get_player_wordcloud

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

With no annotations, the description carries the full burden. It reveals the output structure (two lists) and sorting behavior, adding value beyond the name. However, it does not disclose potential caveats like case sensitivity, text normalization, or how filters interact with results.

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 sentences with no filler. The first sentence explains the return content and structure, the second gives the use case. Every word earns its place and it is well-organized.

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 rich 19-parameter schema and absence of an output schema, the description adequately explains the high-level return shape but lacks details on list item format (e.g., word-frequency pairs) and default behaviors. It is sufficient for basic understanding but not fully comprehensive.

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 covers 100% of parameters with descriptions, so the baseline is 3. The description does not add extra meaning beyond what the schema already provides, but it does not need to since all parameters are well-documented.

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 returns words said in a player's matches, sorted by count, with separate my_words and all_words lists. This precisely identifies the resource and differentiates it from all sibling tools, none of which are wordcloud-focused.

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 a clear use case ('chat-toxicity or tilt flavor') but does not explicitly state when to use alternatives or exclusion criteria. It implies the intended context but lacks direct comparison to sibling tools.

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