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Macrocosmos MCP

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by macrocosm-os

get_gravity_task_status

Check a Gravity task's status and data collection progress to know if it is running, completed, or pending and how many records/bytes each crawler collected.

Instructions

Get the status of a Gravity task and see how much data has been collected.

Parameters:

  • gravity_task_id (str, REQUIRED): The ID of the gravity task to check

  • include_crawlers (bool, default: True): Whether to include detailed crawler information Set to True to see records_collected and bytes_collected for each crawler

Returns:

  • Task status (Running, Completed, Pending, etc.)

  • Task name and start time

  • List of crawler IDs (needed for build_dataset)

  • When include_crawlers=True: records_collected, bytes_collected per crawler

Example: get_gravity_task_status(gravity_task_id="multicrawler-9f518ae4-xxxx-xxxx-xxxx-8b73d7cd4c49")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gravity_task_idYes
include_crawlersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It clearly indicates this is a read-style operation ('Get the status') and details the conditional behavior of include_crawlers. It doesn't mention auth, rate limits, or error cases, but for a simple status getter the disclosed behavior is sufficient.

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 well-organized with clear Parameters, Returns, and Example sections. Each section earns its place, and the example clarifies real usage without redundancy or fluff.

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?

Despite no annotations and a minimal schema, the description provides all necessary operational context: how to invoke it, what the include_crawlers flag changes, what output to expect, and how the result connects to build_dataset. An agent can confidently select and call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description fully compensates. It explains what gravity_task_id refers to, gives the default for include_crawlers, and states the concrete effect of setting it to True (seeing records_collected and bytes_collected per crawler).

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 names a specific verb ('Get'), a specific resource ('Gravity task'), and the key insight ('how much data has been collected'). It clearly distinguishes from siblings like get_dataset_status by focusing on Gravity task 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 gives clear context by explaining what the tool returns, and even flags that crawler IDs are needed for build_dataset, implying workflow usage. However, it does not explicitly state when to prefer this tool over alternatives like get_dataset_status or how it relates to create_gravity_task/cancel_gravity_task.

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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