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DeepBlueCoding

MCP Dota 2 Match Analysis Server

get_hero_deaths

Get chronological list of hero deaths in a Dota 2 match with killer, victim, time, location, and ability. Filter by killer, victim, location, ability, or time for death timeline and pattern analysis.

Instructions

Get chronological list of ALL hero deaths in a match.

Returns all deaths with killer, victim, time, location, and ability used. Use for global death timeline, first blood, or death pattern analysis.

Args: match_id: The Dota 2 match ID killer: Filter by killer hero (partial match, e.g. 'jugg') victim: Filter by victim hero (partial match) location: Filter by map location (partial match, e.g. 't1', 'roshan') ability: Filter by killing ability (partial match) start_time: Filter deaths after this game time (seconds) end_time: Filter deaths before this game time (seconds)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
killerNo
victimNo
abilityNo
end_timeNo
locationNo
match_idYes
start_timeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
deathsNo
successYes
match_idYes
total_deathsNo
coaching_analysisNoAI coaching analysis of death patterns (requires sampling-capable client)
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses chronological ordering, partial-match filtering (with examples like 'jugg' and 'roshan'), and time range filtering with units. It doesn't address edge cases like invalid match IDs or unusual death types, but overall it provides substantial behavioral context.

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 tight and well-structured: a one-sentence purpose, a one-sentence return summary, a one-sentence use case, and a clean args list. No redundant text or fluff—every line earns its place.

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?

With 7 parameters and an output schema present, the description covers all input semantics and the return content (killer, victim, time, location, ability). It also gives practical usage context. The output schema handles the full return structure, so nothing important is left out.

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

Parameters5/5

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

Schema description coverage is 0%, but the Args section in the description documents all 7 parameters with meanings, types, and examples (e.g., 'partial match, e.g. jugg', 'location partial match, e.g. roshan', 'seconds'). This fully compensates for the schema's lack of descriptions.

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 opens with 'Get chronological list of ALL hero deaths in a match', using a specific verb and clearly identifying the resource (hero deaths) and scope (chronological, all in a match). It also states the return fields and common use cases, which distinguishes it from siblings like get_teamfights or get_courier_kills.

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 explicitly says 'Use for global death timeline, first blood, or death pattern analysis', providing clear use cases. However, it does not name alternative tools or provide when-not-to-use guidance, so it falls short of the 'explicit alternatives' criterion.

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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