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Last Price

get_feature_contract

Read-onlyIdempotent

Read your workspace's feature contract: which fields of a pricing request, nested metadata included, your buyer-aware pricing models learn from, each named by its path in the API, and the column each one gets in an ONNX export. While one is saved, each logged quote keeps only these labels, never raw metadata. Not available until feature contracts are switched on for your workspace. Needs a Last Price credential with routing read scope.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: the availability gate, the required credential and scope, and the effect that logged quotes keep only the contract labels and never raw metadata. It stops short of describing error behavior or rate limits, but it is substantially more informative than the annotations alone.

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 front-loaded with purpose and contains no filler; each sentence adds information about what is returned, how logged quotes behave, and what prerequisites apply. The first sentence is long and syntactically dense, which slightly reduces readability, but overall the structure is efficient.

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?

With no output schema, the description carries the burden of explaining return content, and it does: the contract's fields, their API paths, and their ONNX export columns. It also covers availability and authorization prerequisites. For a zero-parameter read tool, this is complete enough for an agent to call it 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?

This tool has zero parameters, so the schema carries no parameter semantics burden. Per the scoring baseline for zero-parameter tools, the description is adequate and does not need to compensate for undocumented inputs.

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 starts with a specific verb and resource ('Read your workspace's feature contract') and explains the contract's contents in detail: pricing-request fields, nested metadata, API paths, and ONNX export columns. The read-only purpose clearly distinguishes it from siblings like set_feature_contract, delete_feature_contract, and infer_feature_contract.

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 gives prerequisites ('Not available until feature contracts are switched on' and 'Needs a Last Price credential with routing read scope') but does not explicitly state when to use this read tool versus alternatives such as set_feature_contract or infer_feature_contract. Usage is implied by 'Read', but there are no explicit exclusions or alternative-routing 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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