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slidecold-mcp

by slidecold
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Python
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Start scraping

start_audience_scrape

Queues a scrape of an audience source using a specified Instagram account and sets its status to SCRAPING so contacts can be collected.

Instructions

Start scraping. Required API key scope: audiences:write. POST /audiences/{id}/scrape Queues a scrape of the audience source using the given Instagram account and sets status to SCRAPING.

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": {
      "id": "<id>",
      "body": "<body>"
    },
    "name": "start_audience_scrape"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesPath parameter `id`.
bodyYesJSON request body.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false and destructiveHint=false. The description usefully adds the required API key scope (audiences:write) and the observable side effect of setting status to SCRAPING, but it does not say what happens on a repeat call despite idempotentHint=false, nor what the response contains.

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?

Four short, front-loaded lines with no filler; the scope requirement and endpoint are easy to scan. The opening 'Start scraping.' slightly duplicates the title but serves as a summary.

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 an asynchronous mutation with a nested body and no output schema, the description omits how progress is observed (polling get_audience, using stop_audience_scrape) and what a successful call returns. It covers auth scope and the state change but leaves the operational loop unstated.

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%, so the schema already carries the parameter burden. The description adds only the meaning that accountId is the Instagram account performing the scrape, and says nothing about the optional limit parameter or its default of 20000.

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 pairs a specific verb with a specific resource and endpoint: 'Queues a scrape of the audience source using the given Instagram account'. It is clearly distinguishable from the sibling stop_audience_scrape, though it never names that sibling explicitly.

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

Usage Guidelines3/5

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

Usage is only implied by the purpose statement. There is no explicit guidance on preconditions (e.g. does the audience need a configured source first?), what to do if a scrape is already running, or which sibling to call to monitor or halt the job.

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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