Horse racing pick [PAID — signal credit or x402 USDC. Cost: 1 signal credit ($1.70-$2.49/credit by pack size). Uncredentialed calls return the 402 payment envelope; set X-API-KEY on the MCP connection or pay x402 out-of-band at GET /api/signal/racing.]
| Name | Required | Description | Default |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the payment requirement, the specific cost range, and the behavior of uncredentialed calls (returning 402 payment envelope). It doesn't describe what a successful response contains, but that's partly covered by the absence of an output schema. The payment disclosure is crucial and well-addressed.
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 dense sentence, front-loaded with the essential purpose ('Horse racing pick'). It efficiently packs the payment, cost detail, error behavior, and authentication method into minimal words. No wasted sentences or redundant content.
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 zero-parameter tool with no output schema, the description covers the key aspects: purpose, payment, error behavior, and authentication. The reference to the instruments tool for parameter details is a sensible pointer. It doesn't describe what the successful output looks like, but given the absent output schema and simplicity, this is acceptable. It's mildly incomplete because it doesn't hint at the response format, but for a paid pick service it adequately sets expectations.
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 shows zero parameters and describes additionalProperties as strings, meaning query parameters are open-ended. The description doesn't list specific parameters, but it references the 'instruments' tool for per-endpoint parameter docs. Since there are 0 parameters defined, the description compensates by pointing to the instruments tool, providing a clear path to parameter information. Schema description coverage is 100% but there are no actual parameters to document.
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 begins with 'Horse racing pick' which identifies the resource and action, though it lacks an explicit verb like 'get' or 'retrieve'. It clearly distinguishes itself from sibling tools like signal_equities, signal_f1, etc., by specifying the domain (horse racing).
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 clearly states the cost requirement and that uncredentialed calls return a 402 payment envelope. It also instructs how to authenticate (set X-API-KEY on the MCP connection or pay x402 out-of-band). It doesn't explicitly state when to choose this tool over siblings, but the paid nature and domain specificity imply the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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There is significant overlap between scan_* and signal_* tools for the same underlying asset classes, e.g. scan_futures vs signal_futures, scan_racing vs signal_racing, and scan_predmarket vs signal_polymarket. Broader catch-alls like analysis, scan_ask, backtest, and signal_generate also blur the boundary, forcing an agent to parse long pricing details before knowing which tool actually applies.
The overwhelming majority of tools follow a clear `scan_` or `signal_` snake_case prefix, which makes the product families easy to recognize. A small set of standalone unprefixed tools — analysis, backtest, instruments, leaderboard, quote, track_record — breaks the pattern, but the overall scheme is still consistent enough to infer.
47 tools is far beyond the practical range for an agent to reason about, even though the server's domain is broad and heavily segmented. Many specialist endpoints could be consolidated under fewer catch-all scanners and signals, but the exposed surface instead forces a large tool-selection decision on every request.
The tool surface covers discovery, cost preview, sample analysis, public track records, leaderboards, broad market scanning, asset-class-specific scanning, sports and event signals, and prediction-market verticals. There are minor gaps in explicit account/credit management and some redundant paths, but for a signal/research service the workflow is largely complete.