get_scheduleGet the F1 season race calendar. Provide year (e.g., 2024). Returns all rounds with race name, circuit, location, and date.
| Name | Required | Description | Default |
|---|---|---|---|
| season | Yes | Season year (e.g., "2025") |
| Name | Required | Description | Default |
|---|---|---|---|
| total | Yes | Total number of races in season | |
| season | Yes | F1 season year | |
| schedule | Yes | List of races |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds detail about the return contents (race name, circuit, etc.), enhancing 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?
Two sentences, front-loaded with action, no wasted words. Efficiently conveys all necessary 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?
Output schema exists, so return values are covered. The description mentions key output fields, making it complete for a simple calendar lookup tool.
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 coverage is 100% with a clear description. The description reinforces the parameter with example values, adding practical guidance 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 action ('Get') and the specific resource ('F1 season race calendar'). It distinguishes from sibling tools, which are unrelated to F1 schedules.
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 example year usage and implies when to use this tool. Lacks explicit when-not-to-use or alternative tools, but context makes it clear.
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.
Several tools are near-clones: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded differ mainly by mode, and deep_research overlaps with all of them. The five polymarket_* tools plus bet_research also blur together, and discover_tools vs suggest_questions both serve a 'what can I do' purpose.
All names are readable snake_case, but the convention is mixed: verb-first (get_current_standings, validate_claim, scan_dependency), noun-first (polymarket_edges, pipeworx_trending), and bare verbs (remember, forget, subscribe). The F1 tools follow a clean get_* pattern that doesn't extend to the rest of the set.
35 tools is excessive, especially since the server is named 'F1' but only 4 tools relate to F1. The set could be consolidated substantially: three ask_pipeworx variants, multiple overlapping polymarket scanners, and two tool-discovery helpers all add weight without clear scope.
The F1 side is thin: no qualifying results, constructor standings, lap data, circuits, or driver search by name. The Pipeworx half is broad, but it belongs to a different domain, leaving the overall surface feeling incomplete for either purpose.