start_voice_session

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that the tool logs the start and returns a greeting tailored to the student's context, but it does not specify permissions, state changes beyond logging, failure behavior, or whether it is a safe read operation. This is moderate transparency for a simple tool.

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 concise and front-loaded, using two sentences to convey the core action, the logging side effect, and the return value. There is no fluff or redundant information, making it easy for an agent to quickly grasp the tool's behavior.

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 simple one-parameter tool with no output schema, the description covers the main purpose and return value well. However, it omits potential prerequisite details (e.g., whether the student must be logged in) and edge cases (e.g., what happens if a session already exists), leaving a few gaps in completeness.

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 input schema fully describes the single studentId parameter, and the description adds no additional parameter-specific details. The reference to tailoring the greeting to the student's context is contextual but does not explain format, constraints, or how the ID is used beyond identifying the student. Baseline 3 is appropriate given 100% schema coverage.

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: to create a new voice interaction session. It uses a specific verb ('creates') and resource ('voice interaction session'), and adds detail that it logs the start and returns a personalized greeting, distinguishing it from related session tools like end_voice_session and process_voice_input.

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 implies the tool is used to start a voice session but provides no explicit guidance on when to use it versus alternatives like process_voice_input or end_voice_session. There is no mention of exclusions or prerequisites, so usage context is only implied.

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