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laserfiche_task_get_status

Retrieve the current status and details of an asynchronous task by providing its operation token. Returns progress, completion, or error information.

Instructions

Look up the status of an async operation by its token.

The async tools (delete_entry, copy_entry, sometimes import_document) return an operation_token instead of the final result — call this to check whether the operation finished. For "wait until done" semantics, use wait_for_task instead so you don't have to write a polling loop.

Args: operation_token: The string token returned by the originating async tool.

Returns: Server's task payload — operationToken, operationType, percentComplete, status (one of NotStarted, InProgress, Completed, Failed, Canceled), redirectUri (set when the op produced a new entry, e.g. after a copy), entryId (the resulting entry's ID when applicable), errors (list — empty on success), and timestamps.

On failure: returns {"mode": "error", "error": <slug>, "operation_token": <str>, ...}. Common slugs: not_found (token unknown — usually expired or from a different server instance), auth_failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operation_tokenYesOperation token returned by an async tool (delete_entry, copy_entry, occasionally import_document). Server-scoped; tokens from a different server instance won't resolve.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Despite no annotations, the description fully discloses the behavior: it is a read-only status check, details the return payload structure, and explains failure modes with common error slugs like 'not_found' and 'auth_failed'.

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?

Description is front-loaded with the core purpose, followed by context, usage guidance, and detailed returns/errors. Every sentence is informative and well-organized without redundancy.

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 tool's simplicity (one parameter) and the presence of an output schema, the description covers all necessary aspects: purpose, usage, parameter, return values including fields and possible errors, and differentiation from sibling tools.

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 coverage is 100% and the schema already includes a description and examples for the single parameter 'operation_token'. The description adds minimal additional context (e.g., mentioning which tools return the token), but the schema carries the bulk of the semantics.

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 'Look up the status of an async operation by its token', specifying the verb (look up), resource (status of async operation), and mechanism (by token). It also distinguishes from the sibling 'wait_for_task' by explaining the difference in semantics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides guidance on when to use this tool versus alternatives: 'For "wait until done" semantics, use wait_for_task instead so you don't have to write a polling loop.' Also lists the originating async tools that return the token.

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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