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commodity_price

Price of ONE Citizens City commodity in APEX from its on-chain AMM pool: price, token and APEX reserves (depth), fee and burn in basis points, whether it is tradeable or paused, and the minimum buy. Pass the name, e.g. "Tomato", "Truffle", "Voidbloom"; an unknown name returns the list of names. For every market at once use commodity_markets; to trade, commodity_swap_build.

Input Schema

NameRequiredDescriptionDefault
commodityYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and largely meets it: it discloses the data source (on-chain AMM pool), the full set of returned fields including depth and burn bps, the paused/tradeable state, and the unknown-name fallback behavior. It stops short of stating read-only nature, auth requirements or freshness/rate limits.

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?

One dense paragraph that front-loads the primary purpose, then return fields, then the input example and fallback, then sibling routing. Every clause carries information, though the return-field enumeration makes the sentence long and slightly list-like.

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?

For a single-parameter read tool with no annotations and no output schema, the description supplies the return shape, the error/fallback behavior, the input example and the sibling alternatives. 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 0% and the lone parameter is only typed as string, so the description has to compensate — and it does, giving concrete example values ('Tomato', 'Truffle', 'Voidbloom') and the semantics of an unrecognized value. It does not state whether the match is case-sensitive or exact.

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?

Opens with a precise verb+resource+scope: the APEX price of ONE Citizens City commodity read from its on-chain AMM pool. It enumerates exactly what is returned (price, reserves/depth, fee and burn bps, tradeable/paused, minimum buy), so an agent can distinguish it from commodity_markets and commodity_swap_build without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Names both alternatives with the condition that selects each: 'For every market at once use commodity_markets; to trade, commodity_swap_build.' It also covers the failure path — an unknown name returns the list of names — which is explicit routing guidance rather than inference.

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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