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hkaanengin

opendota-mcp-server

by hkaanengin

get_hero_matchups

Discover hero counters and favorable matchups with win-rate statistics. Use this data to plan your draft and make informed hero selections.

Instructions

Get matchup statistics showing how a hero performs against all other heroes.

Use this when users ask about:

  • "Which heroes counter Pudge?"

  • "What are Anti-Mage's best matchups?"

  • "Show me heroes that Invoker struggles against"

  • "Who should I pick against Phantom Assassin?"

  • "What's Rubick's win rate against Storm Spirit?"

Returns win/loss statistics for every hero matchup, useful for:

  • Identifying counter-picks (heroes with high win rates against your hero)

  • Finding favorable matchups (heroes your hero performs well against)

  • Draft analysis and hero selection strategy

Supports fuzzy matching for hero names:

  • "Pudge", "pudge", "PUDGE" all work

  • "Anti-Mage", "antimage", "anti mage" all work

  • "Shadow Fiend", "shadowfiend", "sf" all work

Args: hero: Hero name (display name, internal name, fuzzy match) or hero ID Examples: "Pudge", "antimage", "Shadow Fiend", 86

Returns: List of matchup dictionaries, each containing: - hero_name (str): Name of the opponent hero - games (int): Total games played in this matchup - win (int): Games won against this hero - loss (int): Games lost against this hero - win_rate (float): Win percentage (0-100) against this hero

Sorted by game count (most common matchups first)

Examples: get_hero_matchups("Pudge") -> [ { "hero_name": "Anti-Mage", "games": 15234, "win": 7123, "loss": 8111, "win_rate": 46.75 }, { "hero_name": "Invoker", "games": 14521, "win": 8234, "loss": 6287, "win_rate": 56.70 }, ... ]

get_hero_matchups(86)  # Rubick by ID
-> Same format as above

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
heroYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 discloses return format, sorting behavior, fuzzy-matching behavior, and input flexibility. It does not mention potential errors, rate limits, or authentication, but for a read-only lookup tool the described behavior is transparent and sufficient.

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 well-structured with clear sections (purpose, use cases, fuzzy matching, args, returns, example). It is somewhat verbose but each section adds value; the example output is instructive rather than redundant. It could be tightened slightly without losing clarity.

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?

For a single-parameter lookup tool, the description provides comprehensive context: when to use, input semantics, output format, sorting, and a full example. The presence of an output schema is noted, but the description itself already details the return structure thoroughly.

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%, so the description must fully compensate. It does: it explains the 'hero' parameter accepts display names, internal names, fuzzy matches, and IDs, with concrete examples like 'Pudge', 'antimage', and 86. This far exceeds the bare schema definition.

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 a specific verb and resource: 'Get matchup statistics showing how a hero performs against all other heroes.' It clearly distinguishes itself from sibling tools like get_hero_details or get_hero_item_popularity by focusing on head-to-head matchup statistics. The use-case examples further reinforce the specific purpose.

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 lists natural-language triggers ('Which heroes counter Pudge?') and practical applications (counter-picks, draft analysis). It does not name alternative sibling tools directly, but the guidance is clear enough to know when to invoke this tool. It lacks explicit negative guidance ('do not use for X'), so it misses 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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