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DanielTomaro13

sportsdata-mcp

opendota_public_matches

Read-onlyIdempotent

Retrieve recent public (non-professional) Dota 2 matches to analyze the ladder meta, including hero picks, average rank, and outcomes. Use rank filters or paginate for targeted data.

Instructions

A sample of recent public (non-professional) matches — the ladder meta rather than the pro scene.

Returns: [{match_id, start_time, duration, avg_rank_tier, radiant_win, radiant_team:[hero_id], dire_team:[hero_id]}] — hero ids only, no player identity

Example: Recent public matches

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_rankNoMinimum rank tier (10=Herald … 80=Immortal).
less_than_match_idNoPaginate backwards from this match id.
Behavior4/5

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

The description adds meaningful behavioral context beyond the annotations: it notes this is a 'sample' of recent matches (not exhaustive), lists the exact return fields, and clarifies the data contains 'hero ids only, no player identity'. It also states 'Auth: none needed'. No contradiction with annotations is present.

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 compact and well-structured: a one-sentence purpose, a return-format line, a minimal example, and an auth note. Every line earns its place with no redundancy or filler.

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 read-only public data tool with two optional filters and no output schema, the description provides the return structure, the sample nature, and authentication status. It could mention pagination behavior or default ordering, but the schema covers the main parameters and the description is sufficient for a 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%, with both parameters (min_rank and less_than_match_id) fully described in the schema. The description does not add further parameter details, so baseline 3 is appropriate.

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 states the tool returns 'a sample of recent public (non-professional) matches', explicitly distinguishing it from professional play ('the ladder meta rather than the pro scene') and from sibling tools like opendota_pro_matches. It also provides the exact return shape, making the purpose unambiguous.

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 implies usage for public/ladder match data rather than professional matches, giving clear context. It does not explicitly name alternative tools or state when not to use it, but the 'rather than the pro scene' phrasing effectively communicates the boundary.

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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