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Good Earth

Goodearth Check Price

goodearth_check_price

Preview the effective cost of a tool call.

Shows the base cost and any constraint effects (discounts, free trials, surge pricing). Free — no credits required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
npubNo
tool_idYesEither the tool's UUID (from the pricing model) or a bare capability string (e.g. ``"deal_scenario"``). FE callers usually have the capability name; this resolves both so the FE doesn't need to derive UUIDs locally.
dpop_tokenNo
tool_kwargsNoOptional JSON object with tool call parameters for ad valorem / categorical-multiplier pricing preview (e.g. '{"amount_sats": 5000}' or '{"difficulty": "sovereign", "mode": "live"}').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden. It explicitly states that the operation is free and requires no credits, and the word 'Preview' implies no side effects. It does not mention authentication dependencies such as npub or dpop_token, but the cost-related behavior that matters most is disclosed.

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 concise, front-loaded with the core purpose, and every sentence adds value: what it shows and that it is free. There is no redundancy or filler.

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 tool is relatively simple and has an output schema, so return-value documentation burden is reduced. However, the description lacks any usage context around authentication parameters and does not compare against sibling pricing tools. It is adequate but not fully complete for an agent unfamiliar with the environment.

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?

Schema description coverage is 50%; tool_id and tool_kwargs are documented in the schema, but npub and dpop_token are left undocumented. The description adds no parameter-level context, so it does not compensate for the gap. This is a missed opportunity to explain connection/auth parameters.

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 ('Preview the effective cost of a tool call') and clearly names the resource and scope: base cost plus constraint effects such as discounts, free trials, and surge pricing. This differentiates it from related lookup tools like goodearth_get_pricing_model by focusing on the realized, after-constraint price.

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 makes the use case clear: preview costs before executing a call, and emphasizes this preview is free with no credits required. It does not name alternative tools or explicitly state when not to use it, but the context is strong enough for an agent to decide appropriately.

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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