FREE — cost preview for any tool on this server: credit type, per-credit USD range, and (when X-API-KEY is set on this connection) your remaining balance and whether it covers the call. Never deducts a credit.
| Name | Required | Description | Default |
|---|---|---|---|
| tool | Yes | Tool name as listed by tools/list, e.g. "analysis" or "scan_forex". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses the tool's behavior: it is free, never deducts a credit, and provides conditional balance info only when X-API-KEY is set. This covers side effects (none) and authentication requirements, which is exemplary for a simple quote tool.
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 deliver all essential details: cost preview scope, output components, conditional balance, and the non-destructive guarantee. The opening 'FREE' immediately draws attention. No word is wasted, and the structure is logically organized from general to specific.
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 tool's simplicity (one parameter, no output schema, no annotations), the description is nearly complete: it states what the tool provides, when it applies, and its safety profile. It doesn't discuss error handling or response shape, but those are less critical for a cost-preview tool without an output schema.
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% and the schema description already explains the 'tool' parameter clearly. The description adds context with 'any tool on this server', and the schema example 'analysis' or 'scan_forex' helps the agent select valid values. This modestly exceeds the baseline for well-documented 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: 'cost preview for any tool on this server'. It lists specific outputs (credit type, per-credit USD range, balance) and distinguishes it from sibling scan/signal tools as a meta-tool for pricing. The verb 'cost preview' is specific and unambiguous.
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 implies when to use this tool: before invoking any other tool to preview cost. It doesn't explicitly say 'use before calling other tools' or mention alternatives, but the phrase 'for any tool on this server' makes the use case clear. The note about X-API-KEY adds a conditional usage context.
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.