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ProAbono MCP Installation

Official

Look up a ProAbono API Live endpoint or object

get_api_reference

Fetch the ProAbono API contract for an endpoint or object: required params, request body schema, responses. Use before calling or generating API calls for accurate parameter names and shapes.

Instructions

Returns the exact contract of a ProAbono API Live endpoint (parameters, whether each is required, request body schema, responses) or of a named object such as Customer, Subscription, Offer, Feature or Usage. Use it before calling or generating a call to the ProAbono API, so parameter names and shapes come from the contract rather than from memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
objectNoA schema name, e.g. "Customer", "SubscriptionRequest", "Usage".
endpointNoAn endpoint path or fragment, e.g. "/v1/Customer" or "subscription".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the transparency burden. It discloses that the tool returns contract information rather than making the API call, and it enumerates what the contract contains: parameters, required flags, request body schema, and responses. It does not cover edge cases like missing or conflicting arguments, but this is a minor gap for a lookup tool.

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?

Two sentences with no filler. The first sentence states what the tool returns, the second explains when to use it. Every clause earns its place.

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?

For a simple two-parameter lookup tool, the description covers the return value, the lookup modes, and the recommended usage context. A small ambiguity remains because both parameters are optional in the schema and the description does not explicitly require one, nor does it describe the behavior if both or neither are passed.

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 input schema already describes both params at 100% coverage, so the baseline is 3. The description adds useful context by framing them as alternate lookup modes ('endpoint or object') and giving additional object examples, but it does not specify whether both params can be supplied together or what happens if neither is provided.

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 uses a specific verb ('Returns the exact contract') and names a clear resource: a ProAbono API Live endpoint or a named object like Customer, Subscription, Offer, Feature, or Usage. It distinguishes this meta-lookup tool from the many sibling tools that perform actual API operations.

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 to use this tool before calling or generating a call to the ProAbono API, so parameter names and shapes come from the contract rather than memory. It does not name alternative tools or state when not to use it, but the intended context is clear.

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