MCP humanista.digital

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

With no annotations provided, the description carries the transparency burden. It discloses that the tool combines two article systems and that each result indicates its source ('Cada resultado indica su 'fuente''), which are useful non-obvious behaviors. However, it does not mention any side effects or additional behavioral details, but for a read-only search tool this is reasonably comprehensive.

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 front-loads the core action and immediately states the key context. Every phrase adds value without being verbose.

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?

With no output schema, the description should clarify return values. It mentions each result includes its source, but it omits ordering, pagination, per-source limit behavior, and the structure of the result set. It provides a partial picture, making it minimally 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 description coverage is only 33% (only 'idioma' has a description). The tool description does not compensate: it does not explain 'query' or 'limit_por_fuente' semantics, nor how they interact with the dual-system combination. This leaves a significant gap in parameter understanding.

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: searching articles in the Radar section of humanista.digital, and specifies the dual-system behavior (Spanish 'articulos' and English 'articles'). This distinct resource differentiates it from sibling tools like buscar_noticias_observatorio or buscar_entrevistas.

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?

Usage context is implied: it is for Radar articles, but there is no explicit guidance on when to choose this over alternatives like buscar_todo or other search tools. No when-to-use or when-not-to-use scenarios are provided, though the name provides a clear hint.

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 does disclose that only published entities are returned ('publicadas'), which is useful, but it omits other behavioral traits such as default pagination, how filters combine, result ordering, or response format. For a search tool with 8 parameters, this leaves significant uncertainty.

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 sentence that immediately states the action, resource, and scope. Every word earns its place, and there is no redundancy or irrelevant detail. This is an exemplary level of conciseness.

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 complexity (8 optional parameters, no output schema, no annotations), the description is too sparse to be complete. It provides no information about filter usage, pagination, or the response structure. For an agent to use this tool effectively, more context is needed.

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 only 13% (only 'tipo' has a description). The tool description does not compensate by explaining any of the 8 parameters, such as what 'query', 'pais', or 'tecnica' do. Parameters like 'limit' and 'offset' are self-explanatory, but most lack semantic guidance, making this a weak point.

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: 'Busca entidades' (search entities) and specifies the types (institutions, companies, collectives) and the source directory. This distinguishes it from sibling search tools like buscar_profesionales and buscar_proyectos, making the purpose 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?

Usage is implied by the description: when you need to search entities, use this tool. However, there is no explicit guidance on when to prefer it over alternatives like buscar_todo, nor any mention of using obtener_entidad for retrieving a specific entity. The lack of exclusions or alternative references keeps it at an implied level.

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 of disclosing behavior. It only states the basic action of searching interviews without any details on result format, pagination, filtering behavior, or what 'Radar editorial' implies. This is insufficient for an agent to anticipate the tool's behavior.

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, clear sentence that is front-loaded with the core purpose. It is concise and free of fluff, though it could add more useful details without becoming bloated. It is appropriately sized for a basic search 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?

Given the tool's complexity (6 optional parameters, no output schema, no annotations), the description is too thin. It does not explain what results will look like, any filtering options, or how the search behaves, making it incomplete for an agent selecting the tool for a specific task.

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 only 17% (only 'idioma' is described in the schema), and the tool description mentions no parameters at all. The description fails to compensate for the many undocumented parameters (limit, query, offset, tecnica, categoria), leaving the agent to rely solely on parameter names.

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: searching for interviews published in the editorial Radar of humanista.digital. The verb 'busca' and resource 'entrevistas' are specific, and it is clearly differentiated from sibling tools like buscar_articulos_radar or buscar_eventos.

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 clear context about the domain (Radar editorial) but does not explicitly state when to choose this tool over alternatives. Usage is implied by the tool name and sibling list, but there are no explicit exclusions or alternative mentions.

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 carries the full burden of behavioral disclosure. It does mention that only 'públicos y publicados' events are included, which is a useful constraint, but it fails to disclose other important traits such as read-only nature, pagination behavior, sorting, or what fields are returned.

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, front-loaded sentence with no wasted words. It efficiently conveys the core purpose and scope. However, it is somewhat under-specified, which slightly reduces the score since brevity is not a substitute for essential 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?

