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Mcs List Commodities

mcs_list_commodities
Read-onlyIdempotent

Browse the ~85 nonfuel mineral commodities covered by the USGS Mineral Commodity Summaries (MCS) annual data release — lithium, copper, cobalt, rare earths, gold, aluminum, nickel, platinum-group metals, and dozens more, through industrial minerals like barite and feldspar. Each entry names its U.S. statistics columns (production, imports, exports, price, employment, net import reliance — varies by commodity) and whether a world production/reserves-by-country table is also available (mcs_country_comparison). Optional substring query over commodity name or code. Keyless.

Input Schema

NameRequiredDescriptionDefault
limitNoMax commodities to return, default 100, max 200.
queryNoOptional substring filter over commodity name or code, e.g. "earth" or "iron".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare this a safe, idempotent, open-world read. The description adds genuinely useful context beyond that: it is 'Keyless' (no auth needed) and it describes the shape of each returned entry — which statistics columns it carries and whether a country-comparison table exists. It does not mention pagination or limits, but the behavioral disclosure is solid.

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?

Front-loads the purpose and stays to a single dense paragraph with no redundant sentences. The illustrative commodity list ('dozens more') is slightly padded but does convey the domain vocabulary an agent might match against.

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?

With no output schema, the description must explain returns, and it does — statistics columns per entry and country-table availability. The only gap is that the limit parameter's behavior (default 100, max 200) is left entirely to the schema, which is acceptable for a low-complexity two-param list 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 100% and the schema documents both parameters, including the substring example and limit defaults. The description restates that the query is an optional substring over name or code but adds no format, matching, or case details, and never mentions limit. Baseline 3 is appropriate.

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?

States a precise verb and resource — browsing/list of the ~85 nonfuel mineral commodities in the USGS MCS dataset — and enumerates concrete members (lithium, copper, cobalt, rare earths). It implicitly separates itself from mcs_commodity_data (which fetches per-commodity stats) and mcs_country_comparison (which it explicitly notes as the country table tool).

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?

Positions the tool as the catalog/browse entry point and explicitly points to mcs_country_comparison when a world production/reserves-by-country table is wanted. It stops short of explicitly ruling out mcs_commodity_data for row-level data, so the routing is clear for the country case but not fully spelled out for the data case.

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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