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pregrad_signals

PAID ($0.05/call). Pre-graduation on-chain signals for a Solana mint: bundled-launch detection, curve-aware holder concentration, Token-2022 traps, authority state. Call once WITHOUT x402_payment to receive the x402 payment requirements (an accepts array); pay one of them with any x402 client/wallet, then call again with x402_payment set to the base64 X-PAYMENT payload. You are only charged when a result actually comes back.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mintYesSolana mint address
x402_paymentNobase64 X-PAYMENT payload

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Since no annotations are provided, the description carries the burden of behavioral disclosure. It transparently explains that the tool is paid, requires a preliminary call to obtain payment requirements, and that charges occur only when a result is returned. This is valuable context for an agent. It doesn't mention side effects like data mutation, but the tool appears read-only from its purpose.

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 moderately long but information-dense. It effectively communicates the necessary payment workflow without redundant wording. It is well-structured with semicolons and a clear sequence, making it easy to parse.

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

Completeness4/5

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

The description covers the tool's purpose, required input, payment handling, and charging behavior. It lacks an explicit description of the output format, but since no output schema is provided and the tool's purpose is clear, this is not a major omission. Overall, it provides enough context for an agent to use the tool correctly.

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

Parameters4/5

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

The schema already describes both parameters (mint as Solana mint address, x402_payment as base64 payload). The description adds meaningful context by explaining the payment flow and how x402_payment is used (optional initially, required after payment), which goes beyond the schema's basic descriptions.

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

Purpose5/5

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

The description clearly states the tool's purpose: providing pre-graduation on-chain signals for a Solana mint, and enumerates specific signal types (bundled-launch detection, curve-aware holder concentration, Token-2022 traps, authority state). This distinguishes it from sibling tools like token_report or token_risk_deep.

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

Usage Guidelines4/5

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

The description gives clear usage instructions, including the two-step payment workflow (call without x402_payment first to get requirements, then pay and call again) and the charging condition. However, it does not explicitly compare to alternative tools or state when to prefer this over others, falling short of the full 'when/when-not' guidance.

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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