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

With no annotations, the description carries the full burden, and it does disclose the key side effect: the result is written to disk and the path is returned. It omits other relevant traits such as cost/neuron consumption, whether files can be overwritten in out_dir, or that most parameters only apply to one of the two models — though the schema covers the latter.

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, zero waste, with the input→output contract and the disk-write side effect front-loaded. Nothing in it is redundant with the title or schema.

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 an 11-parameter image-editing tool with no annotations and no output schema, the description covers what it does and where the result goes, which is the minimum an agent needs. It does not explain model selection trade-offs or output naming, leaving that entirely to the schema.

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 individual parameters (seed, count, model, strength, out_dir, etc.) are well documented in the schema itself. The description adds no meaning beyond that, so baseline 3 applies.

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?

States a specific verb+resource pair ('Genera una nueva imagen a partir de otra imagen + un prompt') and adds the observable outcome (guarda en disco, devuelve la ruta). The 'a partir de otra imagen' phrasing implicitly separates it from generate_image, but the sibling is never named, so the differentiation is left to inference.

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 only implied: an agent can infer this is the tool to pick when it has a source image, but the description never says when to prefer it over generate_image, nor states prerequisites (accessible input path/URL, model access). No exclusions or alternatives are named.

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 behavioral burden. It usefully discloses two side effects—saving the result to disk and returning the path—but omits details such as overwrite behavior, permissions, cost implications, and how multiple generated variants affect the returned path.

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, front-loaded with the core action and followed by the important side effect and return value. There is no wasted language.

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 rich schema covers all parameters, and the description minimally covers the lack of an output schema by stating that a path is returned. However, it does not clarify the return format when count is greater than 1, nor does it fully address disk-write behavior for a generation tool with nine parameters.

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 all nine parameters are already documented in the schema. The description adds no parameter-level meaning beyond 'from text', making the baseline score of 3 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 a specific verb and resource: generates an image from text. It does not, however, distinguish this tool from the sibling edit_image, so it falls short of a 5.

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 'desde texto' implies a text-to-image generation use case and weakly distinguishes it from edit_image, but there is no explicit guidance on when to use this versus edit_image or get_image_info, and no 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; it usefully discloses that no API calls or quota are consumed, which confirms a safe local read. However, it omits error behavior for missing/inaccessible paths and does not explicitly frame the operation as read-only and side-effect free.

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, zero filler, with the capability stated first and the cost/constraint note second. Nothing could be removed without losing information.

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

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

For a single-parameter local read tool with no output schema, the description names the returned values (dimensions, format, size) and the no-quota trait, which covers nearly everything an agent needs. Only minor gaps remain around failure modes.

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% ('Ruta local o file:// de la imagen'), so the single path parameter is already well documented. The description adds no format examples or path-handling nuances beyond the schema, making baseline 3 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?

States a specific verb and resource ('Lee dimensiones, formato y tamaño de un archivo de imagen local') with three named return fields, so the agent knows exactly what comes back. It does not explicitly contrast with siblings edit_image/generate_image, but the read-only inspection framing makes the difference evident in practice.

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 qualifier 'local' plus 'No consume API ni cuota' implies the correct context (local files, free to call), but it never states when to prefer this over edit_image or generate_image, nor any prerequisites such as file existence or permissions.

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