Deep single-match analysis, 3 ranked +EV plays [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/scan/game.]
| Name | Required | Description | Default |
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No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and largely delivers: it discloses the 1-credit cost, the 402 payment envelope for uncredentialed calls, and both authentication routes (X-API-KEY on the MCP connection or x402 out-of-band). This is genuinely useful operational behavior that goes well beyond what a generic read/write hint would convey. It lacks details on rate limits, but the auth and cost transparency is strong.
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 core sentence is front-loaded and information-dense, with cost and authentication details efficiently bracketed off. Every clause earns its place. It is only slightly penalized for the telegraphic grammar and dense bracket text, which could be destructured without losing meaning.
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 0-parameter tool with no output schema, the description covers the essential decision-making context: what is returned (3 ranked +EV plays), the cost, and the necessary authentication. A brief note on the result shape or what 'deep analysis' includes would round it out, but given the low complexity this is well covered.
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 exposes 0 parameters, earning the baseline of 4 per the rubric. The schema description adds value by directing callers to the 'instruments' tool for per-endpoint parameter docs, which helps mitigate the openness of the additionalProperties bag, even though the main description itself contributes nothing about parameters.
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 tool's function—'Deep single-match analysis'—and its output of '3 ranked +EV plays,' which distinguishes it within the large sibling set. However, it is grammatically telegraphic and never explicitly names what differentiates it from plausible siblings like 'scan_compare' or 'scan_h2h,' coming just short of a 5.
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?
There is no guidance on when to use this tool versus its alternative siblings, despite 50+ scan_*/signal_* siblings. The schema description points to the 'instruments' tool but only for parameter documentation, not for usage selection. No exclusions, preconditions, or when-to-use guidance is given.
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.
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.