Emisoras de Colombia

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 does disclose the return shape ('Devuelve el total de coincidencias y una pagina de resultados') and provides genre mapping guidance. However, the mapping 'El regueton y el hip hop estan dentro de Urbana' introduces 'Urbana', which is not in the declared allowed genre list, creating an internal contradiction. The description also lists 'Salsa' as an allowed genre but later says salsa is within Tropical, which is confusing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and use case, and most sentences carry useful information. However, it is longer than necessary and contains contradictory mapping sentences, particularly the 'Urbana' and 'Salsa' inconsistencies, so not every sentence earns its place.

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 search tool with no output schema, the description covers the main things an agent needs: when to invoke it, what filters are available, genre validation, fallback behavior, and the result summary. Gaps are relatively minor, but the internal genre inconsistency is a real completeness flaw that prevents a higher score.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3; the description adds some beyond-schema guidance, such as using 'texto' for unknown styles and emphasizing that the listed genres are the only valid ones. This added value is partially undermined by the misleading 'Urbana' statement, which could lead an agent to pass a genre value that is not in the schema's documented 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 action ('Busca emisoras de radio colombianas') and enumerates the search dimensions: ciudad, genero, frecuencia del dial, or texto libre. It also distinguishes the tool from station-playing siblings by specifying it is for cases where the user does not name an exact emisora. This is clear, specific, and not tautological.

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

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

The description explicitly says to use the tool when someone asks to listen to Colombian radio without naming an exact station, with concrete examples like 'vallenato en Barranquilla'. It also gives fallback instructions for unknown styles: use the closest genre or pass the style in the 'texto' parameter. It does not explicitly name sibling tools as alternatives, and the when-not-to-use side is implied rather than stated.

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

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

No annotations are provided, so the description carries the full transparency burden. It discloses that the returned address is permanent and redirects to the current signal, and warns that the source link may expire. This adds important behavioral context beyond any schema, explaining persistence and redirect 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 concise and front-loaded with the primary action, then adds a caveat about source expiry. It contains zero fluff and every sentence adds value—coverencing purpose, usage, and a critical warning in two sentences.

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 has only one parameter and no output schema, and the description covers what it returns, when to use it, and a key caveat. It lacks error handling or return-format details, but for a simple retrieval that returns a URL, it is sufficiently complete given annotations are absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the single parameter slug is already well-defined as the station identifier from buscar_emisoras. The description does not add extra parameter semantics beyond that, so a baseline score of 3 is appropriate.

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

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

The description clearly states the tool returns a stable streaming address for a live station, which is a specific verb+resource purpose. It distinguishes itself from siblings like buscar_emisoras (searching) and ver_emisora (viewing details) by focusing on obtaining the playable URL.

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 explicit when-to-use ('usala cuando el usuario quiera escuchar') and also warns against using the source signal directly. However, it lacks any mention of alternatives (e.g., when not to use this tool) relative to siblings, though the instruction to use it for listening is clear.

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?

Since no annotations are provided, the description carries the full burden and delivers excellent context: it enumerates the result fields (ciudad, dial, genero, cadena, sitio oficial) and identifies the response includes both descriptive data and streaming URL. While it doesn't discuss auth, rate limits, or errors, the 'ficha completa' plus the return list gives an agent confidence in what to expect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise, information-dense sentences in Spanish. First sentence handles the purpose and returns; second handles the usage context. Zero fluff, perfectly sized for an agent to read quickly.

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 (1 param, no nested schemas, no output schema) and the completeness of the description plus parameter documentation, it's essentially complete. Rating 4 instead of 5 because the description could have briefly noted error behavior (e.g., invalid slug) — but for a single-record fetch with well-documented parameters, this is nearly perfect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% — the 'slug' parameter already has an excellent description noting it's the identifier from 'buscar_emisoras'. The description text reinforces this by specifying the expected format ('tal como lo devuelve buscar_emisoras'). There are no additional parameter semantics needed. Slightly penalizing for not being at 5 since it could have mentioned whether the slug is case-sensitive, but the description is already doing schema's work.

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

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

The description opens with a specific verb ('Devuelve') and resource ('ficha completa de una emisora'), listing the exact data fields (ciudad, dial, genero, cadena, sitio oficial, descripcion, direccion de escucha) and when to use it (when you already have a slug). This clearly distinguishes it from siblings: it complements buscar_emisoras (which finds slugs) and escuchar (which plays).

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

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

The description explicitly states 'Usala cuando ya tengas el slug de una emisora', directly telling the agent when to call this tool. It also references the sibling tool 'buscar_emisoras' as the source of the slug, establishing a clear workflow and implicitly ruling out usage when seeking stations.

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