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 effectively describes key behaviors: it creates a new room, enforces a maximum of 6 rooms, restricts to specific room types, and automatically numbers rooms (e.g., 'dormitorio 2'). It also mentions the return confirmation with generated name. This covers mutation effects, constraints, and output behavior well for a tool with no 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?

The description is well-structured with clear sections (Args, Returns, Restricciones) and front-loaded purpose. Each sentence adds value: the first states the action, and subsequent sections explain parameters, output, and constraints without redundancy. It could be slightly more concise by integrating sections, but overall it's efficient and organized.

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 (creation with constraints), no annotations, no output schema, and low schema coverage, the description does a good job of providing context. It covers purpose, parameters, returns, and behavioral restrictions. However, it lacks details on error conditions (e.g., what happens if max rooms exceeded) or system interactions, leaving minor gaps for full completeness.

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 1 parameter with 0% description coverage, so the description must compensate. It adds significant meaning: it explains that 'room_type' is the type of room, lists allowed values (comedor, cocina, baño, living, dormitorio), and implies it's required for creation. This provides clear semantics beyond the bare schema, though it doesn't detail format or validation beyond the 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 clearly states 'Crea una nueva habitación en el sistema' (Creates a new room in the system), which is a specific verb+resource combination. It distinguishes from siblings like consultar_habitacion (query), eliminar_habitacion (delete), and modificar_habitacion (modify) by focusing on creation. However, it doesn't explicitly differentiate from other potential creation tools beyond the room context.

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 through the creation purpose and lists restrictions like maximum 6 rooms and allowed types, which provide some context for when to use it. However, it doesn't explicitly state when to use this tool versus alternatives (e.g., modificar_habitacion for updates) or mention prerequisites like system state. The guidelines are present but not comprehensive.

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 full burden. It states this is a read operation ('obtiene información') and mentions the return includes 'todos sus dispositivos' (all its devices), which adds useful context about what information is returned. However, it doesn't disclose important behavioral traits like authentication needs, rate limits, error conditions, or whether this is a real-time query versus cached data. For a read tool with zero annotation coverage, this is insufficient.

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 perfectly structured and concise: one sentence stating the purpose, followed by clearly labeled Args and Returns sections. Every sentence earns its place - the purpose statement is essential, the Args explains the parameter, and the Returns clarifies what information is included. No wasted words.

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

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

Given the tool's moderate complexity (single parameter read operation) with no annotations and no output schema, the description is minimally adequate. It explains the purpose, parameter, and return content, but doesn't provide enough context about the tool's behavior, error handling, or relationship to sibling tools. The Returns section mentions 'información completa' but doesn't specify the format or structure of the returned data.

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 description explicitly documents the single parameter 'room_name' in the Args section, providing semantic meaning ('nombre de la habitación' - name of the room). Since schema description coverage is 0% (the schema has no descriptions), the description fully compensates by explaining what this parameter represents. With only one parameter clearly documented, this is above 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 the tool's purpose: 'Obtiene información detallada de una habitación específica' (Gets detailed information of a specific room). It specifies the verb (obtiene/gets) and resource (habitación/room), but doesn't explicitly distinguish it from its sibling 'consultar_habitaciones' (which likely lists multiple rooms). The purpose is clear but lacks sibling differentiation.

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 no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tools (agregar_habitacion, consultar_habitaciones, eliminar_habitacion, modificar_habitacion) or explain when this specific room query is appropriate versus listing all rooms or modifying rooms. There's no context about prerequisites 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves a list but doesn't mention whether it's read-only, if it requires specific permissions, or if there are rate limits. The 'Returns' section adds some context about output format, but overall behavioral traits are underspecified for a tool with no annotation coverage.

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 appropriately concise with two sentences: one stating the purpose and one detailing the return format. It's front-loaded with the main action. There's no wasted text, though it could be slightly more structured with bullet points for the return details.

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

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

Given the tool's simplicity (0 parameters, output schema exists), the description is minimally adequate. It explains what the tool does and the return format, but lacks context on usage versus siblings and behavioral details like safety or permissions. With no annotations, it should do more to compensate, but the output schema reduces the burden.

