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AI Training Jobs

Get one platform

get_platform
Read-onlyIdempotent

One platform in depth: how its screening works, tips, how and when it pays (from its own help pages, with sources), its official domain for spotting fakes, live job counts, pay and fields.

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": {
      "platform": "<platform>"
    },
    "name": "get_platform"
  }
}

Input Schema

NameRequiredDescriptionDefault
platformYesPlatform slug.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, and destructiveHint=false, so safety behavior is covered. The description adds useful provenance ('from its own help pages, with sources') and notes live job counts, but does not discuss auth, rate limits, pagination, or error behavior.

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 a single front-loaded sentence with a colon introducing the returned details. It is appropriately sized and every clause identifies valuable content rather than wasting space.

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?

With no output schema, the description carries the burden of explaining what comes back, and it does so by enumerating screening details, tips, pay timing, official domain, live job counts, pay, and fields. It is nearly complete for a simple read-only lookup, though it could clarify response shape or invalid-slug behavior.

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?

There is only one parameter, and the schema fully documents it with a 100% coverage enum of valid platform slugs. The description does not add meaning beyond the schema, so the baseline score of 3 is appropriate.

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 states a specific resource ('One platform in depth') and enumerates the detailed contents returned, letting an agent distinguish this from a broad list operation. The phrase 'one platform' also implicitly contrasts with list_platforms.

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 implied by 'One platform in depth,' but the description never explicitly says when to use this instead of list_platforms, get_job, pay_stats, or search_jobs. No exclusions or routing guidance are provided.

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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