Extend MCP

Get (or wait on) a workflow run

get_workflow_run

Read-onlyIdempotent

Get the state and output of a workflow run (workflows group) — resume a status: "running" run or inspect a failed one. wait: true blocks until terminal or wait-budget expiry (call again to keep waiting). Workflow runs commonly take minutes to hours — repeated running responses are normal. Follow any llmContext guidance included in results.

Input Schema

TableJSON Schema

Name	Required	Description
`wait`	No	Block until terminal or budget expiry. Default false.
`runId`	Yes	The run ID returned by run_workflow or list_workflow_runs.
`detail`	No	"concise" (default): status, output, failure fields, dashboardUrl. "full": adds config, confidence/citations, usage, timestamps.
`environment`	Yes	"TEST" = the Test (development) environment, "PRODUCTION" = live. Must match a granted target from get_me (an API key pins one environment).
`waitSeconds`	No	Max seconds to block waiting on the run (clamped to the server wait budget).
`workspaceId`	Yes	Target workspace (ws_...). Must be a granted workspace — get_me lists the accepted values.

Output Schema

TableJSON Schema

Name	Required	Description
`files`	No
`runId`	Yes
`status`	Yes	PROCESSED \| FAILED \| NEEDS_REVIEW \| REJECTED \| CANCELLED, or "running" (resume via the get tool).
`outputs`	No	Per-step output values from completed steps.
`runType`	No
`llmContext`	No
`stepSummary`	No
`dashboardUrl`	No
`failureReason`	No
`failureMessage`	No

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already mark this as read-only, idempotent, and non-destructive, so the description adds meaningful behavioral context: wait semantics, budget expiry, the expectation of repeated 'running' responses, and the instruction to follow llmContext guidance. This gives the agent a clear mental model of how the tool behaves over time.

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 compact and front-loaded with the primary purpose, then adds wait behavior, expected runtime, and instruction-following guidance. Every sentence contributes useful information without redundancy or filler.

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 read-only polling operation with an output schema and full schema coverage, the description covers all necessary operational context: what the tool returns, when waiting is appropriate, how long waits may take, and how to behave upon receiving results. Nothing essential 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 description coverage is 100%, so the baseline is 3. The description goes further by explaining the wait parameter behavior in operational terms ('blocks until terminal or wait-budget expiry', 'call again to keep waiting'), and by contextualizing runId through the workflow run lifecycle. This adds genuine value 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?

States the specific verb 'Get', the resource 'workflow run', and its core purpose: retrieving state and output. It also distinguishes its place among run-related tools by noting it operates on the workflows group and by describing the wait behavior, setting it apart from sibling get_*_run tools.

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?

Provides clear context for when to use it: resume a running workflow run or inspect a failed one. It does not explicitly name alternative tools or exclusion conditions, but the guidance around waiting and repeated running responses is strong enough for an agent to choose this tool correctly.

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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TDQS

A4/5.0

Disambiguation5/5

Each tool targets a distinct resource+action combination, and the descriptions actively disambiguate potential overlaps (e.g., extract_data vs parse_document, detect_form_fields vs edit_pdf, get_file vs get_file_upload). The consistent verb_noun prefix pattern makes the semantic boundary of every tool immediately recognizable.

Naming Consistency4/5

The dominant verb_noun pattern is highly consistent across all nine domains (list_*, get_*, create_*, update_*, delete_*, run_*, get_*_run, get_*_batch, publish_*_version). Minor deviations exist: deploy_workflow_version vs publish_*_version for the same freeze-a-draft concept, and get_form_detection_run doesn't mirror its detect_form_fields counterpart.

Tool Count2/5

86 tools is a very heavy agent-facing surface, well past the 25+ threshold. The count is inflated by the near-identical 13-tool lifecycle repeated across extract, classify, and split (each with list/get/create/update/publish/runs/batches/versions), and while each tool has a distinct purpose, the sheer volume makes selection harder.

Completeness4/5

Core lifecycles are thoroughly covered: create → update → publish → run (single and batch) → poll → cancel → delete-run → list runs/versions. Notable gaps include no delete tool for extractors, classifiers, splitters, workflows, or evaluation sets, and edit/form-detection runs have no list endpoint (documented workaround: keep run IDs). These are hygenic gaps that don't block primary workflows.

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