parsee_run_check
Запускает проверку группы: мониторинг цен или СПП. Занимает время, вернёт «задача запущена».
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| kind | Yes | ||
| group | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Запускает проверку группы: мониторинг цен или СПП. Занимает время, вернёт «задача запущена».
| Name | Required | Description | Default |
|---|---|---|---|
| kind | Yes | ||
| group | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does disclose an important trait: the operation is asynchronous and only returns a task-launched confirmation. However, it does not mention side effects, prerequisites, error behavior, or whether launching a check replaces or duplicates an existing run.
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?
The description is two short sentences, with the primary purpose stated first and the async behavior second. There is no fluff or repetition of schema fields, and every sentence adds useful information.
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?
The description covers the core behavior and immediate return value, and an output schema exists for the response. Still, it omits follow-up steps such as checking status or retrieving results via related tools, and it leaves the group parameter's format underspecified. For a simple launch operation this is adequate but not 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?
Schema coverage is 0%, so the description must explain parameters. It adds meaning by mapping the kind enum: 'monitor' corresponds to price monitoring and 'spp' to СPP. It also clarifies that 'group' is the group being checked, but it does not specify whether group is an ID, name, or other identifier.
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 action: it launches a group check, scoped to price monitoring or SPP. This clearly conveys what the tool does, though it does not explicitly distinguish itself from closely related sibling tools like parsee_monitor_changes or parsee_spp_changes.
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?
The purpose implies when to use it: when you need to start a check on a group. The statement that it takes time and returns 'task launched' gives some expectation-setting, but there is no explicit guidance about alternatives or when not to use this tool, such as using parsee_get_results or parsee_wait for outcomes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.