update_prompt_label

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

Annotations are basic (non-readonly, non-destructive). The description adds that changes take effect immediately for all tagged versions and do not reassign labels or touch history, offering valuable 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 sentences, front-loaded with purpose, followed by behavioral notes and prerequisite. No redundant information; every phrase adds value.

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 tool with 4 parameters (1 required) and an output schema, the description covers immediate effects, side effects, and prerequisite steps. No gaps given the tool's simplicity.

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 100% with descriptions. The description reinforces that only name, description, or color can be updated, adding operational context. While not adding new parameter details, it clarifies mutation scope.

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 'Update a prompt label's name, description, or color only', specifying the verb and resource. It distinguishes from sibling update_prompt_version, which changes label assignments, making the purpose 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?

Explicitly contrasts with update_prompt_version and advises using list_prompt_labels to find the label_id first, providing clear when-to-use and prerequisite instructions.

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