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

Annotations only declare the mechanical hints (not read-only, not idempotent, open-world); they say nothing about authorization or cost. The description adds two genuinely useful behavioral facts beyond them: the admin/owner role requirement and the per-answer cost tradeoff. It stops short of saying whether the switch takes effect immediately or is reversible.

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?

Purpose and cost caveat are correctly front-loaded, and the model inventory earns its length. Deductions for the semicolon-delimited run-on list and the jarring language switch from English prose to Russian model annotations in the same paragraph, which hurts scannability.

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 two-parameter mutation with no output schema, the description covers purpose, authorization, cost, and option selection — enough to call it correctly. It omits only the minor operational detail of when the change takes effect for live conversations, which is not blocking.

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 `model` enum has no description in the schema), and the description fully compensates by characterizing every one of the 11 enum values with a use case and cost tier (e.g. gpt-5.4 for legal/medical/analytics, gpt-4.1-nano for FAQ/routing). This is meaning an agent could not derive from the raw enum list.

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?

States a specific verb and resource — 'Change the AI model the bot answers with' — which is unambiguous on its own. However, it never distinguishes itself from the plausible sibling dosai_update_bot_settings, which an agent might reasonably pick for the same intent.

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 cost warning ('a smarter model costs more per answer, so confirm with the owner') implies a confirmation workflow, and the admin/owner note sets a precondition. But there is no explicit statement of when to use this tool versus updating bot settings wholesale, and no when-not guidance.

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