listar_presets

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world, so safety needs no repetition. The description adds genuine context beyond them: the list mirrors the app and CLI state, and each entry carries a format and a command. It does not describe ordering or empty-list behavior, but with no output schema the return content is at least characterized.

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 zero filler: the first identifies the resource and its payload, the second names the consuming tools. The most actionable information, what the entries contain, is front-loaded.

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 list tool with rich annotations, this covers what it returns and why an agent would call it. The only gap is the exact shape of each preset entry (field names, ordering), which no output schema documents either.

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 takes zero parameters, so there is nothing for the description to disambiguate and the baseline applies. The mention of the `preset` field belongs to the sibling tools, not this one's inputs, so it does not add parameter semantics here.

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 (list) and resource (Apolo's saved presets) and adds what each entry contains: format and command. It also anchors the data to the same presets as the app and CLI. It does not explicitly name the write-side sibling guardar_preset, so the create-vs-read contrast is only implied.

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?

Explicitly tells the agent where the results are consumed: the `preset` parameter of optimizar_imagen and empezar_lote. That gives a clear call-before-optimizing workflow. It stops short of stating when not to use it or what happens if no presets exist.

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