get_video_transcript

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

Annotations indicate readOnlyHint and openWorldHint, so the tool is safe with no destructive effects. The description elaborates on the exact fallback behavior (manual, auto-generated, first available) and confirms no credentials needed, adding value beyond annotations.

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 two sentences with no unnecessary words. It front-loads the core action and key benefit, then details behavior and use case. Every sentence earns its place.

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?

The tool is simple with three params and no output schema. The description explains the fallback logic and what the return contains (plain text plus metadata). It is complete enough for an LLM to understand usage, though error cases are not mentioned.

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 clear descriptions for all three parameters. The description provides extra context (e.g., fallback chain, return format) but does not significantly improve understanding beyond the schema. Baseline 3 is appropriate.

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 name 'get_video_transcript' clearly indicates the action and resource. The description specifies 'Download the full spoken transcript' and distinguishes from siblings by mentioning 'using yt-dlp — no API credentials required', setting it apart from sibling tools like list_video_captions or get_video_metadata.

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 explicitly states use cases ('Ideal for content research without consuming YouTube API quota') and describes the fallback strategy for selecting captions. It does not explicitly state when not to use or provide alternative tool names, but the guidance is clear for an LLM.

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