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

The description does add real behavioral context — chat costs the account's own provider spend and Seliee tokens, and it names the ERR_AI_ACCOUNT_* / ERR_TOKENS_INSUFFICIENT failure modes. But it prefixes the tool with '[read]' while annotations declare readOnlyHint=false and destructiveHint=true, signalling to the agent that this is a side-effect-free read when it is not.

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?

Dense but well front-loaded: purpose and cost first, then the provider/account hint, then parameters and the return/error shape. The parenthetical-heavy parameter block is a little cramped, but no sentence is wasted.

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?

No output schema exists, and the description compensates by naming the returned keys ({text, provider, account_id, account_uuid, model}) and the error codes for limit and balance failures. For an 8-parameter, cost-incurring tool this is complete enough to call 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 description coverage is 0%, so the description must carry all 8 parameters, and it does: it enumerates provider values, explains account_id vs account_uuid naming, distinguishes message (new turn) from messages (prior turns, oldest first, role user|assistant), and documents system, model default, and the max_tokens <= 8192 cap.

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 ('Chat with one of the merchant's AI accounts ... and get the model's reply as text') and explicitly points to list_ai_accounts for account discovery, which separates it from the account-listing and send_chat_message siblings.

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?

Gives concrete usage context: continue a conversation by resending prior turns each call ('the caller keeps the history'), and use list_ai_accounts to find the account. It does not, however, say when not to use it or contrast with send_chat_message, so it stops short of explicit alternatives.

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