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

Annotations only signal non-readonly, non-destructive mutation, so the description carries the behavioral burden and delivers meaningfully. It discloses that the name is unique per partner (implying duplicate-name semantics), that limits are stored unmodified as a note, and critically, that the saved limits are not enforced — saving the agent from a wrong mental model. It does not specify whether a duplicate name overwrites or errors, which would have made this a 5.

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: the core verb-object is front-loaded in the first sentence, followed by two short sentences that add uniqueness and non-enforcement semantics. Being bilingual (German/English) doubles length, but both versions are complete and every sentence earns its place. No filler or repetition of schema data.

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 mutation tool with a complex nested-object parameter and no output schema, the description covers purpose, uniqueness, and the non-enforcement nuance well. However, it omits what happens on duplicate name (overwrite vs. error), any return-value expectations, and any mention of the reasoning parameter. These are notable gaps for an agent deciding how to invoke and interpret the call.

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 coverage is 67%, with name and preset documented but reasoning having no description at all. The description adds genuine semantic value for the preset parameter — clarifying that limits within it are stored as-is and serve only as a note — which is beyond the schema text. However, it does not cover the undocumented reasoning parameter, so it only partially compensates for the coverage gap.

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 verb and resource: 'Saves a named preset (configuration bundle) in the partner profile.' It goes beyond a bare statement by defining what the bundle contains and clarifying a key semantic boundary — that limits inside the preset are stored as notes and not enforced, which differentiates it from limit-setting or enforcement tools among the siblings. It does not explicitly name a sibling tool, but the functional scoping is strong enough to avoid confusion with template_save, letter_design_save, or brand_kit_save.

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 conveys implied usage context: it tells the agent this tool persists a configuration bundle and that enforcement happens 'exclusively on the account and sub-wallet limits set in the web app.' This indirectly warns the agent not to expect limit enforcement from this tool, but it never states explicit when-to-use or when-not-to-use conditions, nor does it name an alternative tool. The guidance is inferable rather than direct.

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