edit_image

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.