resolve_experiment_request

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

No annotations are provided, so the description carries the full burden. It discloses a key behavior — asking the user and blocking other tools when missing is non-empty — but it does not clarify whether the operation is read-only, what 'missing' contains, or what happens when nothing is missing.

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 two short sentences, front-loaded with the core action and then the conditional behavior. It is efficient, though the undefined term 'missing' slightly hurts clarity.

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 7-parameter tool with no annotations and no schema descriptions, this is too thin. An agent cannot determine what makes an experiment request complete, what 'missing' refers to, or how to interpret the result beyond the stated pause-and-ask behavior.

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 0% and the description names none of the seven parameters. The phrase 'required experiment fields' hints that the parameters are the subject of the check, but it does not specify which fields are required or how the default-empty strings should be interpreted.

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 names a specific action — checking required experiment fields — and adds a conditional follow-up: ask the user if missing is non-empty and do not run other tools. It is clearly distinct from the sibling kaggle and drive tools, though it does not name an alternative or define what 'required' means.

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 gives useful sequencing guidance: if missing is non-empty, ask the user and do not run other tools yet. However, it does not explicitly state when to call this tool compared to its siblings, nor does it mention any alternatives.

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