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Get Pipeline Status

replicate_pipeline_status
Read-onlyIdempotent

Poll the status of a running pipeline to check progress and see whether each step completed, failed, or is still pending.

Instructions

Poll the status of a pipeline started with replicate_pipeline_start.

Args:

  • pipeline_id (string): Pipeline ID returned by replicate_pipeline_start.

  • include_outputs (boolean, default true): Include full PredictionResult per step. Set false for a counts-only summary while the pipeline is running.

Returns structuredContent: { pipeline_id, overall_status, total, succeeded, failed, skipped, running, pending, created_at, expires_at, steps: [{ id, model, status, prediction_id, result?, error?, skip_reason?, started_at, completed_at }] }

overall_status: "running" — steps still executing "completed" — all steps succeeded "partial" — all done, at least one failed or was skipped (failed dependency or budget error)

Note: pipeline-level errors (cycle detected, unknown depends_on) are rejected at replicate_pipeline_start with an error response — they never produce a pollable pipeline.

Tip: Poll every 10–30 seconds until overall_status is "completed" or "partial".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipeline_idYesPipeline ID returned by replicate_pipeline_start.
include_outputsNoInclude full PredictionResult per step. Set false for counts-only summary while pipeline is running. Default: true.
Behavior5/5

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

Annotations indicate read-only, idempotent, non-destructive. Description adds behavior details: polling loop, include_outputs toggle for performance, and that pipeline-level errors are caught at start, not here. No contradiction.

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?

Description is structured with sections (Args, Returns, Tip), but is somewhat long. Every sentence provides value, including the example structure and note about pipeline errors.

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?

Comprehensive for a status poller: explains return structure, statuses (running, completed, partial), and usage pattern. No output schema, but the description provides detailed structure.

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 covers both params (100% coverage). Description adds context: pipeline_id origin, include_outputs default and effect (full vs counts-only), beyond 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?

Description clearly states it polls status of a pipeline started with replicate_pipeline_start, lists return fields and statuses, distinguishing it from the start tool.

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?

Explicitly says to poll after starting a pipeline and gives polling interval tip (10-30s). Does not explicitly compare to other status tools among siblings, but usage is clear.

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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