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beesknees-mcp

Beesknees Check Price

beesknees_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

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose useful traits — this is a read-only 'preview' that is free and consumes no credits, and that pricing can be affected by discounts, trials, and surge. However it omits auth requirements even though the schema carries npub and dpop_token fields, leaving the caller unsure whether credentials are needed.

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 short sentences, front-loaded with the purpose before the pricing-detail clause and the free/low-risk note. Every clause earns its place with no 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?

An output schema exists, so return values need not be described, and the cost model is summarized well. But with two undocumented parameters (npub, dpop_token) and no annotations, the auth/identity side of invoking this tool is left to inference, which is a meaningful gap for a 4-param tool.

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?

Schema coverage is 50%: tool_id and tool_kwargs are documented in-schema (including the UUID-vs-capability resolution and the ad valorem/categorical examples), while npub and dpop_token are undocumented in both schema and description. The description's mention of constraint effects loosely connects to tool_kwargs but adds no new parameter meaning, so it sits at the 3 baseline rather than compensating for the coverage gap.

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

Purpose4/5

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

States a specific verb and resource ('Preview the effective cost of a tool call') and enumerates what the preview contains (base cost plus constraint effects, discounts, free trials, surge pricing). An agent can tell this is a cost-preview tool, though it never names a distinguishing sibling like get_pricing_model to clarify boundaries.

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?

'Preview the effective cost ... Free — no credits required' implies you call it before a paid invocation to check the price, and the free note is a mild use signal. But there is no explicit when-to-use vs when-not, and no routing to alternatives such as get_pricing_model or the balance-check siblings.

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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