renacer-psicologico

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

With no annotations, the description carries the full burden. It accurately describes the returned content (information and link) and implies a read-only operation. However, it does not disclose any response format, potential variant, or limitations (e.g., availability). For a simple informational tool, this is adequate but not richly transparent.

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?

A single sentence that is clear, front-loaded, and contains no filler. Every word 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?

For a tool with no parameters, no output schema, and low complexity, the description is sufficient. It tells the user exactly what to expect (information and link) without needing to explain return values or side effects. A small gap is that it doesn't mention whether the link is external or in-app, but this is minor.

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?

There are zero parameters, so the baseline is 4. The description adds value by explaining what the returned information contains (booking link) but doesn't need to clarify semantics for nonexistent params.

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's function: returning information and a booking link for a free 25-minute initial assessment. The verb 'Devuelve' (returns) is specific, and the resource is well-defined, distinguishing it from siblings about credentials, services, and articles.

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 a user needs details on the free initial assessment, but it provides no explicit guidance on when to choose this tool over siblings. There are no exclusions or alternative tool mentions. It is sufficient but lacks explicit context.

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 burden of behavioral disclosure. It discloses that the tool returns verifiable data, which implies a read-only operation, but does not elaborate on authorization, performance, or any side effects. This is adequate for a simple getter but not rich in 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.

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

The description is a single, well-structured sentence that conveys the tool's purpose and data content without unnecessary words. It is concise and front-loaded with the action and resource.

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 simplicity (no parameters, no output schema), the description covers the key aspects of what is returned and mentions who performs the initial assessment. It might be slightly more explicit about the format or structure of the returned data, but overall it is complete enough for a basic data retrieval 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?

The tool has zero parameters, so the baseline is 4. The description adds meaning by detailing the content of the returned data, which is useful even though there are no parameters to document.

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 'Devuelve' (returns) and the resource 'datos verificables de los profesionales del equipo', listing specific data elements like colegiación, enfoques, modalidad, and who performs the initial assessment. This distinguishes it from sibling tools that focus on assessment info, services/prices, or articles.

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 professional credential data is needed, but it does not explicitly mention when not to use it or alternative tools. The sibling list suggests there are alternatives, but no direct comparison is made, so guidance is only implicit.

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 burden of disclosing behavior. It clearly indicates a read-like operation ('Devuelve'), but does not mention side effects, authentication requirements, rate limits, or response structure beyond the basic data included. For a simple retrieval tool, this is adequate but not exceptional.

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 that clearly states the tool's purpose and output. Every word adds value, and there is no redundancy or irrelevant detail.

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 simplicity (no parameters, no output schema), the description adequately covers what the tool returns: services, prices, and URLs. It does not detail the exact response format or pagination, but for a straightforward list endpoint, this is sufficient. It could be more explicit about the data type, but overall it is complete for the intended use.

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 tool has zero parameters, so the schema already fully defines the input. The baseline for 0 params is 4, and the description does not need to add parameter-level detail. It effectively communicates what the output contains, which compensates for the lack of an output 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?

The description clearly states the tool's purpose: it returns online psychology services from Renacer Psicológico, including prices and URLs. The verb 'Devuelve' (returns) is specific, and the resource is well-defined, distinguishing it from sibling tools like get_free_assessment_info or search_clinical_articles.

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 a user needs the list of services and prices, but does not provide explicit guidance on when to use this tool versus alternatives. No exclusions or preferred scenarios are mentioned, so it relies on the user to infer context from the purpose.

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 must carry the full burden of behavioral disclosure. It only says the tool 'locates' a hub, but does not explain what is returned (URL, title, list?), any pagination, authorizations, or error behavior. It adds no meaningful contextual detail beyond the action.

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 that packs essential information clearly. It is front-loaded with the verb and resource, with 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?

Given the low complexity (one parameter, no output schema, no annotations), the description provides a minimal viable level of completeness: it states what the tool does. However, the lack of return-value details and the inconsistency between the tool name (articles) and description (hub) leave gaps in pre-invocation understanding.

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 schema has 100% coverage on the 'topic' parameter, including examples of mental health topics. The description itself doesn't add extra parameter information beyond what the schema already states, so a baseline of 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 uses a specific verb 'localiza' (locates) and a specific resource: the thematic hub of the clinical blog that best fits a mental health topic. It clearly distinguishes from sibling tools focused on assessment info, credentials, and services/prices.

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 finding a blog hub relevant to a mental health topic, but it does not explicitly state when to use this tool versus the siblings (e.g., for content discovery vs. factual info). Usage context is implied but not elaborated.

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