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

With no annotations, the description carries the full burden and does well: it discloses the side effect (email only when a model beats the pick), the cap (up to 4 models), and the cost model (checks consume the user's credits at the normal rate). It stops short of stating check frequency, whether it is recurring, or how to stop watching.

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?

Two sentences with no filler; the core action is front-loaded before the behavioral detail. Dense but each clause (retest count, email trigger, credit cost) 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?

For a mutation/notification tool with no annotations and no output schema, the description covers the key behavior and cost but omits the return value, whether the watch is recurring or one-shot, and how to detach. Adequate but with clear gaps.

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 50%. The 'model' parameter is well documented in the schema (default = best-scoring model) and the description alludes to it as 'the user's pick'; the description's 'completed job' phrasing adds mild meaning to the undocumented, required job_id. Neither fully compensates for the half of parameters lacking schema text.

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+resource ('Watch the task of a completed job') and elaborates with the concrete behavior: re-testing up to 4 new/cheaper models against the user's pick. It is clearly distinct from siblings like get_results or run_benchmark, though it never names an alternative explicitly.

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 phrase 'of a completed job' implies a prerequisite (the job must be finished) and the content implies monitoring for future model improvements, but there is no explicit when-to-use vs alternatives or when-not guidance. Usage is inferable rather than stated.

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