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bach-walmart_scraper4

bach-walmart_scraper4

by BACH-AI-Tools
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

monitor_status

Check the status of a scraping task using its task ID to retrieve data when the task is complete.

Instructions

Some scraping data may take longer than average. If that's the case, you'll get a task_id. Use it to retrieve your data when it's complete.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "task_id": "<task_id>"
    },
    "name": "monitor_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
task_idYesExample value: s_m195ovji14wesgd4u1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral transparency. It states data can be retrieved when complete, but does not disclose what happens if called before completion (e.g., returns status, blocks, errors), whether the task is consumed, or any rate limits. This ambiguity is significant for a status-monitoring tool.

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?

The description is two sentences long, front-loaded with the conditional scenario, and uses no filler. Every clause contributes to understanding the tool's purpose and usage.

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

Completeness3/5

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

For a single-parameter tool with no output schema, the description gives essential context about async scraping but omits critical details like what the tool returns (status vs. data), behavior when the task is incomplete, and how the agent knows the data is ready. These are gaps given the absence of annotations and output schema.

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 schema provides 100% coverage with a simple task_id string and example. The description adds meaning by explaining that this task_id is obtained from previous scraping calls when data takes longer, which helps the agent understand the parameter's origin and purpose beyond the schema.

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 indicates the tool is for retrieving data associated with a task_id from async scraping operations. It distinguishes itself from sibling scraping tools by focusing on retrieval after completion, though it never explicitly names the action as 'monitor status' or 'check status'.

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 provides clear context: use this tool when a scraping operation returns a task_id because data takes longer than average. It implicitly tells the agent to use it for polling/completing async work, though it does not explicitly mention alternatives or when not to use it.

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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