Recommend Contest Problems

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It only says it 'guides' and 'provides a guide' to find problem sets, but does not disclose what the output looks like, whether it depends on specific parameters like targetContest for specific_contest, or any side effects. This is a significant gap given the absence of 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?

The description is concise at two sentences, but the two sentences are somewhat redundant ('guides how to recommend' and 'provides a guide to find customized problem sets'). It is front-loaded with the core purpose and has no fluff, but could be tightened into one sentence.

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?

With five parameters, no annotations, and no output schema, the description is too thin to be complete. It does not clarify how different purposes affect recommendations, the relationship between parameters (e.g., targetContest dependence on specific_contest), or what the returned data structure is. The schema covers parameter specifics, but the description adds almost no contextual completeness.

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%, with all five parameters having clear descriptions. The tool description does not add any additional parameter semantics beyond what the schema already provides, so it earns the baseline score of 3.

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 tool recommends contest problems based on purpose ('목적에 맞는 대회 문제를 추천'), with specific purpose categories like school contests, ICPC, and specific contest preparation. It distinguishes from sibling tools like search-problem and analyze-contest by focusing on generating customized problem 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 provides clear context for when to use the tool: when preparing for school contests, ICPC, specific contests, or general skill improvement. However, it does not mention exclusions or alternatives, such as using search-problem for finding a single known problem, so it just misses a 5.

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