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signal_sports

Sports pick for 35+ sports worldwide [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/sports.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are absent, so the description must disclose behavior. It does disclose that it's PAID and the cost, and that uncredentialed calls return a 402 payment envelope. It also mentions setting X-API-KEY or paying out-of-band. However, it does not describe what a successful response contains, whether it's a real-time or delayed signal, or any rate limits, etc. The focus is on payment rather than behavioral richness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a bit dense and front-loaded with the payment info. It's one long sentence structure with semicolons and brackets. It conveys important info, but it's not as clean as it could be. For a simple tool with no params, the description is longer than necessary, but every piece of info about payment is critical.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool is for 'sports pick' and it's paid, the description doesn't explain what the pick includes, what sports coverage, how the signal is delivered, or any sample usage. Since there is no output schema, the description should provide more context about what the agent can expect from the call. It also fails to explain the relationship to the 'instruments' tool for parameter docs, which is mentioned but not elaborated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, so the schema has nothing to describe. The description doesn't need to add parameter meaning, but it does point to the 'instruments' tool for per-endpoint parameter docs, which is helpful. Given no params, the baseline is 4, but the description's pointer to 'instruments' is useful context so 3 feels appropriate as it doesn't fully clarify what additional parameters might be passed via additionalProperties.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Sports pick for 35+ sports worldwide' which identifies the verb ('pick' as in provide a pick) and the resource (sports signal). It distinguishes somewhat from the many other 'signal_' tools by specifying '35+ sports worldwide' and the paid nature, though it's not explicit about what differentiates it from signal_screener or other signal tools. It could be more specific about the output (e.g., a recommended bet).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

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 vs the many sibling tools like signal_basket, signal_equities, or signal_screener. The description focuses on payment mechanics, not on use cases or scenarios where this would be the right choice.

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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