search_teamsSearch TheSportsDB for sports teams by name — football/soccer clubs in any league worldwide including lower divisions, plus NBA, NFL, MLB and more. Returns team id (use with team_events_next / team_events_last for fixtures and results), sport, league, country, stadium, and description.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false. The description adds value by explaining the return payload (team id, sport, league, country, stadium, description) and the scope (worldwide leagues, lower divisions). It also provides usage context that the openWorldHint alone does not, such as the specific sports covered. This is more than 3 but not quite 5 because it doesn't mention rate limits or behavior for no results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately states the core action 'Search TheSportsDB for sports teams by name', then efficiently adds scope, examples, and return values in a compact clause. Every phrase adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple parameter (single string query), the existence of annotations (readOnlyHint, idempotentHint, openWorldHint) and an output schema, the description covers the key missing details: what the tool searches (sports teams by name), its scope (worldwide leagues, multiple sports), and what information is returned. It is complete for the tool's complexity but could briefly mention that results are limited or that further lookups are needed via team_events_next/team_events_last.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 0% description coverage (no parameter descriptions) and just has an 'examples' array with two examples. The description compensates by explaining that 'query' is a team name and listing the type of data returned, which helps the agent understand what search term to provide. With only one parameter and no enums, the agent can infer most semantics from the examples and tool name, so the description adds meaningful context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'search' and resource 'sports teams', with specific examples of team types (football/soccer clubs, NBA, NFL, MLB) and the scope (any league worldwide including lower divisions). It also lists what the tool returns, distinguishing it from similar tools like 'get_team' (which likely returns details for a specific team ID) and 'search_players'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly names related tools for next steps (team_events_next, team_events_last) and clearly states the tool is for searching by name. It implies when to use this tool (when you need to find a team's ID, sport, league, country, etc.) but does not explicitly state when not to use it or mention alternatives among siblings like 'get_team' or 'league_teams'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.