Free: methodology comparison — the latest Argentina food & beverage index under every estimator (Jevons geometric mean, Carli arithmetic mean, trimmed mean), all computed from the same underlying data. Zero cost.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | food_beverages |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses that the tool is free and zero-cost, and that all estimates are computed from the same underlying data, which is useful behavioral context. It does not deeply cover data sourcing or limitations, but for a read-only comparison tool, this is adequate.
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 concise and front-loaded with the core purpose, using two sentences. However, 'Free' and 'Zero cost' are redundant, repeating the same information in both the label and the final phrase, which slightly detracts from conciseness.
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 tool with only one optional parameter and no output schema, the description covers the main purpose and adds context about cost and data consistency. Yet it does not describe the return format or mention the 'category' parameter, leaving some gaps for an agent to understand how to invoke it correctly.
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 schema declaration for the 'category' parameter has 0% coverage in the description; the description does not explain what this parameter does or its default value. Since the description does not compensate for the missing schema coverage, the parameter semantics are unclear, though the parameter is optional and has a sensible default.
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 clearly identifies the tool's purpose as a methodology comparison for the Argentina food & beverage index, listing specific estimators (Jevons geometric mean, Carli arithmetic mean, trimmed mean). This distinguishes it from sibling tools like get_ar_food_headline and get_ar_food_price_index, which focus on headline numbers or price index values rather than cross-estimator comparison.
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 usage for comparing estimation methodologies on the same underlying data, which is a clear context. However, it does not explicitly name alternatives or state when not to use the tool, though the distinct purpose of methodology comparison inherently sets it apart from the siblings.
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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Each tool serves a clearly distinct access pattern: headline returns a single latest value, methods compares latest values across all estimators, and price_index returns the full time series with filtering. Any potential overlap between headline and the full series is explicitly disambiguated by cross-references in the descriptions.
All tools follow the same get_ar_food_ prefix followed by a specific resource type: headline, methods, and price_index. This consistent verb_noun pattern makes the tool surface predictable and easy to navigate.
Three tools is well-scoped for a focused read-only price-index service, and each tool earns its place by covering a distinct user need: snapshot, methodology comparison, and full series access. This is within the ideal 3-15 tool range.
For a read-only data API, the set covers the core workflows: getting the latest value, comparing methodologies, and retrieving the complete historical series with subcategory filtering. No CRUD or other operations are relevant to this domain, and there are no obvious dead ends or missing access patterns.