Get Spot Prices
get_spot_pricesReturns current spot prices for gold, silver, platinum, and palladium with daily change percentages
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_spot_pricesReturns current spot prices for gold, silver, platinum, and palladium with daily change percentages
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It discloses that the tool returns current spot prices and daily change percentages, but it does not mention data source, latency, currency, or whether the operation is read-only (though 'returns' implies it). This is acceptable but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that immediately states the action and the precise resource set, with no filler or redundant words. Perfectly front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple no-parameter read tool without an output schema, the description adequately covers the essential return content. It could specify the response format or units, but for most use cases it is complete enough to allow correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is fully complete by definition. Baseline 4 applies because there is nothing to document; the description correctly avoids inventing unnecessary parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Returns' and explicitly names the resources (gold, silver, platinum, palladium) plus the daily change percentages. This clearly distinguishes it from sibling tools like get_price_history, making the purpose immediately obvious.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when current spot prices are needed, but it does not explicitly state when to use this instead of get_daily_brief or get_price_history. No alternatives or exclusions are mentioned, leaving usage context implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resources and actions (portfolio, spot prices, history, COMEX vault, coin melt, receipts). However, get_portfolio and get_analytics both report cost basis and P/L, and get_daily_brief and get_stack_signal both provide market commentary, creating mild ambiguity.
All tools follow a clear verb_noun snake_case pattern, with nine get_* prefixed tools and three distinct action verbs (add_, chat_, scan_). Naming is consistent and predictable.
12 tools is well-scoped for a precious metals platform covering portfolio management, market data, and specialized calculations. Each tool serves a distinct function within that domain.
The server supports adding and reading holdings but lacks update/delete operations for holdings, creating a dead end for correcting or removing entries. Market data coverage is thorough, but portfolio lifecycle management is incomplete.