Ángel Moncada Consulting

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

Annotations declare readOnlyHint and idempotentHint, which already cover the safety profile. The description adds context about what is returned (public contact channels and a recommended next step), but does not disclose additional behavioral traits such as data source or limitations. This is adequate given 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?

A single, well-structured sentence that front-loads the action and result. It is concise with no redundant words or 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 zero-parameter, read-only, idempotent tool with an output schema, the description is complete. It clearly states the purpose and result. No invocation-critical information 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?

The input schema has zero parameters, so there is nothing to explain. Schema coverage is trivially 100%, and the baseline for zero parameters is 4. The description correctly does not invent 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 states a specific verb ('Devuelve') and a specific resource ('vías de contacto públicas' and 'siguiente paso recomendado'). It is clearly distinct from sibling tools, which cover methodology, profile, service, cases, recommendations, and search.

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

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

The phrase 'para valorar un proyecto' provides an implied usage context, but the description does not explicitly say when to use this tool over alternatives or when not to use it. No sibling tools are mentioned, so guidance is only implicit.

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

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

Annotations already mark the tool as read-only and idempotent, so the description does not need to restate safety. It adds useful behavioral context by specifying what the methodology covers and that it includes limits and prioritization criteria. No contradiction with annotations exists.

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 front-loads the main purpose and then lists the concrete content areas. Every phrase adds meaningful information with no 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?

Given zero parameters, a safe read-only annotation set, and an existing output schema, the description provides sufficient context. It clearly enumerates what content the tool covers, making it complete for an agent to decide when to invoke it.

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 parameters to clarify. A baseline of 4 applies because no parameter documentation is needed.

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 explains Ángel's methodology for analyzing campaigns, data, web, and processes, including limits and prioritization criteria. This is specific and distinguishes it from sibling tools like get_contact, get_profile, and get_service, which target different 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?

The description implies when to use it: whenever someone needs an explanation of Ángel's working method, analysis criteria, or priorities. However, it does not explicitly mention alternatives or state when not to use this tool, leaving some routing 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds the useful context that the profile is 'público', suggesting no special authorization is needed, which is a modest behavioral insight beyond 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?

A single, concise sentence fully captures the tool's purpose. It is front-loaded with the main object and lists the specific content areas without wasted words.

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

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

For a zero-parameter, read-only profile retrieval tool with an output schema present, the description is complete. The annotations cover safety, and there are no missing inputs or behavioral details that an agent would need to call 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 tool has zero parameters, so the description does not need to explain parameter semantics. The baseline of 4 applies because no compensation is necessary; the input schema is empty and fully self-explanatory.

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 identifies a clear resource: Ángel Moncada's public profile, experience, specialties, and work principles. This distinguishes it from sibling tools like angel_get_contact or angel_get_methodology, which address different aspects.

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: whenever the agent needs Ángel Moncada's professional profile. It does not explicitly name alternatives or state exclusions, but the tool's scope is obvious from the content described.

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 and idempotentHint=true, so the safety profile is covered. The description adds some behavioral context by noting the returned data is 'aprobada' and includes canonical URL, but it does not address errors, authorization, or other runtime behaviors. This is adequate given the read-only, idempotent 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?

A single, front-loaded sentence that immediately states what the tool does and what it returns. There is no redundant wording or unnecessary background.

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, has one required parameter, read-only/idempotent annotations, and an output schema that can cover return-value details. The description is sufficient for basic invocation, though it could have briefly mentioned how to obtain a serviceId or when to use this over related search/list tools.

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 description coverage is 0%, so the description should compensate, but it never explicitly explains the serviceId parameter. However, the parameter is simple, self-descriptive, and its meaning is inferable from the tool name and description ('de un servicio'). The schema provides the type and minLength, so no critical information is missing.

