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get_hero_item_popularity

Retrieve item popularity for a hero across start, early, mid, and late game phases, with item names localized to your chosen language for build recommendations.

Instructions

Item popularity for a hero by game phase (start_game_items, early_game_items, mid_game_items, late_game_items), with item names resolved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hero_idYesHero id (resolve names to ids first with search_dota_entities, e.g. '敌法师' -> 1).
languageNoLanguage for hero/item/ability names. Accepts Steam codes ("english", "schinese", "russian", ...) or tags ("zh-CN", "zh", "ru", ...). Defaults to the OPENDOTA_LANGUAGE env var or "english". Use list_supported_languages to see all options.
Install Server

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description must disclose behavior. It conveys that item names are resolved in the output and that data is split into start/early/mid/late phases, which is useful. However, it does not describe the exact output data shape, whether counts or percentages are returned, or any additional API behavior like pagination or rate limits. This is a read-only operation by name, but no explicit safety detail is added beyond the tool name.

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

Conciseness4/5

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

The description is a single sentence with no filler, front-loading the core purpose and enumerating the phase keys for clarity. It could arguably be more verbose ('Returns item popularity...'), but it is compact and easy to parse.

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

Completeness4/5

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

The tool has one required parameter and moderate output complexity; no output schema exists. The description gives meaningful context about the return structure (phases and resolved item names), enough to understand what the tool provides. It does not detail the exact popularity metric or example payload, but for this straightforward lookup tool, the basics are covered.

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%, with hero_id and language both fully described in the schema. The description adds no information about parameter meanings or how to use them. Since the schema carries the burden, a baseline of 3 is appropriate, as the description contributes no further parameter-level value.

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 clearly identifies the tool as providing item popularity for a specific hero, organized by game phase, with the key added detail that item names are resolved. It is distinct from sibling hero-related tools because none others mention item popularity by phase, though the phrasing is nominal rather than a verb-led action statement.

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

Usage Guidelines3/5

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

The description implies usage: you would call this when you need item popularity data for a hero. However, it provides no explicit guidance on when to prefer it over other hero-related tools, no exclusion criteria, and no mention of alternative tools for similar data such as benchmarks or recent matches. The absence of explicit 'when-to-use' guidance leaves the decision to inference.

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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