Given the tool's complexity (10 optional parameters, multiple enums, no output schema) and the lack of annotations, the description is not complete enough to use the tool effectively. It lacks detail on query behavior, pagination, result structure, and how filters interact, making it insufficient for an agent to invoke correctly.

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 10 parameters but only 30% have descriptions. The description does not explain any parameter (like pais, query, modalidad, or offset) and does not compensate for the low schema coverage. The parenthetical event types are not mapped to the 'tipo' enum, so no additional meaning is provided.

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 'Busca eventos públicos y publicados' with a specific verb ('Busca') and resource ('eventos'), plus a domain scope ('humanidades digitales') and examples of event types. It distinguishes from sibling tools by focusing on events, though it does not explicitly name alternatives.

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 tool versus sibling search tools like buscar_proyectos or obtener_evento. The only context is the domain and event types, but there is no mention of exclusions, prerequisites, or alternative tools, leaving the usage entirely implied.

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 are provided, so the description carries the full burden. It only says 'Busca noticias/entradas agregadas' without explaining the extent of the search, whether it crosses all listed categories, or any constraints like pagination, defaults, or required inputs. It also doesn't clarify the relationship to other search tools.

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 sentence that immediately states the action and resource, with no filler. However, the parenthetical list is somewhat lengthy and could be reduced without losing core meaning.

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 9 parameters, no output schema, and no annotations, this description is incomplete. It doesn't mention the available filters, pagination behavior, or how it differs from the broader 'buscar_todo' tool. Given the complexity, much more contextual detail is needed.

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 only 22% (2 out of 9 params). The description does not explain the meaning of key parameters like 'pais', 'campo', 'tecnica', 'query', 'limit', or 'offset'. It hints at content types that map to 'tipo_actividad', but this is insufficient compensation for the low 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 uses the specific verb 'Busca' and clearly identifies the resource as 'noticias/entradas agregadas en el Observatorio de humanista.digital', with examples of content types. It is clear in isolation but does not distinguish from sibling tools like buscar_proyectos or buscar_eventos, which may overlap in coverage.

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 guidance is provided about when to use this tool versus the many sibling search tools (e.g., buscar_proyectos, buscar_eventos, buscar_todo). The description does not state appropriate contexts, exclusions, or 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 are provided, so the description carries the full burden. It indicates a search/read operation and enumerates filter dimensions, but it does not disclose pagination behavior (limit/offset), result structure, or how filters interact with each other. The description adds some context about the directory but lacks deeper behavioral details.

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 short, front-loaded sentences. It immediately conveys the verb and resource, then lists filter categories. No redundant or filler content.

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?

With no output schema and 8 parameters, the description covers the core purpose and filter categories, but omits pagination details, result format, and edge cases like what happens with no filters. For a search tool, it is adequate but leaves noticeable gaps in 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?

Schema description coverage is 63%, so the description does not need to fully compensate. It restates filter types (país, localidad, idioma, campo, técnica) and introduces 'ERIHS' context, but most parameters already have descriptions in the schema. Parameters like 'limit' and 'offset' are not mentioned in the description, and their semantics are left to inference from names.

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: 'Busca profesionales publicados en el directorio de humanista.digital (personas de humanidades digitales).' It uses a specific verb ('busca'), specifies the resource ('profesionales'), and distinguishes itself from sibling tools by targeting people in the digital humanities directory.

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 provides clear context for when to use the tool: searching for professionals in the humanista.digital directory. It lists filterable attributes (free text, country, locality, language, ERIHS field/technique), giving an idea of use cases, but does not explicitly mention alternatives or exclusions.

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 of behavioral disclosure. It only says 'search projects' without stating whether the operation is read-only, what the response format is, whether pagination applies, or any side effects. The description is purely a purpose statement, not a behavioral disclosure.

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, front-loaded sentence with no fluff. It efficiently states the tool's core purpose. While it lacks critical details, the dimension of conciseness rewards the absence of unnecessary words, and this description earns its place despite being minimal.

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 complexity (9 parameters, no annotations, no output schema), the description is severely incomplete. It does not mention any of the search criteria, result ordering, pagination, or return value shape. An agent would be unable to invoke this tool confidently without external documentation.

