2ds · Visibilidad en IA

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

The annotations already mark the tool read-only and open-world, and the description adds meaningful behavioral context: it analyzes the homepage, inspects multiple external signals, returns a score with concrete improvements, and explicitly delimits its scope. This goes well beyond the structured annotation information.

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?

Three sentences carry the full definition with no filler: the action and resource come first, followed by the specific checks, then the output, and finally a valuable negative scope. Every sentence earns its place and the structure is easy to scan.

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 is sufficiently complete for a single-parameter, read-only tool: it lists inputs, checks, and output type ('puntuación y mejoras concretas'). With no output schema, a slightly more detailed description of the score format would be ideal, but the current text is adequate for safe invocation.

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 already fully documents the single parameter 'web' with an example and type, so schema coverage is 100%. The description adds a small amount of context (public homepage) but does not materially improve on the schema's parameter explanation, warranting the baseline score.

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 opens with a specific verb and resource ('Analiza la portada de cualquier web pública') and enumerates the concrete checks performed: robots.txt, JavaScript-free rendering, schema.org, sitemap, and llms.txt. It also clarifies what the tool does not measure, making it clearly distinguishable from sibling tools that handle content pages or diagnostics.

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 gives a clear context for use ('cualquier web pública') and explicitly states an exclusion: it does not measure whether the web appears in assistant responses. However, it does not name sibling tools or provide explicit when-to-use versus when-not-to-use guidance; the differentiation is implicit rather than stated.

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 convey read-only behavior and a closed-world hint. The description adds that the content is answers to common questions about 2ds, but does not describe response format or that no input is required. With annotations covering the safety profile, this is acceptable but not rich.

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 one short sentence with no filler or redundancy. It front-loads the resource scope and purpose efficiently.

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 zero-parameter, read-only FAQ tool, the description is largely complete: an agent can select it correctly and invoke it without inputs. A minor gap is that it does not explicitly state what the response looks like, but no complex output schema is present and the purpose is simple.

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 is empty, so there are no parameter semantics to clarify. The description's mention of '2ds' and 'dudas habituales' provides the only scoping context, which is sufficient; the score reflects the zero-parameter baseline.

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 states the tool returns answers to common questions about 2ds, which is a clear resource and function. It is not a tautology of the title and is distinguishable from sibling tools by its FAQ-focused purpose, though it does not explicitly differentiate itself.

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 phrase 'dudas habituales' implies the tool is for common questions about 2ds, so usage context is inferable. However, there is no explicit guidance about when to use it versus sibling tools such as 'servicios' or 'solicitar_diagnostico'.

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, so the agent knows this is a safe read operation. The description adds only the freshness detail 'precios actuales' and does not contradict the annotations, but it provides no further behavioral context such as response format or update semantics.

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 short sentence with no filler, and the key scope ('servicios de 2ds') and price freshness are front-loaded. It is appropriately sized for a simple no-argument catalog tool.

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 no-argument, read-only catalog tool, the description plus annotations are sufficient for correct invocation. The only minor gap is that '2ds' is not expanded, but the title and sibling context make the purpose clear enough.

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 there is no parameter documentation burden for the description. The schema fully covers the empty parameter set, and the description does not need to compensate for missing parameter 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 names the resource ('Servicios de 2ds') and the data ('precios actuales'), so an agent can infer this is a catalog/list tool. It lacks an explicit action verb like 'list' or 'show', but the meaning is clear enough and distinguishable from the sibling tools by topic.

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 gives no guidance about when to use this tool instead of siblings such as 'comprobar_visibilidad_ia', 'preguntas_frecuentes', or 'solicitar_diagnostico'. Any usage intent must be inferred from the title and description alone.

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?

The readOnlyHint annotation already declares this as a safe read operation, lowering the bar. The description adds content scope but no extra behavioral detail such as whether it returns contact information, hours, or pricing. It does not contradict the annotations.

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?

One short, well-formed sentence that front-loads the key topics. Every word earns its place with no clutter or repetition.

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 zero-parameter, no-output-schema informational tool, the description adequately covers what the agent can expect: company identity, location, and contact/booking actions. It is sufficient for safe invocation.

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 no parameter information, which is fine because there is nothing for the agent to configure.

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 what the tool covers: who 2ds is, where it works, and how to hire or book an appointment. This distinguishes it from siblings like preguntas_frecuentes (FAQs) and servicios (services), though it lacks an explicit verb like 'retrieve' or 'show'.

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 content scope implies when to use it (when a user asks about the company, location, or booking), but there is no explicit guidance about when not to use it or how it differs from solicitar_diagnostico, which might also involve appointments or contact.

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?

The description adds meaningful behavioral context beyond the annotations: it discloses that data is sent to 2ds, that the diagnostic is free, and that consent must be confirmed. This complements the openWorldHint and idempotentHint annotations without contradicting them.

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 concise sentences: the first states the core purpose, the second provides the prerequisite action. No filler or unnecessary repetition.

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 request-style tool with 6 parameters and no output schema, the description gives enough context to call it correctly: what to do, what to confirm, and what data is used. It could briefly mention what happens after the request, but this is not a critical gap.

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 parameters are already fully documented. The description adds contextual framing around 'datos' and privacy acceptance but does not need to repeat parameter 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 action: request a free AI-assistant visibility diagnosis from 2ds for the user's business. It uses a specific verb and resource, though it does not explicitly distinguish itself from the sibling tool comprobar_visibilidad_ia.

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?

It explicitly tells the agent to confirm the user's data and consent before calling, which is strong usage guidance. It does not mention when the sibling comprobar_visibilidad_ia should be used instead, so alternatives are not covered.

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