ai_configure

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: not whether this persists a setting, applies immediately, is global or per-project, or what happens when the value is null (the schema default). The parenthetical cost remark is the only extra context, and it is incomplete (unclosed).

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?

One short sentence that is front-loaded and easy to scan, but it is under-specified rather than efficient, and the trailing parenthetical is malformed (missing close parenthesis and a fragmentary dash clause).

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?

An output schema exists, so return values need not be explained, but for a configuration-mutation tool with a 0%-documented nullable parameter and no annotations, the description is far too thin to let an agent invoke it correctly.

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 0% and the single parameter is named 'providers' (an array, nullable, default null), yet the description talks about 'provider/model selection' in the singular. The relationship between the array parameter and the described model choice is never clarified, so the description fails to compensate for the undocumented schema.

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 phrase 'AI provider/model selection' names the resource but supplies no real verb describing what the tool does to it (set? read? apply?). It does not distinguish itself from siblings like config_set, ai_deploy_proxy, or setup_services, leaving the agent to guess the actual operation.

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?

There is no when-to-use, when-not-to-use, or alternative-tool guidance at all. With config_set and config_doctor among siblings, the agent has no signal about which configuration entry point to pick.

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