transcribe

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

There are no annotations, so the description carries the full burden. It discloses the output artifacts, that the openai engine requires an API key, that whisper runs locally, and that the result may be long. However, it says nothing about cost, latency, or failure behavior; for example, what happens if YouTube captions do not exist, or how the 'auto' engine chooses. Those gaps matter for a tool that can make network or GPU calls.

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 compact and front-loaded: the main action and outputs come first, then a scannable pipe-separated engine list, then the next-step hint. Every sentence earns its place, and nothing obvious is missing. The only cost is that the engine list is dense and relies on parenthetical shorthand.

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?

An output schema exists, so the description need not explain return values, yet it usefully names the produced files anyway. What is missing is a description of what a 'run' is, whether existing transcripts are overwritten on re-run, and how the 'auto' engine selects among the others. Those are important for a tool with three parameters, one required, and no annotation coverage.

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 0%, so the description must compensate. It does well on engine, giving each option meaning, even though the schema has no enum. But run is not explained and language, including its 'vi' default, is never mentioned. So one parameter is well covered and two are not.

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 gives a specific action and object ("Chuyển audio của run thành chữ") and names the two output files (transcript/transcript.txt with timestamps, transcript.json). That is enough for an agent to understand its role versus the synthesis tools like tts_render or qa_audio. It never explicitly contrasts itself with those siblings, though, so 4 rather than 5.

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 lists every engine value with the condition that selects it (captions = YouTube subtitles, text = existing .txt, openai = needs OPENAI_API_KEY, whisper = local faster-whisper), which is real selection guidance. It also adds a follow-up step, telling the agent to read the resulting transcript.txt with the file-reading tool in chunks. It does not state when not to use the tool, such as when a transcript already exists.

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