Set active prompts

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

The description goes beyond annotations by explicitly stating that historical run data is preserved even though the active prompt set is replaced. This usefully contextualizes the destructiveHint=true annotation. It does not detail failure modes, but the output schema and annotations cover much of the remaining burden.

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 primary action and key guarantee (preserving historical data) are front-loaded, and the usage guidance is compact but specific.

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 two-parameter tool with full schema coverage, a clear output schema, and informative annotations, the description covers the essential agent decision points: what the tool does, when to use it, and what behavioral guarantee matters (historical data preservation).

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 100%, so both parameters are already well documented. The description adds contextual meaning by framing prompts as 'approved buyer questions' and 'exact user-supplied set', but brand_id semantics are left entirely to the schema, which is sufficient.

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 uses a specific verb ('Replace') and resource ('a tracked brand's active measurement prompts'), and clarifies the exact user-supplied nature of the set. This clearly separates it from sibling tools like generate_prompts and list_prompts.

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 explicit 'Use when' scenarios: the user has approved buyer questions, wants to import a research prompt set, or needs agreed prompts for an audit. It also excludes the alternative by stating 'instead of AI-generated prompts', pointing the agent toward generate_prompts.

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