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 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to explain parameters, so it appropriately focuses on output. The 'Returns' section adds semantic value by specifying the output includes room names and device counts by type, which is helpful beyond what the output schema might provide.

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: 'Obtiene la lista completa de habitaciones con su información' (Gets the complete list of rooms with their information). It specifies the verb 'obtiene' (gets) and the resource 'habitaciones' (rooms). However, it doesn't explicitly differentiate from its sibling 'consultar_habitacion' (consult room), which likely retrieves a single room rather than the complete list.

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 no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tools like 'consultar_habitacion' for single-room queries or 'agregar_habitacion' for adding rooms. There's no context about prerequisites, such as authentication or system state requirements.

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 clearly indicates this is a destructive operation ('Elimina') and specifies important constraints about room emptiness. However, it doesn't mention authentication requirements, potential side effects beyond deletion confirmation, error conditions, or rate limits. The description adds value beyond what structured fields would provide but doesn't fully compensate for the lack of 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?

The description is well-structured with clear sections (Args, Returns, Restricciones) and front-loaded with the core purpose. Every sentence earns its place: the opening statement defines the action, the Args section explains the parameter, Returns indicates the outcome, and Restricciones provides crucial usage constraints. No wasted words or redundant 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 destructive operation with no annotations and no output schema, the description does well by specifying the action, parameter meaning, return confirmation, and important constraints. It covers the essential context needed to understand this tool's purpose and limitations. The main gap is the lack of detailed behavioral information about authentication, error handling, or what the confirmation actually contains.

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?

With 0% schema description coverage and only one parameter, the description provides essential semantic context: 'room_name' is 'nombre de la habitación a eliminar' (name of the room to delete). This clearly explains what the parameter represents. While it doesn't specify format constraints or examples, it successfully compensates for the complete lack of schema documentation for this single parameter.

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 ('Elimina' - deletes) and the resource ('una habitación del sistema'), making the purpose immediately understandable. It distinguishes from siblings like 'agregar_habitacion' (add), 'consultar_habitacion' (query), and 'modificar_habitacion' (modify) by specifying deletion rather than creation, retrieval, or updating. However, it doesn't explicitly contrast with these alternatives in the description text itself.

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

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

The 'Restricciones' section provides clear contextual guidance on when to use this tool: only when the room is empty (without devices) and after all devices have been removed first. This establishes important prerequisites for successful invocation. However, it doesn't explicitly mention when NOT to use it or name specific alternative tools for related operations.

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 discloses that the tool modifies an existing room's name and automatically updates associated devices, which is useful behavioral context. However, it doesn't mention permissions needed, whether the operation is reversible, error conditions (e.g., if old_name doesn't exist or new_name conflicts), or rate limits. The description adds value but leaves significant behavioral gaps.

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 efficiently structured: a clear purpose statement, followed by a behavioral note (automatic device updates), then separate Args and Returns sections. Every sentence adds value, with no redundant or vague language. It's appropriately sized for a simple update 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 no annotations and no output schema, the description does a decent job: it explains the tool's purpose, parameters, and return confirmation. However, for a mutation tool, it lacks details on permissions, error handling, and the format of the return confirmation. It's minimally viable but has clear gaps in behavioral context.

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 description explicitly documents both parameters (old_name, new_name) with clear semantics in the Args section, despite 0% schema description coverage. It explains what each parameter represents, compensating fully for the schema's lack of descriptions. Since there are only 2 parameters and both are well-explained, this earns a high score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Modifica el nombre de una habitación existente' (Modifies the name of an existing room). It specifies the verb (modify/update) and resource (room name), but doesn't explicitly differentiate from sibling tools like 'agregar_habitacion' (add room) or 'eliminar_habitacion' (delete room) beyond the different action verbs.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., room must exist), exclusions, or compare it to sibling tools like 'consultar_habitacion' (query room) or 'eliminar_habitacion' (delete room). The agent must infer usage from the tool name and description alone.

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