum — Healthcare Provider Data (Hosted)

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

No annotations are provided, but the description fully discloses the tool's behavior: it is read-only, returns two layers with source and dates, warns about limitations, and lists specific exclusion lists. No contradictions.

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 well-structured and front-loaded with the purpose. Each sentence adds value, though it is somewhat lengthy. Could be slightly more concise without losing clarity.

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

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

Despite no output schema, the description explains the two layers of results and the provenance contract. It covers all necessary context for an agent to understand the tool's functionality and limitations.

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 already describes the single parameter 'npi' as a 10-digit string requiring Luhn validation. The description does not add additional semantic meaning beyond what the schema provides, so baseline score of 3 applies.

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 is an integrity check for a healthcare provider by NPI, with two distinct layers (EXCLUDED ANYWHERE and COMPROMISED ANYWHERE). It stands out from sibling tools that deal with datasets, provider info, sources, and search.

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 explicitly notes it is a screening aid only, requiring re-confirmation against primary sources, and that absence of a match is not a guarantee. This provides clear context for when to use the tool, though it could offer more direct comparison to alternative tools.

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

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

No annotations provided. Description explicitly states 'Read-only static data', which adds transparency beyond an empty annotations block. However, it does not mention any permissions, caching, or data staleness considerations.

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 with clear enumeration of returned items. Front-loaded with verb 'Return' and specific nouns. No wasted words.

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 no parameters, no output schema, and no annotations, the description adequately lists the contents of the return value. Missing details on output format or what the provenance contract spec entails, but still sufficient for basic usage.

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

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

No parameters. Baseline for 0 parameters is 4 per guidelines. Description does not add parameter info since there are none.

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 specifies the tool returns Fonteum methodology metadata including version, URL, provenance contract spec (14 fields), and 41 source families. It uses specific nouns and distinguishable from sibling tools that seem to do checks or 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?

No explicit guidance on when to use this vs alternatives. However, the purpose is clear enough that an agent would infer it's for retrieving static overview metadata. Does not state when not to use or provide alternatives.

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. Description states 'Read-only' and mentions return format (record with provenance contract). Lacks details on error handling or restrictions, but adequate for simple read operation.

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 redundancy, front-loaded key information (action, identifier, output). Efficient use of words.

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 lookup tool with one parameter and read-only semantics, description covers purpose, input, output type, and safety. No output schema, but return value is described. Minor gaps: no mention of error conditions or explanation of 'fourteen-field provenance contract'.

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% (single param with description including Luhn validation). Description adds '10-digit National Provider Identifier' which reinforces but doesn't significantly extend schema.

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

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

Explicitly states action (look up), resource (healthcare provider), identifier (NPI), and source (CMS NPPES NPI Registry). Distinguishes from sibling 'fonteum_search_provider' which is for searching multiple results.

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

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

Clearly implies use case when you have a specific NPI. No explicit 'when not to use' or alternatives, but context with sibling tools provides differentiation.

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

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

With no annotations provided, the description carries the full burden. It declares the operation as read-only and lists the fields returned. No additional behavioral traits (e.g., rate limits, authentication) are disclosed, but for a read-only list tool, the description is satisfactory.

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, directly states the purpose and output fields, with no extraneous information. Fully front-loaded.

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 parameters and no output schema, the description provides a clear overview of the return content. However, it does not mention whether the list is exhaustive, paginated, or ordered, which could be relevant for completeness.

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 zero parameters and 100% coverage. The description adds value by explaining what the output contains (authority, tier, etc.), which is beyond the schema. Baseline for 0 parameters is 4.

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 ('List') and the resource ('federal public-record source families'), and specifies the type of information returned (authority, tier, refresh cadence, official URL). It distinguishes from sibling tools which deal with exclusions, datasets, or provider records.

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 the tool is for retrieving source family information, but does not explicitly state when to use it versus alternatives (e.g., when you need provider data, use sibling tools). No exclusionary criteria are given.

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

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

With no annotations, the description fully carries the burden. It discloses the data source (CMS NPPES, filtered to Fonteum scope), pagination (up to 100 records, default 25), and the presence of 14-field provenance. This is good behavioral context, though it doesn't cover authentication or rate limits.

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, front-loaded with core purpose, no redundant words. Every sentence adds value: purpose, constraints, and output characteristics. Highly concise and well-structured.

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 4 well-documented parameters, the description provides sufficient context: source, filtered scope, max results, and provenance. Missing details about output structure or pagination beyond limit are minor given no output schema, but overall adequate.

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 detailed parameter descriptions. The description adds minimal extra meaning beyond 'search by vertical + state' and the limit context. Baseline 3 is appropriate as the schema does most of the work.

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 uses a specific verb 'Search' with clear resources 'healthcare providers by vertical + state', and differentiates the tool from siblings like 'get_provider' (single lookup) and 'list_sources' by specifying the source (CMS NPPES) and filtered scope. This is a clear, distinct purpose.

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 states the primary use case (search by vertical and state) but does not explicitly mention when to use alternatives or exclusions. The usage is implied, but no explicit guidance is given for choosing between this tool and siblings.

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