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 only 11%, and the description adds nothing about any of the 9 parameters. It fails to compensate for the sparse schema, offering no explanation of 'pais', 'tipo', 'campo', or other filters. The agent cannot understand the meaning or expected format of parameters from the description.

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 ('Busca') and resource ('proyectos publicados en el directorio de humanista.digital'), clearly indicating a search operation for published projects. It distinguishes from sibling tools like 'obtener_proyecto' and other entity-specific searches by its clear focus on projects.

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 guidance is provided on when to use this tool versus alternatives such as 'buscar_todo' or 'obtener_proyecto'. There are no mentions of filtering, result limits, or scenarios where this tool is preferred, leaving the agent to infer usage from the name 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?

With no annotations, the description carries the full burden of behavioral disclosure. It only states the basic search function and does not mention behavior such as filtering by campo/tecnica, pagination (limit/offset), rating threshold (valoracion_minima), or return format. This is minimal but not contradictory.

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 with no filler or redundancy. It is front-loaded with the essential action and resource, making it highly scannable.

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 has 6 parameters, no output schema, and no annotations, the description is too minimal. It fails to provide necessary context about available filters, pagination, or how it differs from related tools, making it difficult for an agent to know how to use it correctly beyond the basic search intent.

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 0%, and the description adds no meaning to any of the 6 parameters. It does not explain the purpose of 'campo', 'tecnica', or 'valoracion_minima', leaving the agent to infer their roles from names alone, which is insufficient for correct invocation.

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 the specific verb 'Busca' (searches) with a clear resource 'reseñas de libros' (book reviews) and mentions the source platform. It distinguishes from sibling tools like obtener_resena (which retrieves a single review) and other buscar_* tools by specifying the content type.

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 usage context is implied by the description: agents should use this tool when searching for book reviews. However, there is no explicit when/when-not guidance or mention of alternatives such as buscar_todo or obtener_resena, leaving some ambiguity.

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 disclosure burden. It states the search intent and content type but does not mention return shape, pagination behavior, ordering, or whether the query parameter is required; the read-only nature is only implied.

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, front-loaded sentence that gives both the action and a concrete example, with no wasted words or redundancy.

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 search tool with no annotations and no output schema, the description provides enough domain context to define what a 'selección' is, but it omits parameter behavior, pagination, and result format. The obvious schema names keep it minimally viable but not 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?

Schema description coverage is 0% and the tool description does not explain the semantics of query, limit, or offset beyond their property names and basic types/ranges. The names are somewhat self-explanatory, but the description does not compensate for the lack of schema documentation.

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 'Busca' (search) with a defined resource 'selecciones publicadas' and provides an example ('Radar #N: señales del mes'), making its purpose unmistakable and distinguishing it from sibling search 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?

The description implies the tool is for searching published newsletter-style selections, but it does not explicitly state when to prefer this over sibling search tools or offer exclusion criteria. The example clarifies the content type but no alternative guidance is 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 carries the transparency burden. It discloses that the tool searches across multiple categories at once, which is a behavioral trait, but it does not explain how results are returned, limit handling, or any other nuances. This is minimal but not misleading.

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 starts with the key concept 'Metabuscador' and lists the search scope. Every word adds value, and there is no redundancy or filler.

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 lack of output schema, annotations, and parameter descriptions, the description should provide more context about result structure or how the limit applies. It covers the basic purpose and scope but leaves significant gaps for an agent trying to predict the tool's behavior.

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 0%, so the description must compensate. It indirectly indicates 'un texto' corresponds to the query parameter, but it completely omits any explanation of 'limite_por_tipo'. With two parameters and one unaddressed, it fails to adequately clarify the tool's inputs.

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 'Metabuscador' that searches a text simultaneously across professionals, entities, projects, events, interviews, and news. This specific verb and resource list effectively distinguishes it from the sibling tools that target individual categories.

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 word 'simultáneamente' implies this tool is for cross-category searches, but there is no explicit guidance on when to prefer it over the individual buscar_* tools or any exclusions. The context of sibling tools makes the use case apparent, but the description does not articulate it directly.