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 a specific verb ('Devuelve') and resource ('un servicio'), and enumerates exactly what is returned: approved description, fit, capabilities, limits, and canonical URL. This distinguishes it from sibling get_* tools like angel_get_contact and angel_get_profile by focusing on service-specific data.

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 caller needs approved service details, but it does not explicitly state when to prefer this tool over alternatives such as angel_list_cases, angel_recommend_service, or angel_search. No exclusions or alternative conditions are provided.

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 and idempotentHint=true, so the safety profile is covered. The description adds the useful behavioral detail that only publicly included projects/brands are listed, but it does not disclose pagination, filtering behavior, or any other side effects. No contradiction with 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?

A single, well-structured sentence that front-loads the action and resource. Every word contributes meaning, and there is no redundant filler or restatement of the title.

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, has no required parameters, has output schema support, and annotations cover read-only/idempotent behavior. Still, the complete absence of parameter semantics and sibling usage guidance leaves meaningful gaps for an agent trying to use filters or decide between this and angel_search.

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 carries the full burden of explaining 'query' and 'category', but it does not mention either parameter at all. The agent receives no guidance on what values are valid, what these filters do, or how they affect the returned list.

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 verb ('Lista') and a specific resource ('proyectos y marcas' on the 'página de casos'), which clearly distinguishes it from siblings like angel_get_contact, angel_get_profile, and angel_search. Even without naming siblings, the resource is distinct 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 the tool should be used when someone wants to list publicly included projects and brands from Angel Moncada's cases page. However, it does not explicitly address when to prefer this over angel_search or other siblings, nor does it mention any exclusions or prerequisites.

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 establish readOnlyHint and idempotentHint, so safety is covered. The description adds useful behavioral context: the tool is heuristic ('parece encajar mejor') and explicitly explains to the user that this is only an initial orientation, setting expectations about the recommendation's nature.

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 with no filler. It front-loads the core purpose and uses the remaining clause to convey the behavioral nuance of initial orientation.

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 output schema and annotations cover return shape and safety, and the core purpose is clear. However, the description omits guidance on optional parameters and does not help an agent choose between this tool and its siblings, so completeness is only 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 0%, and the description only clarifies the meaning of 'situation' as a business situation. The optional 'goal' and 'stack' parameters receive no explanation, leaving the agent to guess their intended content and role in the recommendation.

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: relating a business situation to the best-fit Ángel service. It also conveys the 'initial orientation' role, which helps distinguish it from sibling tools like angel_get_service or angel_get_contact, though it does not explicitly name those 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?

The phrase 'orientación inicial' and 'situación de negocio' imply this tool is for early-stage routing when a user is unsure which service fits. However, the description gives no explicit guidance about when to prefer this tool over siblings like angel_search or angel_get_service.

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 and idempotentHint annotations already cover the safety profile; the description adds that results are matches with canonical URLs and scope is public content. It does not reveal behavior such as pagination, result ordering, or empty-result handling, so it adds only modest context beyond 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?

Two short sentences with the core behavior first and the output characteristic second. Every clause adds information and there is no 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?

For a simple two-parameter search tool with a read-only/idempotent annotation and an output schema, the description covers the main user intent and the output shape. It could be more complete with explicit guidance on when to choose this tool over direct siblings, but is not critically incomplete for 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?

Schema description coverage is 0%, but the two parameter names are self-explanatory: 'query' is the search text and 'limit' caps result count. The description reinforces the meaning of query by saying it searches services, experience, methodology, and cases, though it adds no detail about limit or query formatting.

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 ('Busca') over a defined set of resources: services, experience, methodology, and public cases of Ángel Moncada. It also states the output form ('Devuelve coincidencias con URLs canónicas'), which distinguishes this search tool from the targeted sibling getters and listers.

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 cross-cutting search across the knowledge base, but it does not explicitly say when to prefer it over angel_get_*, angel_list_cases, or angel_recommend_service. The sibling names give context, yet the description itself leaves the choice to inference.

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