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parsee_status

Что сейчас происходит в приложении: версия, вход в аккаунт и тариф, вход на Ozon и Wildberries, идёт ли сбор и на каком он шаге, сколько карточек уже собрано. Стоит вызывать перед долгими действиями: если сбор уже идёт, второй запускать не нужно.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries full burden for behavioral disclosure. It discloses what status information will be surfaced and implies that calling it does not start collection, but it does not explicitly state that it is read-only or describe any side effects or limits.

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?

Two tight sentences: the first enumerates the status fields, the second gives a practical reason to call the tool. Every clause adds value, and the most important usage guidance is placed at the end without padding.

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

Completeness5/5

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

For a parameterless status tool with an output schema present, the description is complete. It tells the agent what to expect, why it matters before long actions, and what to watch for (an already-running collection). Nothing essential is missing.

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?

The tool has zero parameters and the input schema is an empty object, so there is nothing for the description to explain. The baseline for a parameterless tool is 4, and the description appropriately focuses on the returned status content rather than inputs.

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 explains what the tool reports: app version, account/tariff, Ozon/Wildberries login state, collection progress, and collected card count. It is distinct from sibling tools because it is a status snapshot rather than a configuration, execution, or export action, though it does not explicitly name a competing sibling.

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 explicit usage context: call before long-running actions to avoid starting a second collection if one is already in progress. This is a clear when-to-use and when-not-to-use signal, but it does not identify an alternative tool by name.

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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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.