normahub_transcribe_audio

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

No annotations exist, so the description carries the full burden. It usefully discloses that access is via NormaHub so no VPN is required and that two input sources are supported, but it says nothing about latency for long audio, cost/credit consumption, size limits, or failure modes — relevant gaps for an unannotated 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?

Two tight sentences, front-loaded with what the tool does and followed by accepted input forms. No filler and nothing repeated.

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 5-parameter, no-annotation, no-output-schema tool, the description covers what it does and where input comes from. It stops short of describing the returned artifact (plain transcript text vs. segments/timestamps), which is the one thing an agent cannot infer from structured fields.

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 100%, so every parameter is already documented (url vs file_path precedence, model default, language auto-detection, prompt hints). The description only echoes the url/file_path duality and adds no new semantic detail; baseline 3 applies.

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?

Specific verb ('Transcribe') plus resource ('audio recordings, voice notes, video soundtracks'), the engine used (OpenAI Whisper via NormaHub), and the accepted inputs. It is unmistakably distinct from the sibling generation/model-listing tools.

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 sentence 'Accepts local file path or public HTTP URL' gives input-mode guidance, and the purpose makes the use case implicit. However, there is no statement of when to prefer this over alternatives, no prerequisites, and no mention of constraints such as file size or supported duration.

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