generate_config

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

Annotations declare readOnlyHint=false, meaning this is a state-changing operation, but the description never discloses what 'generate' does beyond producing a result — whether it persists the config, validates the prompt, or consumes credits. The 'using AI' phrasing aligns with openWorldHint=true and hints at non-determinism, but that is the only behavioral disclosure beyond the annotations, leaving persistence and side effects unexplained.

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?

A single front-loaded sentence with no wasted words; every component contributes (verb, resource, source, method). It scores highly on compactness, though the brevity comes at the cost of operational detail that other dimensions penalize.

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?

With no output schema and a sibling named create_config, the description leaves essential operational questions unanswered: what the tool returns, whether the generated config is persisted, and how this step fits into the config lifecycle. An agent cannot determine whether calling generate_config alone achieves the goal or whether a follow-up call to create_config is required.

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 only 50%: the `name` parameter has no description, and the tool description does not explain it either. The phrase 'natural language prompt' marginally confirms that `prompt` takes free-form scraping instructions, but it adds no meaning beyond the schema's own 'Describe what to scrape' and fails to compensate for the undocumented `name` parameter or clarify how name and prompt relate.

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 names a specific verb (generate), a resource (scrape config), and the method (from a natural language prompt using AI). It is clear about what the tool does. However, it does not differentiate it from the sibling create_config, which plausibly produces the same end state, so the agent cannot tell from the description alone how the two relate.

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?

No when-to-use or when-not-to-use guidance is provided. With create_config as a sibling, the description never clarifies whether generate_config persists the result, whether create_config should be used for structured input, or whether the generated output feeds into create_config. The only implied context is 'you have a natural language prompt,' which is insufficient to disambiguate the config lifecycle.

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