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Simba MCP Server

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by getsimba-ai

Set Pipeline Schedule

set_pipeline_schedule
DestructiveIdempotent

Set or replace a pipeline's refresh schedule with daily or weekly cadence, UTC hour, and optional weekday. Enable or pause the schedule to control runs.

Instructions

Replace the refresh schedule of one owned pipeline. cadence is "daily" or "weekly"; hour_utc is a whole UTC hour 0-23; weekday (0 = Monday … 6 = Sunday) is required for weekly and must be omitted for daily; enabled false pauses the schedule and keeps its settings. Returns the schedule with next_run_at (UTC). Each due slot starts one ordinary run (poll it with get_pipeline_run); a slot is skipped while a run of that pipeline is still going. After a scheduled run succeeds the pipeline keeps its newest 30 versions; a version a model or recipe was built from is never removed. Requires the create:models scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cadenceYes
enabledYes
weekdayNo
hour_utcYes
pipeline_refYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.12.0

TDQS

A4.6/5.0
Behavior5/5

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

Adds rich behavior beyond the annotations: slot-skipping while a run is in progress, one ordinary run per due slot, the newest-30-versions retention rule with protection for versions a model/recipe was built from, and the required create:models scope. This is substantial context the annotations alone do not convey.

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?

Front-loads the core action, then layers validation rules and operational behavior. Every sentence adds value, though the version-retention detail is slightly tangential to setting a schedule and makes the description on the longer side.

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?

For a destructive/idempotent write with an output schema present, the description still covers inputs, side effects, retention consequences, scope requirement, and the resulting next_run_at. Nothing an agent needs to invoke it correctly is missing.

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 the description carries the burden and largely delivers: cadence is "daily"/"weekly", hour_utc is a whole UTC hour 0-23, weekday is 0=Monday…6=Sunday, required for weekly and omitted for daily, and enabled false pauses while preserving settings. Only pipeline_ref is left unexplained, which is a minor gap.

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?

States a specific verb+resource+scope: 'Replace the refresh schedule of one owned pipeline.' An agent can immediately tell this sets/replaces a schedule rather than polling (get_pipeline_run) or running a pipeline, and 'owned' scopes who it applies to.

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?

Gives clear operational context: 'enabled false pauses the schedule and keeps its settings', weekday required for weekly / omitted for daily, and points to get_pipeline_run for polling the resulting runs. No explicit when-not guidance or named alternative scheduler tool, but no sibling competes for this task either.

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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