recommend_dota_pick

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

No annotations are provided, so the description carries full burden. It discloses calibrated win rates, internal normalization, and return format. It does not mention any destructive actions or error conditions, but is reasonably transparent.

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?

Description is well-structured with a lead sentence, context, and clear Args section. It is concise and front-loaded with main purpose. Every sentence adds value.

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 3 parameters, no output schema, and sibling tools, the description is fairly complete. It explains what, how, and output. Lacks explicit when-not-to-use, but overall sufficient.

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 0%, but the description compensates by explaining each parameter: my_heroes (names/aliases, 0-4), enemy_heroes (0-5), my_side with default. It adds meaning beyond the schema.

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 the top 3 Dota 2 heroes to pick next, with calibrated win rates. It uses specific verb and resource, and differentiates from siblings like predict_dota_winrate and get_dota_counters.

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 context on parameters and return format, but does not explicitly state when to use this tool vs alternatives or when not to use it. The Args section helps, but no direct exclusions.

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