yt_shorts_experiment_table

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

Annotations already cover readOnly, idempotent, and openWorld, and the description adds substantial behavior beyond them: the newest-first ordering, the live YouTube Data API v3 + Analytics API v2 sourcing, the unauthenticated fallback to public channel pages, and the '—' placeholder for private retention columns. The only gap is that it doesn't say what happens on API failure or auth errors.

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?

Three sentences, front-loaded with the deliverable and column list before the data-source/auth caveats and the empty-case notice. The middle sentence is dense but every clause (auth fallback, placeholder behavior) carries information an agent needs; little could be cut without loss.

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?

With no output schema, the description does the heavy lifting by naming the columns, the ordering, the placeholder for unavailable metrics, and the 'No Shorts found' empty case — enough for correct invocation and interpretation. Minor gaps remain around result-size limits and error behavior, but nothing essential is missing.

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 single 'handle' parameter is fully documented in the schema (100% coverage, including pattern and default), so the description adds nothing parameter-specific beyond referring to "the channel's" Shorts. A baseline 3 is appropriate when the schema already carries the semantics.

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 a specific verb and artifact — "Generate a GitHub-Flavored Markdown comparison table" — scoped to the channel's YouTube Shorts, and enumerates the exact columns. This clearly separates it from siblings like yt_video_details (single video) or yt_channel_snapshot (different output shape).

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 when this is the right tool (you want a newest-first retention/engagement comparison across Shorts), and it explains the authenticated vs unauthenticated data paths. However, it never explicitly says when to prefer a sibling such as yt_video_details or yt_channel_snapshot, so the agent must infer routing from the output format alone.

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