SideEye Human Signal Court

by site.chatgpt.bootyplease.saas-bundlecheck

Run a paid release gate and get proof

answer_duel

Paid one-tool x402 flow. Compare two candidate answers against explicit requirements for $0.01 USDC on Base. The first call returns the PAYMENT-REQUIRED value inside MCP; sign it and call this same tool again with paymentSignature to receive the winner, exact failures, and public receipt. Candidate text is not stored.

Input Schema

TableJSON Schema

Name	Required	Description
`task`	Yes
`duelId`	Yes	Caller-generated id used for the public receipt URL.
`candidateA`	Yes
`candidateB`	Yes
`requirements`	No
`paymentSignature`	No	Optional x402 v2 PAYMENT-SIGNATURE. Omit on the first call; provide the signed value on the second call.

Schema Changelog

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

Changed1 schema field changedAug 22, 2026

addedInput schema / properties / paymentSignature

Added value: +{
+  "description": "Optional x402 v2 PAYMENT-SIGNATURE. Omit on the first call; provide the signed value on the second call.",
+  "minLength": 16,
+  "type": "string"
+}

AddedAug 17, 2026

TDQS

B3.4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently reveals that this is a paid flow ($0.01 USDC), describes the two-step payment signature requirement, states that candidate text is not stored, and lists the return values (winner, failures, public receipt). This is substantial and above average for transparency.

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

Conciseness4/5

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

The description is two sentences long but packs essential information: purpose, fee, flow, output, and privacy note. It is front-loaded with the core purpose and then explains the flow efficiently. No unnecessary words.

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

Completeness3/5

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

The description covers the main flow and returns, but leaves some gaps: it does not explain how to sign the payment value or what exactly the 'PAYMENT-REQUIRED value' is, nor does it mention any prerequisites like wallet or funding. Given the tool's complexity (paid, two-step), this is somewhat incomplete but not severely lacking.

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

Parameters2/5

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

The schema description coverage is only 33% (duelId and paymentSignature have descriptions). The description adds meaning to paymentSignature by explaining the two-step flow, but it does not clarify the purpose of task, candidateA, candidateB, or requirements beyond the general comparison context. Since coverage is low, the description needed to compensate but only partially does so.

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 clearly states a specific action: comparing two candidate answers for a fee via a two-step x402 flow. It mentions the fee and the payment requirement, making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like try_answer_duel, which may serve a similar purpose without payment, so it lacks full sibling differentiation.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool: when a paid comparison with proof is needed. It also outlines the two-step usage pattern (first call without paymentSignature, second with it). However, it does not mention alternatives or situations where this tool should not be used, leaving the 'when not to use' guidance implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All SideEye Human Signal Court tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0

Disambiguation3/5

answer_duel and try_answer_duel share the same core action of comparing two candidate answers, while play_sideeye and cast_verdict both involve casting a vote and earning a leaderboard point. The descriptions draw meaningful boundaries via payment/free and today's case vs. general case, but an agent could still easily pick the wrong tool.

Naming Consistency4/5

Most tools follow a clear verb_noun pattern such as file_case, list_cases, cast_verdict, and play_sideeye. leaderboard breaks the pattern as a bare noun, and answer_duel reads as both verb+noun and noun+noun, so the convention is strong but not perfect.

Tool Count5/5

Seven tools cover the main activities of the court platform: filing cases, listing cases, voting, evaluating answers, and checking reputation. The count feels intentional and neither bloated nor thin for the stated purpose.

Completeness4/5

The core loop of file_case, list_cases, cast_verdict, and leaderboard is solid, and answer_duel/try_answer_duel add a distinct evaluative workflow. Obvious gaps like a dedicated case-detail endpoint, explicit case resolution/outcome view, or update/delete operations are missing, but agents can work around them.

Resources

Need Help?