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

The annotations already mark this as a read-only, non-destructive operation, and the description adds meaningful behavioral context: accepted formats, base64 input limit, decoded size caps, default compact return, and the combined transcript-plus-analysis behavior. It demonstrates what the tool actually does beyond the declarative annotations, though it does not disclose possible errors or rate limits.

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?

Four tight, focused sentences cover the tool's purpose, output, usage context, and applicable exceptions. The content is front-loaded, with no repetitive phrases or unnecessary verbiage; every sentence directly contributes to selecting and invoking the tool.

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?

Even without an output schema, the description names the return categories and explains the compact by default behavior, which gives the agent the necessary expectation of what comes back. Input constraints, supported formats, size and duration limits, and alternate routes for narrow requests are all present. For a read-only audio analysis tool, this is complete enough to call correctly on the first attempt.

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%, so the parameters are fully explained in the input schema itself. The description reiterates the audio URL/base64 and file-format constraints but does not add new semantic meaning beyond the schema. A 3 is the appropriate baseline when the schema already does the heavy lifting.

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 names a specific verb and resource ('Transcribe English audio AND score how it was said') and enumerates concrete outputs: transcript, tagged transcript, emotion and style label scores, and time-local segments. It also explicitly distinguishes the tool from its siblings by inviting the user to choose alternatives when only words or only tone matter, so there is no ambiguity about scope.

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 gives an explicit when-to-use signal ('Use when the user cares about both the words and the delivery') and tangible examples (meetings, support calls, interviews, voice notes). It also names the exact alternatives for the narrow cases: oruk_transcribe_audio for words only and oruk_analyze_tone for tone only.

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