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DanielTomaro13

sportsdata-mcp

dabble_competitions

Read-onlyIdempotent

Retrieve sports competitions by exact name or get every competition for a sport ID, including inactive ones. Filter by name or sportId to avoid the massive unfiltered dataset.

Instructions

Look up competitions by EXACT name (name, case-sensitive; e.g. 'NRL', 'Premier League', 'AFL Matches' — note 'AFL' alone returns nothing) OR list EVERY competition for a sport (sportId, including ones not currently active — ~20 for AFL). Pass at least one filter: bare /competitions is the ~38 MB / 142k-row firehose (deliberately avoid). For browsing currently-bettable comps, prefer dabble_active_competitions.

Returns: {status, data:[{id, name, sportId, country}]} (filtered by name or sportId — empty if the exact name isn't found)

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoExact competition name (e.g. 'NRL', 'Premier League', 'AFL Matches').
sportIdNoList all competitions for ONE sport (sportId from dabble_sports) — includes non-active ones.
Behavior5/5

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

While annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, the description adds valuable behavioral context: case-sensitive exact matching, empty results for non-existent names, inclusion of non-active competitions, and the full response shape. These details go beyond the annotations and meaningfully inform the agent's expectations.

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?

Every sentence serves a distinct purpose: describing the primary lookup modes, warning about the bare endpoint, pointing to the alternative tool, specifying the return format, and noting auth requirements. The structure is front-loaded and well-organized, with no filler.

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?

Even though there is no output schema, the description provides the exact return structure, edge-case behavior (empty results), and a performance warning about the unfiltered endpoint. Combined with the annotations and parameter semantics, the description is fully sufficient for correct tool selection and invocation.

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 coverage is 100%, but the description significantly enriches both parameters. It clarifies that 'name' is exact and case-sensitive with examples (e.g., 'AFL' alone returns nothing), explains that 'sportId' includes non-active competitions, and warns that at least one filter is needed despite the schema listing zero required parameters. This compensates for schema optionality and prevents misuse.

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 looks up competitions by exact name OR lists every competition for a sport, with a specific verb-resource pairing. It explicitly distinguishes itself from dabble_active_competitions by noting the preference for browsing currently-bettable comps, making its 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 Guidelines5/5

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

The description gives explicit when-to-use contexts: exact name lookups or broad sport-wide listings. It also warns against calling without filters (the ~38 MB / 142k-row firehose) and recommends dabble_active_competitions as an alternative, providing clear usage boundaries.

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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