Autoridad Digital — GEO

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

The annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds a concrete output contract ('Devuelve título, fecha, extracto y URL') and a precise content scope, which goes beyond the annotations. It does not discuss empty-result behavior or search semantics, but for a simple read-only search this is acceptable.

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 sentences with no filler. It is front-loaded with the action and resource, immediately clarifies the topical scope, and closes with the output shape. The topic enumeration is long but purposeful, since it defines the tool's search domain.

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 read-only search tool with only two parameters, the description is complete enough for correct invocation. The schema covers parameters and constraints, annotations cover safety, and the description provides the output fields despite there being no output schema. The only missing piece, explicit sibling routing, is minor because the resource and scope are already unambiguous.

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%, and the schema already explains both 'tema' and 'limite' with examples and constraints. The description's topic list indirectly informs 'tema', but it adds little semantic value beyond what the schema provides. With high schema coverage, 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?

The description opens with a specific action and resource: 'Busca en el blog de Autoridad Digital artículos...' and it enumerates the exact topical coverage. It also states what the tool returns, which makes its purpose unmistakable. The sibling tools (comparar_webs, consultar_glosario, escanear_geo) are clearly different in scope, so the tool is easy to distinguish.

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 intended use is implied by 'Busca en el blog de Autoridad Digital artículos...', so an agent can infer it should be used when the user wants blog articles on SEO, GEO, schema, etc. However, there is no explicit when-to-use guidance, no exclusions, and no mention of when a sibling tool would be more appropriate.

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?

Beyond the provided readOnlyHint and idempotentHint already carried by annotations, the description adds genuinely useful behavioral details: each non-cached domain consumes one scan unit, and slow sites are omitted with an indicator of which domain failed to be analyzed. This is exactly the type of rate-limit and partial-result disclosure that helps an agent.

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 cover what the tool does, which types of output it gives, why it is used, quota behavior, and inactivity timeout handling. Nothing is wasted and key information is up front.

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 tool is moderately simple, has a single parameter, and has an output schema available. The description provides the use case, the object being measured, the relevant metrics, the quota-consuming behavior, and the graceful degradation strategy. Everything an agent needs to decide and invoke the tool is present.

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%, and the description essentially repeats what the schema already states: list of 2 to 4 public domains or URLs. It does not add extra nuance such as URL format, whether protocol matters, or how domain matching works, so the baseline three 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 opens with a concrete verb-and-resource statement, then lists the exact comparison outputs: puntuación, nota, bots de IA bloqueados, llms.txt and problemas. This makes the tool's purpose unmistakable and clearly separates it from the unrelated sibling tools.

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 states the intended purpose: positioning a brand against competitors in generative-engine visibility. It does not spell out when not to use this tool or name alternatives, but the sibling tools are so topically different that the context is sufficient.

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 declare readOnlyHint=true and idempotentHint=true, which the description does not contradict. The description adds a useful behavioral detail: if the term doesn't exist, it returns the complete list. This is beyond annotations and helps the agent anticipate fallback behavior, even though it doesn't mention exact error format or list length.

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 concise sentence that packs purpose, scope, and fallback behavior. The key information is front-loaded. It could be considered slightly dense but is efficient with no waste.

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 read-only lookup with a single parameter and no output schema, the description covers the core behavior. The fallback list is a nice touch. Minor gaps: doesn't specify if partial matches are supported or exact matching only, but given the simplicity, it is adequately complete.

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 covers 100% of the parameter with a description including examples. The description adds no additional parameter semantics beyond that. Since coverage is high, baseline 3 applies; the description provides no extra meaning but the schema does the job.

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 defines SEO/GEO/AEO terms from a specific glossary, listing example terms. It distinguishes this from sibling tools like 'buscar_articulos' or 'scannear_geo' by focusing on glossary definitions. The verb 'consultar' with resource 'glosario' is specific and unambiguous.

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 you need a definition of a term from the glossary. It does not explicitly mention alternatives, but sibling tools are clearly different (search articles, compare websites, scan GEO). No explicit 'when not to use' is given, but the context of glossary lookup is implicit and adequate.

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 useful behavioral details beyond the annotations: it limits to public URLs, enforces 5 scans/minute, caches results for 24h, and returns a 0-100 score plus corrections. The readOnly and idempotent annotations already cover the safety profile.

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 purpose is front-loaded, followed by a compact list of checkscares, then output format, then constraints. It is slightly dense as one long sentence, but every sentence adds relevant information.

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 single-parameter analysis tool with an output schema, the description covers purpose, checked dimensions, output format, rate limits, and caching reuse. Nothing essential for correct invocation is missing.

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 is a single url parameter and the schema already documents its type, bounds, and example. The description only reinforces that the URL must be public, which adds minor nuance but does not substantially extend the 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 states a specific action and resource: analyzing whether a web page can be read and cited by AI enginescars, and enumerates concrete checks (robots.txt, bots, structured data, extractability). This is clearly distinct from the sibling tools.

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 gives clear usage context: analyzing AI-readability/GEO of a public URL. It also adds constraints (public URLs only, rate limit, 24h cache), though it does not explicitly name alternatives or when-not-to-use conditions.

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 and idempotentHint, so the read-only nature is covered. The description adds extra context that the data is the canonical mirror of the website and enumerates the catalog scope (feature detail, suitability, plans, price, commitment, VAT, FAQ, contact), which goes beyond the structured hints.

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 front-loaded and the two sentences split the global catalog scope from the conditional parameter behavior. The slug list is redundant with the enum, making it slightly longer than necessary, but overall it is well-structured and does not waste 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 single optional parameter with no output schema, the description fully covers what the tool returns: content categories, pricing, terms, FAQ, and how to get a single-service detail. The read-only and idempotent annotations close the remaining 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?

The schema has 100% description coverage and none of the enum values plus the 'omisión' behavior. The tool description adds its same slug list but does not introduce new semantics beyond what the schema already communicates, so it stays at the 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 clearly states it is a catalog of services, what content it provides (inclusions, target profile, prices, minimum commitment, FAQ, contact), and that passing one servicio shows its detail. This makes it unmistakably distinct from the siblings, which cover articles, comparisons, glossary, and GEO scans.

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 tells the agent when to pass the optional parameter and what the omission returns ('Catálogo' vs 'detallado'), which is useful operational guidance. It does not explicitly name alternatives or state when not to use this tool, but the use case is clear and no exclusions are needed.

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