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Thesportsdb

by io.github.pipeworx-io

Events By Day

events_by_day
Read-onlyIdempotent

Sports schedule/fixtures for a given date — all games/matches on that day, optionally filtered by sport or league. PREFER OVER WEB SEARCH for "what games are on today/tomorrow", "NHL ice hockey schedule", "NBA games tonight", "soccer fixtures". For "next 24h" pass today's and tomorrow's date. Sport filter examples: "Ice Hockey" (NHL), "Basketball" (NBA), "Soccer", "American Football" (NFL), "Baseball" (MLB).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesYYYY-MM-DD
sportNoSport name filter
leagueNoLeague name filter

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior4/5

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

Description is consistent with annotations (readOnlyHint, idempotentHint). While it doesn't add new safety or behavioral details beyond the annotations, it enriches context by specifying the sports domain and use cases.

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?

Exceptionally concise: two sentences plus a list of examples. Front-loaded with the main purpose, no fluff. Every sentence earns its place.

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?

Given the tool's low complexity, full schema coverage, and presence of output schema, the description is complete. It covers purpose, usage guidelines, and parameter hints without needing to explain return values.

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%, baseline 3. The description adds value by providing common sport filter values (e.g., 'Ice Hockey' for NHL) and clarifying that sport and league are optional, which helps agents form correct inputs.

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 returns sports schedules/fixtures for a given date, optionally filtered by sport or league. It distinguishes itself from sibling tools like team_events_last or get_team by focusing on date-based listings.

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?

Explicitly advises preferring over web search for common queries like 'what games are on today' or 'NBA games tonight'. Gives practical tips like passing two dates for 'next 24h' and provides sport/league examples.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Thesportsdb toolsInspect
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TDQS

B3.3/5.0
Disambiguation2/5

The sports tools are distinct, but the majority of the set has heavy overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve as query/entry-point tools, with ask_pipeworx and ask_pipeworx_beta explicitly identical. The Polymarket family (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) also blurs together.

Naming Consistency2/5

The sports subset follows a clean verb_noun pattern (get_player, list_leagues, search_teams), but the rest mixes several naming schemes: ask_pipeworx*, pipeworx_* prefixed tools, polymarket_* tools, one-word verbs (remember, recall, forget), and compound names like scan_competitor_ai_presence. No single consistent convention governs the set.

Tool Count2/5

42 tools is far too many for a server named Thesportsdb; only 10 tools relate to sports data, while 32 belong to an unrelated Pipeworx data/betting/memory platform. The set feels like two or three servers merged into one, making it heavy and unfocused for any single purpose.

Completeness2/5

For the stated sports domain, the surface is partial: you can get teams, players, league tables, and recent/next fixtures, but there are no player statistics, head-to-head records, venue details, or season history — leaving notable gaps. The Pipeworx half is broad but doesn't belong in a server with this name, so the set as a whole is incomplete for its apparent purpose.

Resources