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get_ecommerce_performance

Retrieve e-commerce performance metrics segmented by product category and region. Input counter ID, optional currency and dates to analyze revenue and conversions.

Instructions

Get e-commerce performance by product category and region.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
counter_idYesCounter ID
currencyNoCurrency code, e.g. RUB, USDRUB
date_fromNoStart date YYYY-MM-DD
date_toNoEnd date YYYY-MM-DD

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are present, and the description does not disclose any behavioral traits such as whether the operation is read-only, authentication requirements, or rate limits. The description is minimal and leaves the agent uninformed about side effects or constraints.

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?

The description is a single concise sentence that conveys the core purpose without unnecessary words. It is well-structured and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists (not shown), the description could be more complete by indicating what the output contains (e.g., metrics by category and region). The current description provides only a high-level purpose, leaving the agent to infer details from the output schema.

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?

The input schema has 100% description coverage, so the baseline is 3. The description adds context that the data is grouped by product category and region, which is not evident from the schema parameters (counter_id, currency, date_from, date_to). This adds some value, but the description could better map the schema parameters to the grouping concept.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it gets e-commerce performance, with modifiers 'by product category and region,' which distinguishes it from sibling tools like get_page_performance or get_organic_search_performance. However, it could be more specific about what metrics are returned.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like get_page_performance or get_organic_search_performance. It does not mention prerequisites or when not to use it.

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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