Подключения к ИИ-сервисам

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds valuable behavioral context by disclosing that API keys are never shown—only their last characters—which is exactly the kind of safety-relevant detail that goes beyond annotations.

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 two short, front-loaded sentences. The first sentence states purpose and scope; the second addresses key redaction. No wasted words, and every sentence earns its place.

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 simple list operation with one optional parameter and no output schema, the description provides sufficient information: what is listed, for what scope (case), and a critical privacy guarantee. It does not describe pagination or exact return format, but these are not necessary given the tool's simplicity.

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 input schema fully documents the single 'case' parameter, including its default behavior when omitted. The description does not add further parameter-level detail, so with 100% schema coverage the baseline score of 3 is appropriate.

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 clearly states what the tool does: it lists AI services connected to a case, including models and bot usage counts. It distinguishes itself from sibling tools like ai_save, ai_test, and ai_delete by framing this as a read-only enumeration of existing connections.

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 gives context ('connected to the case') and the optional case parameter, but it does not explicitly state when to use this versus alternatives or provide exclusion criteria. Usage is implied rather than explicitly guided.

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