get_competition_event_results

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it returns 'focused results data' with a default round filter and optional limits/solve details. However, it lacks information on error handling, rate limits, authentication needs, or data freshness, which are important for a tool fetching competition data.

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 well-structured and appropriately sized. It starts with a clear purpose statement, followed by behavioral notes, parameter explanations, return details, and examples. Each sentence adds value, but the parameter explanations could be slightly more concise (e.g., combining event_id examples).

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 the tool's moderate complexity (5 parameters, no annotations, but has an output schema), the description is mostly complete. It covers purpose, usage, parameters, returns, and examples. The output schema likely handles return structure details, so the description appropriately focuses on semantics. However, it could improve by mentioning sibling tool distinctions or error cases.

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 schema description coverage is 0%, so the description must compensate. It adds significant value by explaining all 5 parameters: competition_id (with examples like 'WC2025'), event_id (with event code examples), round (default and options), limit (optional max results), and include_solves (default and purpose). This goes well beyond the bare schema, though it could provide more detail on parameter constraints (e.g., format validation).

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's purpose: 'Get results for a specific event within a WCA competition.' It specifies the verb ('Get'), resource ('results'), and scope ('specific event within a competition'), distinguishing it from sibling tools like get_competition_results (which likely returns broader results) and search_competitions_by_event (which searches competitions rather than fetching results).

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 usage: 'By default, returns only Final round results for better LLM processing' and explains when to use the 'round' parameter ('Use "all" for all rounds'). However, it does not explicitly state when to use this tool versus alternatives like get_competition_results or search_competitions_by_event, which limits the score to 4.

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