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 are provided, so the description carries the full burden for behavioral disclosure. 'Listar' suggests a read-only operation, but the description does not explicitly state that it is safe/no side effects, nor does it mention any authentication, pagination, or return format details. It only notes that the badges are 'active' (a filtering behavior) but lacks broader transparency.

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, front-loaded sentence that says exactly what the tool does. There is no wasted wording or redundant information, making it highly efficient.

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 and no output schema, the description is nearly complete. However, it does not describe the response format or the fields of a badge, which would be helpful for an agent without an output schema. Still, the simplicity of the operation makes this a minor 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 tool has zero parameters, and the schema is empty. Baseline for 0 params is 4. The description adds no parameter-specific details (as none exist), which is appropriate. It does confirm the scope ('active badges') but this is more about result filtering than parameter semantics.

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 that the tool lists the catalog of active badges for the humanista.digital community. It uses a specific verb ('Lista') and a specific resource ('badges/insignias'), which distinguishes it from sibling tools that search or list other entity types.

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 used when a user needs the active badge catalog, and it provides community-specific context. However, it does not explicitly mention when to use this tool over alternatives like listar_taxonomias or listar_topics, nor does it give exclusion criteria.

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 are provided, so the description must disclose behavior, but it only mentions the resource type. It does not explain pagination, ordering, authentication, or what fields are returned.

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 sentence, front-loaded with the verb, no filler. Perfectly concise, though limited in content.

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 a simple listing tool, the description omits essential details like return format, pagination behavior, and whether results include all reports or are filtered. With no output schema and no annotations, the agent has little to go on.

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 0% and the description does not mention the limit/offset parameters at all. No explanation of pagination or bounds is provided, leaving the agent to infer from parameter names.

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 lists published monthly reports, using a specific verb (Lista) and resource (informes mensuales publicados). It distinguishes from obtener_informe_mensual by focusing on listing rather than fetching a single report.

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 tool versus alternatives. The description only states what it does, not when to prefer it, nor does it mention exclusions like unpublished reports.

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 clearly states what the tool returns (valid taxonomy values) and even enumerates the taxonomy groups, offering transparency about the tool's output. It doesn't mention side effects, but as a list operation the behavior is straightforward and unlikely to have side effects.

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 sentence that is front-loaded with the main action and resource, then expands with specific taxonomy categories. It is concise, informative, and 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 simple zero-parameter list tool, the description covers the essential information: what it returns and why to use it. It could optionally note that the operation is read-only, but that is implied by the nature of the tool and the absence of parameters. The description is sufficiently complete for an agent to select and invoke it correctly.

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 properties, so the baseline is 4. The description adds no parameter information, but none is needed since the tool takes no parameters.

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 'Devuelve' and clearly identifies the resource: valid taxonomy values of humanista.digital, listing specific categories such as ERIHS fields and techniques, interview categories, and event types. It distinguishes from sibling tools by explicitly naming the taxonomy groups, making it obvious this is the vocabulary lookup tool.

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 tool's purpose is to provide values 'para usarlos como filtros en otras herramientas,' which gives clear context on when to use it. It doesn't explicitly mention alternatives or when not to use it, but the intended use case is well-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?

No annotations are provided, so the description alone must disclose behavior. It mentions only that it lists topics, but it omits the filtering behavior of the 'solo_destacados' parameter, any read-only nature, sorting, pagination, or return format. The undocumented boolean parameter materially affects results, making this a meaningful transparency gap.

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 front-loads the verb and resource, includes illustrative examples, and contains no filler or redundancy. It effectively communicates the core purpose in minimal space.

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 has one optional parameter and no output schema, the description is too thin. It does not explain the filtering parameter, the expected return structure, or any behavioral details like ordering or limits. Although listing topics is simple, the presence of 'solo_destacados' suggests functionality that is completely undocumented.

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 defines 'solo_destacados' as a boolean with zero description coverage. The description does not mention this parameter or explain its purpose or impact, leaving the agent without any semantic guidance. While the name alone hints at 'featured only', the description fails to add value beyond the raw 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 action ('Lista' lists) and resource ('temas/topics editoriales de humanista.digital'), with concrete examples like GIS, IA aplicada, and edición digital. This differentiates it from sibling tools such as listar_taxonomias and the various buscar_* tools, making the purpose unmistakable.

