youtube_get_trending

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

Beyond the annotations, it discloses auth needs (Data API v3 vs keyless yt-dlp fallback), return contents (source metadata and video records), and variability over time. This adds meaningful behavioral context without contradicting the read-only/idempotent hints.

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 three sentences with no fluff. It opens with the main purpose, then usage guidance, then behavioral notes, making it well-structured and efficiently front-loaded.

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 single-parameter list tool with no output schema, it covers purpose, usage boundaries, data source behavior, and return contents. This is complete enough for an agent to select and invoke it appropriately.

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?

The schema already documents 'limit' with 'Max results (default 10)' at 100% coverage. The description repeats the parameter name but doesn't add additional semantic meaning beyond the schema.

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 uses the specific verb 'List' with the resource 'currently trending YouTube videos' and scope 'up to limit'. It also explicitly distinguishes itself from keyword search, which differentiates it from the sibling youtube_search tool.

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?

It states 'Use this for broad discovery, not keyword search', providing clear when-to-use context and an exclusion. It also mentions the data source fallback and that results change over time, but it doesn't name the exact alternative tool (e.g., youtube_search).

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