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get_player_wardmap

Generate a player's ward placement heatmap showing observer and sentry counts and positions on the map, with optional filters for wins, heroes, game modes, and more.

Instructions

Ward placement heatmap for a player: total observer/sentry counts plus the raw position maps (keys are x,y on a 64x64 grid — divide by 64 for map fraction; game coords = value*range/64).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
winNo1 = wins only, 0 = losses only.
dateNoOnly matches from the last N days.
sortNoSort results by this field, descending (e.g. 'start_time').
limitNoMax results to return.
patchNoPatch id filter (e.g. from get_constants patch).
havingNoMin games played (used by hero-stat tools).
offsetNoSkip this many results (pagination).
regionNoRegion id filter.
hero_idNoOnly matches on this hero id.
game_modeNoGame mode id filter (e.g. 22 = Ranked All Pick).
lane_roleNoLane role: 1=Safe, 2=Mid, 3=Off, 4=Jungle.
account_idYesSteam32 account id (the number after /players/ in an OpenDota profile URL, or from search_players).
is_radiantNo1 = Radiant side only, 0 = Dire only.
lobby_typeNoLobby type id filter (e.g. 7 = Ranked).
significantNo0 (this server's default) includes ALL game modes including Turbo; 1 = only standard/ranked-style modes (OpenDota's own default, which hides Turbo).
with_hero_idNoOnly matches with these heroes on the player's team.
against_hero_idNoOnly matches against these heroes.
excluded_account_idNoExclude matches where these account ids played.
included_account_idNoOnly matches where these account ids played.
Install Server

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It explains the coordinate system ('keys are x,y on a 64x64 grid') and how to interpret raw position maps, which adds non-obvious behavior. However, it does not disclose the output structure beyond counts and maps, nor any caveats about performance, scaling, or network behavior. That is acceptable but not rich for an un-annotated tool.

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 that is front-loaded with the core purpose and wastes no words on filler. It packs in the coordinate legend and conversion rule efficiently. It could have separated the coordinate explanation into a second sentence for readability, but overall it is lean and structured well.

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?

For a tool that returns a wardmap for a player with many filter parameters, the description explains the key output components (total counts + raw position maps) and the coordinate math, which is non-obvious and essential for correct interpretation. With no output schema, the description adequately covers the return structure though it does not mention, for example, whether results include game mode or hero breakdowns, but the filters in the schema imply these are applied. The description is sufficiently complete for typical agent invocation.

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%, and the input schema documents every parameter with clear descriptions (win, date, sort, limit, etc.). The description adds nothing about parameters themselves—it only describes the output format and coordinate conversion. Since the schema already covers the semantics, a baseline of 3 is appropriate with no additional value from the description.

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

Purpose5/5

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

The description clearly identifies the tool's purpose: 'Ward placement heatmap for a player' with a specific resource (player) and resource (ward placements). It distinguishes itself from sibling tools like get_player_wordcloud (word chat) or get_player_heroes by naming the ward heatmap topic. No ambiguity.

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 implicitly indicates the tool is used when an agent needs ward placement data for a player, but it does not explicitly state when to use this tool compared to alternatives like get_player_totals (which might include warding stats) or get_player_histogram. No exclusions or when-not-to-use guidance is given; context must be inferred.

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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