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 by specifying editorial topics and examples, but it does not explicitly state when to use this tool versus alternatives like listar_taxonomias or search tools. There are no exclusions or alternative recommendations, leaving the agent to infer usage 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 burden of behavioral disclosure. It adds useful context by stating the response includes 'campos, técnicas y proyectos asociados' and that only published entities are returned, but it does not describe behavior for invalid slugs, error handling, or authentication. It is moderately transparent but not fully comprehensive.

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, concise sentence that immediately communicates the action, target resource, key qualifiers, and response contents. No filler or redundancy.

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 1-parameter fetch-by-slug tool, the description adequately covers the core purpose and the expected response content. It lacks details on not-found behavior or error handling, but given the tool's simplicity and the lack of annotations or output schema, it is largely 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 provides only a parameter name ('slug') and type with no description, and the description merely repeats 'por su slug' without explaining what a slug is, its expected format, or how to obtain it. With 0% schema coverage, the description fails to compensate by adding meaningful parameter semantics.

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+resource ('Obtiene la ficha completa de una entidad') and clarifies the scope ('por su slug') and content ('con campos, técnicas y proyectos asociados'). It clearly distinguishes itself from the buscar_* search tools and the other obtener_* detail tools by targeting generic entities.

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 clearly implies usage when you already know the entity's slug and need the complete record, which differentiates it from search tools like buscar_entidades. However, it does not explicitly state when not to use it or name alternative tools, so exclusions and alternatives are missing.

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 exist, so the description carries the full burden. The verb 'obtiene' implies a read-only operation, and 'contenido completo' clarifies the extent of data returned. However, it does not disclose error responses, not-found behavior, or any potential side effects. More transparency would be beneficial, but the core behavior is reasonably clear.

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, efficient sentence that immediately states the action, target, and parameter format. There is no redundancy or filler; every word contributes to understanding.

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 get-by-slug tool with one parameter and no output schema, the description adequately explains that it retrieves complete interview content. It doesn't explain response structure or errors, but given the tool's simplicity, this is a minor gap. It is complete enough for most use cases.

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 only lists 'slug' as a string with no description (schema coverage 0%). The description adds critical meaning by stating that the slug can be either 'slug' or 'slug_en', which is not obvious from the schema. This compensates for the schema's lack of detail.

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 ('obtiene' - obtains), clearly identifies the resource ('entrevista publicada' - published interview), and specifies the scope ('contenido completo' by 'slug o slug_en'). It distinguishes this from sibling obtener_* tools that target different entities (entidad, evento, etc.).

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 have a slug or slug_en and need the full interview, but it does not explicitly state when to use this vs alternatives like buscar_entrevistas or other obtener_* tools. No exclusion criteria or alternative naming is provided; usage is inferred from the tool's 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?

No annotations are provided, so the description carries the full burden. It discloses that only public and published events are returned, which is useful, but it does not mention error behavior, return format, or any access requirements.

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 is immediately front-loaded with the action ('Obtiene') and contains no redundant 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?

The tool is simple (one param, no output schema), but the description omits return value structure and error scenarios. The phrase 'detalle completo' is vague about what is included, leaving the agent with unanswered questions.

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 one parameter 'slug' with no description (0% coverage). The description merely says 'por su slug', providing minimal additional meaning beyond the parameter name, and does not explain the slug format or constraints.

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 the specific verb 'Obtiene' (gets) and resource 'evento' (event), adding qualifiers 'público y publicado' (public and published) and 'por su slug' (by its slug). This clearly differentiates it from sibling obtener_* tools targeting other resources.

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?

Usage is implied: the tool is for retrieving event details given a slug. However, the description does not explicitly mention when to use this versus buscar_eventos for searching or other obtener_* tools for different resources, nor does it state exclusions.

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 carries the full burden. It discloses that only published reports are retrievable, which is a behavioral constraint. However, it does not disclose error handling (e.g., missing slug), required permissions, or the exact structure of the returned content. For a simple read operation, this is acceptable but not exhaustive.

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, clear sentence that efficiently conveys the tool's core functionality. There is no redundant information, and the key details (action, resource, identifier) are 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?

