Extend MCP

Get (or wait on) a classify run

get_classify_run

Read-onlyIdempotent

Get the state and output of a classify run (classify 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). 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 classify_document or list_classify_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
`file`	No
`runId`	Yes
`output`	No	Winning classification (PROCESSED only).
`status`	Yes	Terminal status, or "running" (resume via the get tool).
`runType`	No
`llmContext`	No
`dashboardUrl`	No
`failureReason`	No
`failureMessage`	No

TDQS

A4.5/5.0

Behavior5/5

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

The annotations already declare readOnly, idempotent, and non-destructive behavior, and the description adds meaningful non-obvious behavior: wait: true blocks until terminal or wait-budget expiry, repeated calls are needed to continue waiting, and llmContext guidance in results should be followed. No contradiction with annotations.

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?

Three sentences with no wasted words: the core purpose is front-loaded, then the wait behavior, then the llmContext follow-up instruction. Every sentence earns its place.

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?

Given the detailed input schema, the annotations, and an output schema, the description captures the essential runtime behaviors an agent needs: polling, non-terminal states, wait-budget behavior, and llmContext handling. Nothing critical for correct invocation is missing.

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 description coverage is 100%, and each parameter already has a rich description including defaults, enums, and constraints. The description adds useful behavioral framing for wait but does not meaningfully expand on parameter semantics beyond the schema, so the baseline of 3 is appropriate.

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 states a specific verb and resource: 'Get the state and output of a classify run.' It also clarifies the operational purpose—resuming a running run or inspecting a failed one—which distinguishes it from list/cancel/batch siblings without opening their schemas.

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?

The description gives clear context for when to use this tool: resume a 'running' run or inspect a failed one, and use wait: true to block. It doesn't explicitly name alternatives or exclusion cases, but the context is strong enough for an agent to select it over listing or cancellation tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Extend MCP tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources

Need Help?