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gilangwinduasmara

dota2-coach-mcp-server

Analyze Dota 2 match

analyze_dota2_match

Fetch a public Dota 2 match from OpenDota and return coaching-report-ready JSON with draft, stats, timelines, and optional player deep-dive.

Instructions

Fetch a public Dota 2 match from OpenDota and return a coaching-report-ready JSON summary: result, draft, per-player stats and benchmark percentiles vs. their rank bracket, objectives/teamfight timelines, rank medal, and (with player) a deep-dive on one participant (lane efficiency, deaths log, skill build, damage sources, rune control, item/ability usage counts, item timing, gold/xp/net-worth timelines). Use the returned JSON to write the actual coaching analysis yourself — this tool only extracts and translates data, it does not generate advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
playerNoFocus the deep-dive section on one participant: account_id (exact), personaname (substring, case-insensitive), or hero localized name (substring, case-insensitive). Always pass this when the user asks about their own performance rather than a general match recap. If ambiguous or no match, the tool errors and lists the actual participants — retry with a more specific value (account_id is always unambiguous).
no_waitNoDon't request/wait for a full parse if the match is unparsed; analyze whatever basic data is available.
refreshNoBypass the local cache and re-fetch from OpenDota (e.g. the match was reparsed).
match_idYesNumeric Dota 2 match id, e.g. from a Dotabuff/OpenDota/Stratz URL like .../matches/7891234567

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full load and does well: it discloses the external source (OpenDota), that only public matches are supported, the non-advice behavioral boundary, and the deep-dive mode gated by `player`. It stops short of latency, rate-limit, or cache/parse-failure behavior (those live only in parameter text), so it is not exhaustive.

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?

Front-loaded with the core action and result, followed by the boundary statement. The long parenthetical inventories are dense but informative rather than filler. Slightly unwieldy as a single sprawling sentence, but every clause conveys field-level payload information an agent needs.

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?

No output schema exists, so the description must convey return structure — and it does, listing result, draft, per-player stats with rank benchmarks, timelines, and the optional deep-dive. Combined with the advice boundary, an agent has enough to decide to call it and to interpret the payload.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real semantics: it explains that `player` switches on a whole extra deep-dive section and enumerates its contents (lane efficiency, deaths log, skill build, timings). That goes beyond the schema's parameter description by tying the parameter to output shape.

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?

States a specific verb and resource ('Fetch a public Dota 2 match from OpenDota') and enumerates the returned payload (result, draft, per-player benchmarks, timelines, optional deep-dive). An agent immediately knows both what it does and what it produces; no siblings exist to differentiate from.

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?

Clearly frames the tool's role: extract/translate data, then 'write the actual coaching analysis yourself — this tool only extracts and translates data, it does not generate advice.' That is a meaningful boundary on when the tool's output suffices. It offers no explicit when-not-to-use conditions or alternatives, but with no siblings the gap is minor.

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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