Get Prompts for Profession

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true, providing a strong safety profile. The description adds no further behavioral context—it does not mention whether results are deterministic, whether the library is updated, rate limits, or any authentication requirements. With annotations covering the basics, the description should still add some operational transparency, but it contributes none.

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 the core action and scope. The second sentence about LLM compatibility is somewhat promotional but relevant to usage context. No wasted words overall.

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?

Given a read-only, idempotent tool with a complete schema and an output schema present, the description covers the core purpose but omits practical context such as what the returned prompts look like or how they are structured. It is adequate but leaves gaps for an agent deciding between this and similar prompt-related tools.

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 fully documented in the schema, including examples for 'profession' and limits for 'limit'. The description adds no additional parameter semantics beyond what the schema already provides, making a baseline 3 appropriate.

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 (get) and resource (curated AI prompts for a specific profession), with concrete scope (19,715+ prompts, 65 professions). It is clearly distinguishable from siblings like match_prompt_to_task or search_ai_tools, which do not retrieve curated profession-based prompt sets.

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 implies when to use it—when you want curated prompts for a given profession—but does not explicitly state when to choose this over alternatives like match_prompt_to_task or search_ai_tools. No exclusions or conditions are provided.

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