מדד מחירים לפי רשת
chain_price_indexPrice index of each retail chain WizStore covers (100 = national median basket; below 100 is cheaper), cheapest first, with store counts.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
chain_price_indexPrice index of each retail chain WizStore covers (100 = national median basket; below 100 is cheaper), cheapest first, with store counts.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds real behavioral context the annotations cannot: the index baseline (100 = national median basket), the direction of the scale (below 100 is cheaper), and the ordering and inclusion of store counts.
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?
A single sentence with no filler; the key interpretation rule (100 = national median, below 100 cheaper) is embedded where it is needed and the ordering/content facts follow immediately. Nothing could be removed without losing meaning.
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?
With no output schema, the description must carry the return shape, and it does: index values, their scale, ordering, and the presence of store counts. It does not state how many chains are returned or whether the list can be empty, but for a zero-argument aggregation tool this is nearly complete.
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?
There are zero parameters, so per the baseline a 4 is appropriate. The description implicitly confirms the call takes no filters by saying the index covers every chain WizStore covers, which matches the empty input 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 states a specific resource (price index per retail chain) and adds the scale semantics and ordering, so an agent knows exactly what it returns. It does not explicitly distinguish itself from the similar sibling compare_basket_by_chain, so it falls short of the top mark.
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?
Usage is only implied: the description makes clear this is a cross-chain overview (cheapest first, with store counts), which suggests when it is useful, but there is no explicit when-to-use or when-to-prefer-alternatives guidance versus siblings like compare_basket_by_chain or cheapest_stores_in_city.
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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