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DanielTomaro13

sportsdata-mcp

pandascore_teams

Read-onlyIdempotent

Fetch esports teams and their current rosters. Filter by videogame, search by name, and paginate to compare teams across providers.

Instructions

Esports teams with their current rosters.

Returns: [{id, name, acronym, slug, image_url, location, current_videogame, players:[{id, name, first_name, last_name, role, nationality}]}] — SHAPE FROM VENDOR DOCS.

NOTE: this shape is from the vendor's documentation and has NOT been verified against a live response (we hold no key for this provider). Treat it as approximate — inspect the actual payload before relying on a field name.

Example: CS2 teams {"filter_videogame": "csgo"}

Auth: needs your own key in PANDASCORE_TOKEN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number.
per_pageNoPage size (max 100).
search_nameNoPartial team-name match.
filter_videogameNoTitle slug.
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable context: the return shape is from vendor docs and unverified, requiring payload inspection, and auth via PANDASCORE_TOKEN is required. This goes beyond annotations.

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 structured with separate sections for return shape, caveat, example, and auth. All sentences are informative; no fluff, though slightly long.

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 list tool with 4 optional parameters and no output schema, the description provides return shape, example, auth, and a verification caveat. Pagination is implied via page/per_page in schema. It's sufficiently complete.

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 has 100% coverage, but the description adds a concrete example for filter_videogame ('csgo' for CS2), clarifying the slug format. Other params are adequately described in schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Esports teams with their current rosters' and provides the return shape, clearly indicating this tool retrieves team data with rosters. This distinguishes it from sibling tools like pandascore_players and pandascore_matches, though it's a noun phrase rather than an explicit verb.

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

Usage Guidelines3/5

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

The description provides an example ('CS2 teams' with filter_videogame: 'csgo') implying when to use it, but doesn't explicitly compare with alternatives like pandascore_players or pandascore_leagues. No exclusions or when-not guidance.

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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