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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

pipeline_status

Read-only

Retrieve a pipeline execution's current state—running, paused, completed, failed, or aborted—plus completed steps and the next step to run.

Instructions

Get the current state of a pipeline execution.

        Returns the execution state (running/paused/completed/failed/aborted),
        completed steps, and the name of the next step to run.

        Args:
            execution_id: The pipeline execution ID returned when starting 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": {
      "execution_id": "<execution_id>"
    },
    "name": "pipeline_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
execution_idYesThe pipeline execution ID returned when starting a pipeline.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.5.1
    • addedInput schema / properties / execution_id / description
      Added value: +"The pipeline execution ID returned when starting a pipeline."
  2. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing the return payload — state values (running/paused/completed/failed/aborted), completed steps, and next step — which is important since no output schema exists.

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 text is short and front-loaded: the purpose sentence comes first, return values second, and the Args block last. The Args block mildly duplicates the input schema, but the overall size is appropriate for a one-parameter tool.

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 status lookup with one required string parameter and no output schema, the description covers purpose, the shape of the returned data, and where the ID comes from. Only edge behavior (what happens for an unknown/expired execution_id) is unstated, a minor gap at this complexity.

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?

Schema coverage is 100% and the description's execution_id note is essentially identical to the schema's own description, adding no format, validation, or error semantics. With the schema doing the heavy lifting, the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource ('Get the current state of a pipeline execution') and enumerates the states it can return, so the agent knows exactly what this reports. It does not explicitly name sibling tools like list_print_pipelines or pipeline_pause/resume/abort, so differentiation is inferable rather than stated.

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

Usage Guidelines3/5

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

Usage is only implied: the parameter note ('returned when starting a pipeline') hints that this is called after starting an execution, presumably for polling. There is no explicit when-to-use, when-not-to-use, or pointer to pipeline_pause/pipeline_abort/pipeline_retry_step for acting on the reported state.

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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