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DeepBlueCoding

MCP Dota 2 Match Analysis Server

get_objective_kills

Get all major objective kills (Roshan, Tormentor, towers, barracks) from a Dota 2 match to analyze timing, tower trades, and high ground pushes.

Instructions

Get all major objective kills in a Dota 2 match.

Returns kills of:

  • Roshan: game_time, killer, team, kill_number (1st, 2nd, 3rd Roshan)

  • Tormentor: game_time, killer, team, side (which Tormentor was killed)

  • Towers: game_time, tower name, team, tier, lane, killer

  • Barracks: game_time, barracks name, team, lane, type (melee/ranged), killer

Use this to analyze:

  • When did each team take Roshan?

  • Tower trade patterns and timing

  • High ground pushes and barracks destruction

  • Tormentor control

Args: match_id: The Dota 2 match ID

Returns: ObjectiveKillsResponse with all objective kill events

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
match_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
successYes
match_idYes
tower_killsNo
roshan_killsNo
barracks_killsNo
tormentor_killsNo
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly explains what data is returned (e.g., Roshan kill includes game_time, killer, team, kill_number) and the overall response type (ObjectiveKillsResponse). This adds substantial context beyond the schema, though it omits details like read-only nature or error behavior.

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 well-structured with a leading summary, a bulleted breakdown of returned objectives, and a separate 'Use this to analyze' section. Every sentence adds value, and the format makes it easy to scan quickly.

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

Completeness5/5

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

An output schema exists, so the description doesn't need to detail return structures extensively. It still covers what objectives are included, their fields, and common use cases. For a single-parameter match-scoped tool, this is complete and self-sufficient.

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

Parameters4/5

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

The schema has one parameter (match_id) with 0% description coverage, so the description must compensate. It does so by stating 'match_id: The Dota 2 match ID,' which clarifies the meaning beyond the bare schema type. Since this is a single simple parameter, this explanation is sufficient.

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 starts with a specific verb+resource: 'Get all major objective kills in a Dota 2 match.' It clearly enumerates the objective types (Roshan, Tormentor, Towers, Barracks) and their associated fields, which differentiates it from sibling tools like get_hero_deaths or get_teamfights.

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

Usage Guidelines4/5

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

The description provides explicit analytical use cases under 'Use this to analyze:' such as 'When did each team take Roshan?' and 'Tower trade patterns and timing.' This gives clear context for when the tool is appropriate. However, it doesn't explicitly mention when not to use it or name alternatives, so it stops short of a 5.

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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