submit_job

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

With no annotations, the description fully discloses the async behavior (immediate 'queued' status), expected wall-clock times for different source types, and special sandbox behavior (canned fixture output). This is transparent about what the caller should expect. No contradictions with 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 four sentences, each delivering actionable information: behavior, timing, beta status, and sandbox testing. There is no fluff; 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 description is comprehensive for a submission tool: it explains the immediate response ('queued' with a job id), how to track progress (get_job), expected performance, beta limitations, and testing options. Although there is no output schema, the description covers the key return behavior. The nesting and options are well documented in the schema, and the description adds the behavioral context necessary for correct usage.

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 input schema already provides full descriptions for all parameters (100% coverage), so the baseline is 3. The description adds beyond that by giving timing estimates that depend on source type and include_trailer, enriching the semantics of those parameters. It does not explain each parameter individually, but the schema does, and the added context about time is useful.

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 opens with a clear verb and resource ('Submit a podcast for processing'), and distinguishes itself from siblings by noting that it returns a job id immediately and that polling is done via get_job. This makes its role 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?

It provides explicit guidance: the tool submits a job asynchronously, and callers should use get_job to poll status. It also clarifies constraints for youtube_url (beta, rejected for live keys) and suggests sandbox keys for deterministic testing, which are valuable usage conditions.

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