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jtkehler

crowdsmart-mcp

by jtkehler

get_document_status

Read-only

Check whether CrowdSmart has extracted text from an uploaded document, returning pending, processing, completed with passage count, or failed with error.

Instructions

Show whether CrowdSmart has extracted the text of an uploaded document.

Use it when upload_document returned "processing". "status" is "pending" or "processing", then "completed" (with the number of passages) or "failed" (with the error).

Args: agent_id: Knowledge Agent ID. document_id: Document ID, from upload_document.

Input Schema

NameRequiredDescriptionDefault
agent_idYes
document_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, so safety is covered; the description adds the status lifecycle (pending/processing → completed with passage count or failed with error), which tells the agent this is a poll-until-terminal operation. It doesn't state rate limits or polling cadence, which keeps it short of a 5.

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?

Purpose is front-loaded in the first sentence, followed by the trigger condition and the status semantics; the arg list is short and earns its place. Minor noise from an unbalanced quote around "processing" but nothing substantive is wasted.

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 two-parameter read-only status check with an output schema present, the description covers what it does, when to call it, and how to interpret each returned status. Return-value detail is correctly left to the output schema.

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 0%, so the description must carry parameter meaning — and it does, labeling agent_id as the Knowledge Agent ID and document_id as coming from upload_document. It doesn't describe the ID format/pattern, but the provenance hint is the more useful information.

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 and resource — shows whether text extraction of an uploaded document has completed — and is clearly distinguishable from siblings like list_documents and read_document. The description also names the upstream tool (upload_document) that produces the document_id, anchoring it in a workflow.

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 use it when upload_document returned "processing", which is a concrete trigger condition. It doesn't name an alternative (e.g., read_document once completed), but the polling context is clear enough for correct selection.

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