Skip to main content
Glama

parsee_set_region

Меняет город, из которого смотрятся цены на Wildberries и Ozon. На WB это код пункта назначения, на Ozon — географическое положение браузера; ассистенту эта разница не важна, достаточно назвать город. Уже собранные данные не пересчитываются — после смены запустите проверку заново.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and delivers: it warns that already collected data is not recalculated, advises rerunning the check, and clarifies that underlying WB/Ozon differences are irrelevant. This is strong side-effect disclosure for a setter.

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?

Three sentences, each earning its place: action, platform nuance, and side-effect warning. No filler and the main purpose is front-loaded.

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?

For a one-parameter setter with an output schema, the description covers the essential behavior, parameter semantics, and post-condition. It could mention how to read the current region, but that is a routing nicety rather than a correctness gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description compensates: 'достаточно назвать город' tells the agent the parameter is simply a city name and platform-specific codes are not required. This adds real meaning beyond the bare string type.

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

Purpose5/5

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

The description opens with 'Меняет город, из которого смотрятся цены на Wildberries и Ozon' — a specific verb, resource, and purpose. It clearly distinguishes this setter from the sibling getter parsee_get_region.

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 gives clear context: use this tool to change the city used for price lookups, and rerun the check after changing. It does not explicitly mention alternatives like parsee_get_region, but the usage scenario is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation4/5

Most tools map cleanly to distinct resource/action pairs, and the descriptions explicitly point to complementary tools (e.g., browser_search → parse_urls → wait → get_results). The main ambiguity is the help/cloud_manual duplication and the similar price/result output of get_prices versus get_results.

Naming Consistency3/5

All tools share the parsee_ prefix and snake_case, and most follow a verb_noun pattern (create_group, get_results, set_region). However, several tools are noun-like (status, help, price_history, spp_changes, wb_cabinet) and browser_search reverses the verb_noun order, so the pattern is readable but not uniform.

Tool Count2/5

32 tools is a large surface for an MCP server, even for a broad parsing/monitoring domain. The count feels inflated because multiple cloud/help/documentation tools and several similar data-retrieval tools could be consolidated.

Completeness5/5

The tool set covers the full workflow: search/discovery, collection, task lifecycle, group management, analytics/history, scheduling, settings, export, and seller-cabinet integration. There are no obvious dead ends, and every operation has the supporting tool needed to act on its output.