List Recipe Drafts

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds value by noting it does not load datasets (scope limitation) and that it requires checking backend capability first, which is useful behavioral context 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?

Two concise sentences, front-loaded with the core action and limitation. Every word earns its place; no filler or redundancy.

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 a simple input schema (one required parameter) and rich annotations, so the description is nearly complete. The mention of checking backend capability is a useful prerequisite, and the limitation about not loading datasets is clear. The only minor gap is lack of detail on the return format, but an output schema exists, so this is acceptable.

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 description coverage is 0%, so the description must compensate for the undocumented parameter. The description does not add any specific meaning to the 'study_id' parameter beyond what the schema provides (it's a required string). However, the description implies the parameter identifies the study for which drafts are listed, which is a minimal addition but still leaves the parameter semantics largely unspecified.

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 states it lists study draft metadata without loading datasets, which clarifies the tool's scope and distinguishes it from tools that load full datasets. However, it does not explicitly name sibling alternatives like get_recipe_draft or create_recipe_draft, so differentiation is implied rather than explicit.

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 mentions checking backend draft capability first, which provides some usage context, but it does not specify when to use this tool versus alternatives or when not to use it. No explicit guidance on selecting between list_recipe_drafts and other list/get tools is provided.

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