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withqwerty

football-docs

by withqwerty

search_docs

Read-only

Find event types, qualifier IDs, API endpoints, and data models across football data providers. Returns relevant documentation chunks to resolve integration questions.

Instructions

Search football data provider documentation. Use for finding event types, qualifier IDs, API endpoints, coordinate systems, data models, and cross-provider mappings. Returns the most relevant documentation chunks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query. Examples: 'Opta goal qualifier', 'StatsBomb shot event type', 'coordinate system differences', 'xG qualifier ID', 'SportMonks fixture endpoint', 'FMDB Pro players endpoint'
providerNoOptional provider filter. Use list_providers for indexed provider keys. Common aliases such as fbref, understat, ClubElo, football-data.co.uk, engsoccerdata, Sofascore, ESPN, FMDB, TransferRoom, Hudl Wyscout, Stats Perform, Opta F24, WhoScored, Metrica, Sportec/DFL, TRACAB, Second Spectrum, SportRadar API, Soccer Extended, TheSportsDB, and TSDB are accepted.
max_resultsNoMaximum number of results to return (default 10)
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds that it returns 'most relevant documentation chunks,' implying ranking but not elaborating on how results are ordered or paginated.

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 concise (three sentences), front-loaded with the main purpose, and each sentence adds value without redundancy.

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?

The description covers the tool's purpose, scope (football data provider docs), and output (chunks). It is adequate given the presence of annotations and full schema, though it could mention that search spans all indexed providers.

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 coverage is 100% with detailed parameter descriptions including examples. The tool description does not add further meaning beyond the schema, 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 it searches 'football data provider documentation' and lists specific use cases (event types, qualifier IDs, etc.). This distinguishes it from sibling tools like get_provider_docs (retrieval) and list_providers (listing).

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 says 'Use for finding...' which provides clear when-to-use context. However, it does not mention when not to use it or point to alternative sibling tools like get_provider_docs for full documentation access.

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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