Список AI-агентов

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

The annotation declares readOnlyHint=false, meaning the tool is not read-only, yet the description describes a pure list/read operation ("Возвращает список"). This is a direct contradiction. No side effects are disclosed.

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 sentences, front-loaded with the core outcome (returns list), and includes only essential fields and usage guidance. No waste.

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 parameters and no output schema, the description adequately covers the return fields and positioning for use. However, the annotation contradiction prevents a perfect completeness score as the description is not fully aligned with the tool's declared behavioral hints.

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 has zero parameters, so the schema fully covers parameters. Per the rubric, a zero-parameter tool gets a baseline score of 4, and the description appropriately adds no unnecessary parameter details.

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 the tool returns a list of all AI agents in the account, specifying exact fields (ID, name, status, access type, model ID, token usage). This distinguishes it from related tools like get_ai_agent (single agent) and create/update/delete agent operations.

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 explicitly instructs to use this tool before operations on an agent to obtain the ID, providing clear when-to-use context. It does not mention alternatives but the use case is specific and actionable.

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