Returns live gold price per gram from zahabprice.com — updated every ~60 seconds. Infer country from context: currency clues (ريال/SAR→sa, جنيه/EGP→eg, درهم/AED→ae, دينار→kw/bh/iq/jo), explicit location, or language. If unsure, use default.
| Name | Required | Description | Default |
|---|---|---|---|
| karat | No | Gold karat. Default: 21 (most common in Arab markets). 24K = pure gold. | |
| country | No | ISO country code. Default: sa (Saudi Arabia). Infer from context when possible. | sa |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It reveals the data source, the ~60-second update frequency, and the inference fallback behavior. It doesn't detail return format, but for a simple read tool this is adequate and adds value beyond the schema.
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 two sentences, front-loaded with the core purpose, and each sentence earns its place by providing functional detail (source, update rate, inference rules). No wasted words.
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?
Given the tool's simplicity (2 optional parameters, no nested objects, no output schema), the description covers the essential information: what it returns, where it comes from, and how to choose parameters. It stops short of stating the currency of the returned price, but that is a minor omission for a tool that likely returns prices in a locally inferred currency.
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 input schema already covers both parameters with enums and descriptions (100% coverage). The description adds practical semantics by explaining how to infer the country from user context and explicitly warns when to use the default, which is valuable beyond the raw schema.
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 opens with a specific verb ('Returns'), a specific resource ('live gold price per gram from zahabprice.com'), and an update cadence. This clearly distinguishes it from siblings like get_silver_price and calculate_installment.
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 provides explicit guidance on how to infer the country parameter from context (currency clues, location, language) and when to fall back to the default. It does not explicitly contrast with alternatives, but the context is clear and helpful.
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.
Each tool has a clearly distinct purpose: retrieving gold price, retrieving silver price, listing countries, and calculating installments. No two tools overlap in function, so an agent can easily select the right one.
All tool names follow a consistent verb_noun pattern in lowercase with underscores: get_gold_price, get_silver_price, list_countries, calculate_installment. The naming is uniform and predictable.
With 4 tools, the server is well-scoped for its purpose of providing live gold/silver prices and related purchase calculations. The count is within the ideal range and each tool earns its place.
The tool surface covers the primary domain actions: fetching prices, listing countries, and calculating installments. Minor gaps like historical price data or unit conversions exist, but they are not essential to the core workflows.