For a one-parameter retrieval tool, the description is fairly complete: it identifies the resource and how to retrieve it. However, the absence of an output schema and annotations means the description should ideally clarify the return format or error conditions. The phrase 'contenido completo' is vague, and there is no mention of behavior when no published report matches the slug.

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 defines 'slug' only as a string with no description, and schema description coverage is 0%. The description compensates by indicating that the slug identifies the monthly report and that the report must be published. This adds meaningful context beyond the schema, though it doesn't define slug format or validation.

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 ('Obtiene' / gets), the resource ('informe mensual' / monthly report), and the method ('por su slug' / by its slug). It also specifies 'contenido completo' and 'publicado', adding precision. It distinguishes from sibling tools by focusing specifically on monthly reports.

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 have the slug of a monthly report, use this tool. However, it does not explicitly mention alternatives like 'listar_informes_mensuales' for obtaining slugs, nor does it provide any exclusions or when-not-to-use scenarios. Guidance is minimal and left to inference.

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 are provided, so the description carries the transparency burden. It discloses that only published professionals are returned ('publicado') and lists the content categories, providing useful behavioral context beyond just stating the 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?

A single sentence with all key information front-loaded: action, resource, identifier, and content scope. There is no filler or redundant 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?

For a simple retrieval tool with one parameter and no output schema, the description covers purpose and response content. It does not address edge cases like not-found behavior or slug format, but is sufficiently complete for its complexity.

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 no description for the slug parameter (0% coverage). The description mentions 'por su slug' but does not explain what a slug is or how to obtain one, leaving the agent to infer the format from domain knowledge.

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 retrieves a complete professional profile by slug, enumerating included content (links, fields, techniques, entities, projects). This distinguishes it from sibling tools like obtener_entidad and buscar_profesionales.

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 slug is known (por su slug) but does not explicitly contrast with buscar_profesionales or other retrieval tools. No when-not-to-use guidance is provided, leaving some ambiguity.

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 for behavioral transparency. It discloses that the tool returns only published projects and lists the content of the complete record (images, fields, techniques, entities, professionals). It does not mention error behavior or authorization, but for a simple read operation, this is adequate.

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, front-loaded sentence that immediately states the action and resource. Every word earns its place, with no filler 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 simple get-by-slug tool with no output schema, the description provides a helpful list of what the returned record includes, covering the main return content. It does not mention error cases or pagination, but these are less critical given the tool's simplicity. Overall, it is sufficiently complete for an agent to use correctly.

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 one required parameter (slug, string). The description repeats 'por su slug' but does not elaborate on the slug format, example values, or constraints beyond the schema. It adds the constraint that the project must be published, but given the schema description coverage is 0%, the description does not sufficiently compensate.

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 that the tool retrieves the complete record of a published project by its slug, listing included aspects (images, fields, techniques, entities, associated professionals). This distinct, specific verb+resource+scope clearly differentiates it from sibling tools like obtener_entidad or buscar_proyectos.

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 the full record of a published project and already have its slug. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or alternative tools for searching, so the guidance remains 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?

No annotations are provided, so the description carries the burden. It states it retrieves the complete content of a published review, but it does not disclose potential 404 behavior, authentication needs, or rate limits. For a simple fetch, this is acceptable but lacks depth.

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 leads with the verb and includes all essential information. No fluff or redundancy.

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 one-parameter retrieval tool with no output schema, the description covers the purpose and identifier adequately. It mentions 'contenido completo' as the return, but it could benefit from edge-case behavior (e.g., not found). Overall, it is sufficiently complete for this complexity level.

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 only declares 'slug' as a string without description. The description adds meaning by clarifying that the slug can be either the main slug or 'slug_en', which goes beyond the schema. It does not give format examples but still contributes useful semantics.

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 ('Obtiene') and resource ('contenido completo de una reseña de libro'), and clearly indicates the identifier ('por su slug'). It distinguishes itself from sibling tools like 'buscar_resenas' and other 'obtener_*' tools that target different entities.

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 this tool should be used when you have a slug (or slug_en) to retrieve a specific review, but it does not explicitly contrast with 'buscar_resenas' for search scenarios. The context is clear, but exclusions or alternative tool mentions are absent.

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