Store API

Каталог моделей

list_models

Read-onlyIdempotent

List available Store API models with prices in rubles per 1M tokens. Use it before ask_model to pick a model. — Список моделей Store API с ценами в рублях за 1 млн токенов.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`provider`	No	Filter by provider: openai, anthropic, google, deepseek, qwen, mistral, xai, zai

Output Schema

TableJSON Schema

Name	Required	Description	Default
`images`	No	Image models with the price of one image in rubles
`models`	No	Text models with prices in rubles per 1M tokens

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 24, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "images": {
+      "description": "Image models with the price of one image in rubles",
+      "items": {
+        "properties": {
+          "display_name": {
+            "type": "string"
+          },
+          "model": {
+            "type": "string"
+          },
+          "price_rub": {
+            "type": "number"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "models": {
+      "description": "Text models with prices in rubles per 1M tokens",
+      "items": {
+        "properties": {
+          "display_name": {
+            "type": "string"
+          },
+          "input_per_1m_rub": {
+            "type": "number"
+          },
+          "model": {
+            "type": "string"
+          },
+          "output_per_1m_rub": {
+            "type": "number"
+          },
+          "provider": {
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}

First observedSep 24, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds that prices are denominated in rubles per 1M tokens, which is useful context, but it does not disclose further behavior such as default provider handling or potential absence of results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The English sentence is concise and front-loaded, stating the core function and pricing unit immediately. The Russian translation is redundant for an AI agent but not harmful; the overall length is appropriate for the simple tool.

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

Completeness4/5

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

Given the tool's simplicity, one optional parameter, and an output schema that covers return values, the description provides sufficient context. It explains the purpose, pricing unit, and recommended usage sequence, leaving little ambiguity for correct invocation.

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?

Schema description coverage is 100%, and the only parameter 'provider' is already documented in the schema with allowed values. The description does not add extra parameter-level meaning beyond the schema, so the baseline score of 3 applies.

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 the action ('List available Store API models') and the resource (models with prices in rubles per 1M tokens). It also references the sibling ask_model, giving some differentiation, though it does not explicitly distinguish itself from compare_models.

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

Usage Guidelines4/5

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

The description explicitly says 'Use it before ask_model to pick a model', providing a concrete usage context. It does not name when not to use it or mention compare_models as an alternative, but the guidance is clear and actionable.

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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