send_message_to_deeptutor

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds minimal behavioral context—it mentions the 'direct conversation' aspect but doesn't describe what happens when a message is sent (e.g., whether it creates a session, returns a response, or affects memory). While not contradicting annotations, it doesn't enrich behavioral transparency beyond the guardrail.

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 a single, dense sentence that front-loads the usage condition. It wastes no words and conveys the essential guidance efficiently. The structure is ideal for quick parsing by an agent.

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?

Given the tool's moderate complexity (5 parameters, 3 required) and the presence of a fully descriptive schema and an output schema, the description is sufficient for correct invocation. It covers the key usage trigger (explicit request) and the alternative (Codex). Minor context like how session_id interacts or what happens without it is already handled by the schema, so nothing critical is missing.

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 100%, meaning each parameter is already described in the schema. The description does not add additional parameter-level meaning beyond restating the condition for direct_dt_conversation. Since the schema handles parameter semantics fully, the baseline of 3 applies—the description neither enhances nor detracts.

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's purpose: 'send_message_to_deeptutor' is for conversing directly with DeepTutor. It specifies the exact condition ('only when the user explicitly asks to converse directly with DeepTutor') and differentiates it from Codex, which handles ordinary tutoring. This makes the tool's role unambiguous and distinct from siblings like deeptutor_status or list_deeptutor_sessions.

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 provides explicit usage guidance: it tells the agent when to use this tool (only upon explicit user request for direct DeepTutor conversation) and when not to (Codex handles ordinary tutoring). It names the alternative (Codex) and sets a clear boundary, so the agent can decide correctly without confusion.

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