mcp-fabric-api

pipeline_list_schedules

Read-only

Retrieve all schedules configured for a pipeline by supplying workspace and pipeline IDs, enabling review of pipeline automation and scheduled runs.

Instructions

List all schedules for a pipeline

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": {
      "workspaceId": "<workspaceId>",
      "pipelineId": "<pipelineId>"
    },
    "name": "pipeline_list_schedules"
  }
}

Input Schema

Name	Required	Description	Default
`pipelineId`	Yes	The pipeline ID
`workspaceId`	Yes	The workspace ID

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.8.0Sep 6, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already communicate that this is a read-only, non-destructive operation. The description adds only the word 'all' to indicate no filtering, but does not disclose output shape, pagination, ordering, or error behavior beyond what annotations imply.

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 no wasted words. Every element ('List', 'all', 'schedules', 'for a pipeline') carries meaning and contributes to understanding the tool's purpose.

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?

For a simple read-only listing tool with two fully documented parameters and safe annotations, the description is nearly sufficient. It lacks explicit output or pagination details, but those are not critical for a basic list operation with no output schema.

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?

The input schema already covers both required parameters with clear descriptions (workspaceId and pipelineId). The description adds no additional parameter-level meaning, so it meets the baseline but does not go beyond the schema.

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 uses a specific verb ('List') and a specific resource ('schedules') scoped to 'a pipeline'. This clearly distinguishes the tool from sibling tools like pipeline_list_runs, pipeline_list, and schedule management tools.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or relationship to sibling tools such as pipeline_list_runs or pipeline_create_schedule, leaving usage context entirely implicit.

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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