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Get import status

get_import
Read-only

Read an import run's progress: status (pending, active, completed, canceled), cancel_reason, scanning (still listing folders), the target board_token (files are in sub-boards named after each folder), and files counts (total, pending, completed, skipped, failed). skipped includes files already on the board unchanged. cancel_reason on canceled: overlimit — out of storage or assets, or the next file would have crossed into storage overage the workspace has not agreed to (nothing past that point was stored); incomplete — some files failed; failed_to_start — could not start, e.g. sustained provider rate limiting; oauth_credential_deleted / target_collection_deleted — the connection or board was removed; blocked — blocked by an admin. Poll no more than every 15–30 seconds.

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": {
      "token": "<token>"
    },
    "name": "get_import"
  }
}

Input Schema

NameRequiredDescriptionDefault
tokenYesImport token returned by import_from_google_drive or import_from_dropbox
organizationNoWorkspace slug, as returned by list_organizations. Omit it when the account has a single workspace — it is then resolved from your token. Pass it only when the account has several, or when you mean a workspace other than the obvious one.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Changed3 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / context
      Removed value: -{
      -  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
      -  "type": "string"
      -}
    • changedInput schema / required
      Previous value: -[
      -  "token",
      -  "context"
      -]New value: +[
      +  "token"
      +]
  3. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the readOnlyHint/destructiveHint annotations, the description adds substantial behavioral context: the full status value set, what `skipped` means, the meaning of each cancel_reason including the storage-overage side effect ("nothing past that point was stored"), and a polling rate constraint. This is exactly the kind of information an agent needs to interpret results correctly.

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 returned fields are front-loaded before the long cancel_reason enumeration, and the polling constraint closes the description sensibly. The cancel_reason list is dense and semi-colon-packed, but every entry carries decision-relevant meaning rather than 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?

There is no output schema, so the description must carry the return-value burden, and it does so by naming every field and decoding the ambiguous ones (`skipped`, each `cancel_reason`). For a simple two-parameter status read, nothing essential 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%, so both `token` and `organization` are already documented in the schema itself. The description adds no parameter-level meaning beyond confirming the token refers to an import run, so the baseline of 3 applies.

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?

"Read an import run's progress" is a specific verb+resource, and the description immediately enumerates the exact fields returned (status, cancel_reason, scanning, board_token, files counts). It is clearly distinct from the sibling import_from_google_drive / import_from_dropbox tools that create imports rather than report on them.

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?

It gives concrete operational guidance ("Poll no more than every 15–30 seconds"), which tells the agent how to use the tool without hammering the API. It stops short of explicitly naming the sibling tools that produce the token or stating when not to call it, but the context for use 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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