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Saylor Innovations: pay-per-call data

Get price and payment instructions for an endpoint

get_endpoint
Read-onlyIdempotent

Given an endpoint URL from search_endpoints (with its parameters filled in), returns the exact resource URL, price and x402 payment instructions. The agent then pays over HTTP and receives the data. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull https://saylorinnovations.com/api/... URL including query parameters.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds useful behavioral context: it returns price and payment instructions, is free, and the agent then pays and receives data. It also clarifies the input is a fully-qualified URL from search_endpoints, adding value beyond annotations without contradicting them.

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

Conciseness5/5

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

The description is two sentences with zero fluff. It front-loads the purpose ('Given an endpoint URL from search_endpoints...'), states the return contents, and adds the 'Free.' note. Every sentence earns its place; it is concise and well-structured.

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

Completeness5/5

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

The tool is simple (one parameter, no output schema), and the annotations already cover safety and idempotency. The description explains the return content (URL, price, payment instructions), the source of the input, and the overall flow. Nothing an agent needs to call it correctly is missing.

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?

Schema coverage is 100% (the url parameter is fully described as a full https URL including query parameters). The description adds meaning by specifying the URL should come from search_endpoints and have its parameters filled in, which clarifies the expected source and format. This enriches the parameter's semantics beyond the schema.

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 states a specific verb ('returns'), a clear resource (endpoint price/payment instructions), and a distinct flow: given an endpoint URL from search_endpoints, it provides the exact resource URL, price, and x402 payment instructions. It also mentions 'Free.' to signal cost. This clearly differentiates from search_endpoints (which finds endpoints) and other sibling tools that check tokens or reports.

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 explicitly says 'Given an endpoint URL from search_endpoints', which establishes the tool's place in the workflow: use after search_endpoints to obtain payment details. It implies the usage context (post-search, pre-payment) and the flow of paying over HTTP. However, it does not explicitly state when not to use it or name alternatives, but the context is clear enough.

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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