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astronomer

astro-airflow-mcp

Official
by astronomer
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

get_pool

Retrieve detailed information about a specific Apache Airflow resource pool, including total slots, occupied, running, queued, and open slots to monitor capacity and utilization.

Instructions

Get detailed information about a specific resource pool.

Use this tool when the user asks about:

  • "Show me details for pool X" or "What's the status of pool Y?"

  • "How many slots are available in pool Z?" or "Is pool X full?"

  • "What's using pool Y?" or "How many tasks are running in pool X?"

  • "Get information about the default_pool" or "Show me pool details"

Pools are used to limit parallelism for specific sets of tasks. This returns detailed real-time information about a specific pool's capacity and utilization.

Returns detailed pool information including:

  • name: Name of the pool

  • slots: Total number of available slots in the pool

  • occupied_slots: Number of currently occupied slots (running + queued)

  • running_slots: Number of slots with currently running tasks

  • queued_slots: Number of slots with queued tasks waiting to run

  • open_slots: Number of available slots (slots - occupied_slots)

  • description: Human-readable description of the pool's purpose

Args: pool_name: The name of the pool to get details for (e.g., "default_pool")

Returns: JSON with complete details about the specified pool

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pool_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It discloses that the tool returns real-time information about capacity and utilization, and lists all return fields. No contradictions noted.

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?

The description is well-structured with usage examples and return field definitions. Slightly verbose but front-loaded with purpose and no wasted sentences.

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?

Given an output schema exists, the description explains return values in detail. It covers the parameter, usage scenarios, and output, making it fully complete for a simple read tool.

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?

Schema coverage is 0%, so description compensates. It explains the single parameter 'pool_name' with example 'default_pool', adding meaning beyond the schema's type only.

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 clearly states 'Get detailed information about a specific resource pool.' with specific verb+resource. It distinguishes from siblings like 'list_pools' by focusing on a single pool's details. Examples of user queries reinforce the purpose.

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 explicit 'when to use' examples mimicking user queries (e.g., 'Show me details for pool X'). It does not explicitly mention when not to use or alternatives, but the context is clear and specific.

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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