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

Annotations already flag destructiveHint=true and idempotentHint=true, but the description adds real context: partial-update semantics, whole-list replacement of triggerPhrases/participantList/availability.days, the evaluation order (availability → participant list → thread ownership → trigger phrases → aiRule), and that the response returns warnings when the saved combination would silence the AI. That is material behavior an agent cannot infer from the 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?

Front-loaded with the core purpose and partial-update rule, then the evaluation order, then exclusions. Every sentence carries information, though the single dense paragraph could be split for faster scanning of the exclusion clauses.

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 noting the response carries silence-simulation warnings to relay. Combined with partial-update rules, list-replacement caveats, decision order, and explicit exclusions, an agent has enough to call this destructive mutation 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 50% and the nested rules object is heavily self-documented, so the schema carries most of the load. The description still adds cross-field meaning the schema cannot: omitted fields keep their value, lists are replaced wholesale, and fields are evaluated in a specific order. It stops short of explaining individual field interactions like matchMode vs enabled beyond what the schema already says.

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 WhatsApp 'AI rules' of a Convocore agent) and immediately clarifies the resource's effect: governing when the AI should or should not reply to inbound WhatsApp messages. It also names what it is not (update_agent/patch_agent_prompt, update_whatsapp_number_settings aiPaused), so it is distinguishable from siblings without inspecting schemas.

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?

Explicitly routes to alternatives: content changes go to update_agent / patch_agent_prompt, pausing goes to update_whatsapp_number_settings aiPaused. It also prescribes the read-first workflow with get_whatsapp_ai_rules before mutating lists, which is exactly the when-and-how guidance an agent needs.

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