get_matchA match or tournament by its 4-character code: players with levels, spots left, venue, time, level range, result. Public data only.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | The code from the link. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds that the operation is public, which signals no special auth is needed, and enumerates the returned data (players, spots left, venue, time, level range, result), which is valuable since there is no output schema. No contradiction with annotations.
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?
A single dense sentence front-loads the resource and key, then lists the returned fields with no redundant wording. Every clause contributes information.
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?
For a one-parameter, read-only getter with annotations covering safety, the description is complete: it states the input, the data scope, and the relevant output fields. Since there is no output schema, the explicit field list is especially important and is present.
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 input schema already describes 'code' as 'The code from the link' with 100% coverage, so the description adds little. The claim of a '4-character code' is slightly inconsistent with the schema's minLength 4 / maxLength 6, creating minor ambiguity. No enum or nested structure to explain.
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 identifies the resource (a match or tournament) and the lookup mechanism (4-character code), and lists the fields returned. However, it is phrased as a noun phrase rather than an explicit verb-led statement such as 'Retrieves...', and it doesn't explicitly differentiate itself from sibling lookup tools beyond the code-based access.
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 implies the right use case: use this when you already have a match/tournament code and need its details. It does not explicitly name alternatives like find_matches or state exclusion criteria, but 'by its 4-character code' and 'public data only' provide clear context.
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.
Each tool targets a clearly distinct resource or action: about/API key, match creation, club searching, match searching, schedule generation, group retrieval, match retrieval, and joining. Even similar tools like find_matches and get_match are separated by clear inputs and purposes.
Nearly all tools follow the verb_noun pattern: create_match, find_clubs, find_matches, generate_schedule, get_group, get_match, join_match, create_api_key. The only deviation is about_kicksmash, which uses a preposition-style prefix instead of a verb.
Nine tools is well-scoped for a padel-focused assistant. Each tool serves a distinct user need without redundancy or bloat.
The core workflows—discovering clubs/matches, creating matches, joining matches, retrieving match/group info, and generating schedules—are well covered. Update/cancel/leave operations are absent, but the organizer manageUrl suggests those happen outside the MCP surface, so this is a minor gap rather than a dead end.