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PrefectHQ

prefect-mcp-server

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by PrefectHQ

get_automations

Retrieve automations with optional filters by ID, name, or enabled state. Get compact summaries or full details including trigger config and actions.

Instructions

Get automations with optional filters.

Returns compact summaries by default (trigger_type, action_count). Filter by specific ID(s) for full detail including trigger config, actions, actions_on_trigger, and actions_on_resolve.

Filter operators:

  • id.any_: Match specific automation IDs

  • name.any_: Match automation names

  • enabled.eq_: Filter by enabled state

Examples: - List all automations: get_automations() - Full detail: get_automations(filter={"id": {"any_": [""]}}) - Get by name: get_automations(filter={"name": {"any_": ["my-automation"]}}) - Only enabled: get_automations(filter={"enabled": {"eq_": True}})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of automations to return
filterNoJSON filter object for querying automations
workspace_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
errorYes
detailNo
successYes
automationsYes
Behavior4/5

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

Without annotations, the description carries the full burden. It discloses default compact summaries and full detail via ID filtering. It could mention read-only nature but is otherwise thorough for a read operation.

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-structured with bullet points and examples, front-loaded with the core purpose. Every sentence adds value, and there is no redundancy.

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 the tool has three parameters, an output schema, and moderate complexity, the description covers all necessary context: filter operators, default behavior, and usage examples. It is complete for agent selection and invocation.

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 description adds significant value beyond the input schema by explaining filter operators, examples, and the effect on returned detail level. Schema coverage is 67%, and the description compensates well for the filter parameter.

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 the tool gets automations with optional filters, distinguishing it from sibling tools like get_flows or get_deployments by resource type. It uses specific verbs and provides filter operators and examples.

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 usage examples and filter operators, guiding when to use filters for summary vs full detail. However, it does not explicitly state when not to use this tool or mention alternatives.

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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