transcribe_from_file

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 does well by explaining key behavioral traits: it generates SRT files (output format), mentions hallucination prevention for 'condition_on_previous_text' and 'vad_filter', describes language auto-detection and translation capabilities, and indicates default values for many parameters. However, it doesn't cover performance characteristics, error conditions, or file format requirements.

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 (Args, Returns) and front-loads the core purpose. Each parameter explanation is concise yet informative. However, some explanations could be more streamlined (e.g., 'condition_on_previous_text' and 'vad_filter' both mention 'ハルシネーション防止' - hallucination prevention, creating slight redundancy).

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 (11 parameters, no annotations, but with output schema), the description is quite complete. It explains the tool's purpose, all parameters with semantics, and mentions the return values (SRT file path and language info). The output schema existence means the description doesn't need to detail return structure. It could improve by mentioning performance implications or file size limits.

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?

With 0% schema description coverage (titles only, no descriptions), the description provides comprehensive parameter semantics beyond what the schema offers. Each of the 11 parameters receives clear explanations in Japanese that add meaning: 'file_path' as absolute path, 'device' for inference hardware, 'model_size' as Whisper model, language codes for input/output, 'initial_prompt' for technical terms, boolean flags with purposes, and thresholds with their functions.

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: 'ローカルの動画/音声ファイルから字幕を生成します' (Generate subtitles from local video/audio files). It specifies the verb ('生成します' - generate), resource ('字幕' - subtitles), and source ('ローカルの動画/音声ファイル' - local video/audio files), which distinguishes it from the sibling 'transcribe_from_url' that works with URLs instead of local files.

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 usage context through the parameter explanations (e.g., 'device' for CUDA/CPU inference, 'input_lang' for auto-detection when omitted), but doesn't explicitly state when to use this tool versus alternatives like 'transcribe_from_url'. The distinction from the sibling tool is clear (local files vs. URLs), but no explicit guidance on choosing between them is provided.

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