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get_hero_benchmarks

Obtain typical player benchmarks for any Dota 2 hero, showing percentile stats like kills, last hits, and GPM, optionally segmented by rank bracket to compare performance across skill levels.

Instructions

Benchmarks for a hero: what various percentiles of players achieve (last hits, kills, GPM, ...) by rank bracket (1 Herald ... 8 Immortal; omit for all).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bracketNoRank bracket 1-8 (Herald..Immortal). Omit for all brackets.
hero_idYesHero id (resolve names to ids first with search_dota_entities, e.g. '敌法师' -> 1).
Install Server

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are present, so the description carries the disclosure burden. It discloses the core output semantics (percentile values by bracket) and the option to omit a bracket, but it does not mention anything about the response shape, default behavior beyond 'omit for all', or any caveats. For a read-only query tool this is adequate but not thorough, warranting a mid-range score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, compact sentence that wastes no words. It front-loads the core concept ('Benchmarks for a hero') then specifies the main fields and the optional bracket filter. Every clause serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, so the description should provide enough to succeed. It explains what data all accessible agencies but does not describe the structure of the response, how percentiles are presented, whether a heroic record is required beyond an ID, or the data source. Since the required parameter is handled by the schema and the tool returns, a minimal description is acceptable, but there are gaps regarding response format and defaults.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, meaning both parameters are already fully described in the schema. The description adds minimal semantic value beyond the schema, such as mapping bracket numbers to rank names ('1 Herald ... 8 Immortal') and stating that omitting bracket means 'all brackets', but these details also appear in the schema. With full schema coverage, the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is specific about what the tool returns: percentiles of what various players achieve (last hits, kills, GPM, etc.) for a given hero, broken down by rank bracket. This clearly differentiates it from sibling tools like get_hero_stats or get_hero_matchups, which return different aggregate data. It lacks only the explicit 'retrieves/gets' verb, but the meaning is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states what data is shown but provides no explicit guidance on when to choose this tool versus get_hero_stats, get_hero_rankings, or get_hero_players. There are no conditions, prerequisites, or exclusion scenarios mentioned, leaving the agent to infer the appropriate use case.

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

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