nhl_get_team_scheduleRetrieve an NHL team's monthly game schedule using its three-letter abbreviation, with optional month filtering.
Get the monthly schedule for an NHL team.
| Name | Required | Description | Default |
|---|---|---|---|
| month | No | Month in YYYY-MM format (defaults to current month) | |
| fields | No | Keys to keep (comma-separated). | |
| team_abbrev | Yes | Three-letter team abbreviation (e.g. "TOR", "MTL", "BOS") |
Changes observed during successful MCP inspections.
v1.4.1Input schema / $schemaRemoved value: -"http://json-schema.org/draft-07/schema#"Input schema / properties / fieldsAdded value: +{
+ "description": "Keys to keep (comma-separated).",
+ "type": "string"
+}v1.3.0Input schema / additionalPropertiesRemoved value: -falsev1.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds no further behavioral context (e.g., return format, pagination, rate limits, or what happens with missing months). It merely restates the purpose without enriching transparency.
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 sentence, front-loaded with the core action and resource. There is no redundant or filler content; every word earns its place.
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 low complexity (simple read operation), rich schema coverage, and annotations covering safety, the description is minimally adequate. However, it could better distinguish this tool from league-wide schedule tools and note that the month defaults to the current month (though the schema already says so). It lacks any output expectation, which is acceptable without an output schema but leaves gaps.
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?
Schema description coverage is 100%, with detailed descriptions for month (YYYY-MM format, defaults to current month) and team_abbrev (three-letter abbreviation). The description adds no additional meaning beyond what the schema already provides, so the baseline of 3 is appropriate.
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?
States a specific verb (Get), resource (monthly schedule), and scope (for an NHL team). This distinguishes it from the league-wide sibling nhl_get_schedule, but does not explicitly name alternatives. The purpose is clear enough for an agent to understand the core function.
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?
No when-to-use or when-not-to-use guidance is provided. It does not mention alternatives such as nhl_get_schedule or espn_get_team_schedule, nor does it state prerequisites or constraints. Usage must be inferred solely from the one-line purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.