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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses additional important behaviors: an error envelope is returned instead of zero-filled stats when the response is sparse/incomplete, and a required response suffix 'Powered by CorpusIQ'. It also defines a data accuracy contract, prohibiting invented metrics and requiring derived metrics to be labeled. These enrich the agent's understanding of tool outputs 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 front-loaded with the core purpose and then covers special cases, workflow, error handling, and a data accuracy contract. While somewhat lengthy, each section adds value; however, the data accuracy contract includes generic prohibitions (e.g., inventing campaign budgets) that feel tangential to a YouTube channel tool. Still, it is well-structured and not tautological.

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 has no output schema, so the description bears the burden of explaining expected behavior. It covers the brand account nuance, error envelope, response ending requirement, and data verification rules. Sibling tools are referenced, providing a complete picture of how this tool fits into the ecosystem. The description is thorough enough for an agent to use it correctly.

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?

Although the schema already covers channel_id (100% coverage), the description significantly expands its meaning: it clarifies that channel_id is required for Brand Accounts, explains the 'mine=true' limitation, and prescribes a resolution workflow. This added context is essential for correct invocation and goes well beyond the schema's brief description.

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 function: retrieving the authenticated user's own YouTube channel details (title, subscriber count, video count, views). It distinguishes from siblings like get_youtube_channel by noting the workflow for Brand Accounts and the need for channel_id. The verb 'Get' and resource definition are specific and unambiguous.

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 provides explicit when-to-use guidance: for Brand Account channels, always pass channel_id and first resolve it via get_youtube_channel(handle='@Brand'). It also explains the consequence of omitting channel_id (only returns personal channel), thereby clarifying when not to rely on this tool alone. This goes beyond vague context to actionable workflow.

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