Fetch current NFL football game scores, schedules, and results. Returns team matchups, final scores, scheduled start times, team standings, and individual player stats. Use for fantasy football, sports analysis, or following NFL season progress.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include readOnlyHint=true, and the description reinforces this with 'Fetch' and lists detailed return content (matchups, scores, start times, standings, player stats). This adds context beyond annotations by describing what data is returned. No mention of limitations, but baseline is well covered.
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 two sentences, front-loaded with the action and resource. Every clause adds relevant information: what is fetched, what is returned, and intended use cases. No 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?
For a simple read-only tool with no parameters and no output schema, the description is quite complete. It covers input (none needed), behavior (fetch current data), output (specific data elements), and use cases. Minor gaps like timezone or update frequency are not critical.
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 tool has 0 parameters, so schema coverage is 100%. Per the rubric, a baseline of 4 is appropriate. The description adds value by explaining what will be returned, compensating for the lack of parameter details.
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 uses a specific verb 'Fetch' and clearly identifies the resource: NFL football game scores, schedules, and results. It distinguishes itself from sibling tools by focusing explicitly on NFL, unlike NBA and NHL siblings.
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?
Provides clear usage context: 'Use for fantasy football, sports analysis, or following NFL season progress.' While it doesn't explicitly mention when not to use or name alternatives, the NFL-specific scope implies separation from NBA/NHL tools.
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 tools are mostly distinct in purpose, with get_all_scores providing a combined summary and the league-specific tools offering more detailed statistics and player data. However, there is some overlap since get_all_scores also returns scores from each league, which could cause an agent to hesitate when choosing between the combined and specific tools.
All tool names follow a consistent get_<scope>_scores pattern, with get_all_scores being the only deviation from the league-specific naming but still clear and predictable. This makes it easy to understand the function of each tool at a glance.
The server has 4 tools, which is well within the ideal 3-15 range. Each tool serves a clear purpose: one for each major league and a combined all-scores option. This is a compact, focused set with no unnecessary bloat.
The tools cover the core need for retrieving scores from NBA, NFL, and NHL, including schedules, standings, and player stats. A minor gap is the lack of date or team-specific queries, and the absence of MLB coverage, but for daily score monitoring the surface is reasonably complete.