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veroq_commodities

Access real-time commodity market data including gold, silver, oil, and natural gas prices with change percentages and units.

Instructions

Get commodity prices (gold, silver, oil, natural gas, etc.). No arguments returns all; pass a slug for one commodity.

WHEN TO USE: For commodity market data. Covers precious metals, energy, and industrial commodities. RETURNS: Price, change, change percent, and unit per commodity. COST: 2 credits. EXAMPLE: { "symbol": "gold" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoCommodity slug (e.g. gold, silver, crude, natural_gas, copper, platinum). Omit for all.
Behavior4/5

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

No annotations provided, so description carries full disclosure burden. Provides 'RETURNS' section detailing response structure (price, change, change percent, unit), 'COST' section disclosing rate limits (2 credits), and clarifies read-only nature through 'Get' verb. Could mention data latency (real-time vs delayed) but covers primary behavioral traits.

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?

Perfectly structured with clear headers (WHEN TO USE, RETURNS, COST, EXAMPLE). Front-loaded with core action. No redundant text; every line provides distinct value (usage context, return schema, cost constraints, syntax example). Excellent information density.

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 tool with no output schema, the description is comprehensive. Compensates for missing output schema by documenting return values in text. Parameter semantics, cost structure, and usage patterns are fully explained. No gaps remain for agent invocation.

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 100%, establishing baseline of 3. Description adds value by providing concrete JSON example ('{ 'symbol': 'gold' }') and explicitly clarifying the optional behavior ('No arguments returns all'), which goes beyond the schema's basic parameter definition.

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?

Description opens with specific verb 'Get' and resource 'commodity prices', lists concrete examples (gold, silver, oil, natural gas), and clearly distinguishes from siblings like veroq_crypto and veroq_forex by specifying commodity asset classes (precious metals, energy, industrial commodities).

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?

Includes explicit 'WHEN TO USE' section defining scope (commodity market data, precious metals, energy, industrial). Explains parameter behavior (omit for all, pass slug for one). Lacks explicit 'when not to use' or named sibling alternatives, but domain is distinct enough from the 40+ siblings to prevent confusion.

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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