transcribe_podcast

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

No annotations provided, so description carries full burden. Discloses that speaker detection is off by default, caching by file hash, returns only lightweight metadata, and explains why full transcript is not returned. Covers supported formats. Does not mention auth needs or rate limits, but these are less critical for a transcription 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 well-structured with clear sections (STEP, What it does, Returns, Caching, Supported formats, After transcription). It is longer than a typical tool description (10 sentences), but each sentence adds meaningful information. Could be slightly more concise, but the length is justified by the complexity.

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 complexity (6 parameters, no output schema, no annotations), the description covers workflow, caching, supported formats, and post-transcription steps. It does not detail error scenarios or performance, but the provided information is sufficient for typical use. Describes the return value adequately with lightweight metadata and packed_ready flag.

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% with good descriptions. The description adds value beyond schema by explaining the caching behavior, output format, and workflow context. Provides extra detail on enable_diarization, which the schema already covers, but the description clarifies its engine dependency and default off state.

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 clearly that it transcribes a podcast file using Whisper AI, with specific verb+resource. Distinguishes itself as the first step in a workflow, and mentions speaker detection and caching, differentiating from potential siblings like import_transcript or transcribe_start.

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 positions itself as STEP 1 and provides a clear post-transcription workflow (call get_ui_state). However, it does not explicitly mention when to avoid using this tool or alternatives like import_transcript, so some guidance is implicit.

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