Recommend Luogu Problems

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

Annotations declare readOnlyHint=true, and the description does not contradict this. It adds value by specifying the tool returns 'seed' problems and includes 'search hints', which gives insight into the output beyond what annotations provide. However, it does not detail other behavioral traits like pagination or error handling.

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 a single, efficient sentence that front-loads the verb and resource. Every word contributes meaning, with no repetition or fluff.

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 description lacks details about the return format (e.g., what a 'seed' problem looks like, how search hints are presented). Given the absence of an output schema, this information is missing, leaving the agent without a full picture of what to expect.

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 detailed parameter descriptions. The tool description only loosely maps to the 'topic' and 'painPoint' parameters without adding new information beyond the schema. Thus, it meets the baseline but does not exceed it.

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 the verb 'recommend', the resource 'Luogu problems', and the context 'from a topic or student pain point'. It also adds 'with search hints for further exploration', which distinguishes it from related sibling tools like luogu_find_related_problems or luogu_find_topic_problems by implying a focus on generating starting points.

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 usage when a topic or pain point is identified, but lacks explicit guidance on when to use this tool versus alternatives like luogu_find_topic_problems. No exclusions or prerequisites are mentioned, making the guidance only implicit.

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