Analyze Contest Trend

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains that the tool provides a guide containing difficulty distribution, algorithmic tags, and study direction, which is helpful. However, it does not disclose whether the tool is read-only, whether it fetches live data, rate limits, or any other side effects. No annotation contradictions exist.

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 two concise sentences that front-load the purpose and enumerate the expected output content. Every sentence adds value with no wasted words or redundancy.

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 clarity on the exact output format—it says 'provides a guide' without specifying whether the result is text, structured data, or something else. It also omits any mention of the compareYears parameter and how it affects the returned analysis, leaving significant gaps for an agent with no output schema to infer behavior.

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?

The input schema already provides detailed descriptions for both contestSlugs and compareYears, covering 100% of the parameters. The tool description adds minimal parameter-specific context beyond that, so the baseline score of 3 applies—the schema does the heavy lifting.

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 it analyzes problem-setting trends for specific contests and lists expected outputs like difficulty distribution, algorithm tags, and study direction. However, the phrasing '방법을 안내합니다' (guides the method) introduces slight ambiguity about whether the tool actually performs the analysis or merely provides instructions.

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 no explicit guidance on when to use this tool versus its siblings (e.g., list-contest, search-contest, recommend-contest-problems). It does not mention alternatives, exclusions, or any prerequisites, leaving the agent to infer usage context on its own.

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