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batch_archive_documents

DestructiveIdempotent

Archive multiple documents in bulk to remove them from collection views while keeping them searchable. Use for cleaning up outdated documents without deletion.

Instructions

    Archives multiple documents in a single batch operation.

    This tool processes each document sequentially, continuing even if
    individual operations fail. Rate limiting is handled automatically
    by the Outline client.

    IMPORTANT: Archived documents are removed from collections but remain
    searchable. They won't appear in normal collection views but can
    still be found through search or the archive list.

    Use this tool when you need to:
    - Archive multiple outdated documents at once
    - Clean up collections in bulk
    - Batch hide documents without deleting them

    Recommended batch size: 10-50 documents per operation

    Args:
        document_ids: List of document IDs to archive

    Returns:
        Summary of batch operation with success/failure details
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description adds behavioral context beyond annotations: documents are removed from collections but remain searchable, sequential processing with failure tolerance, and automatic rate limiting. Annotations already indicate destructive and idempotent behavior, so description complements well.

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 description is well-structured with an intro, behavioral notes, bullet points for use cases, recommended batch size, and parameter description. It is appropriately sized, though could be slightly more concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (batch operation, potential failures), the description covers sequential processing, effects on visibility, recommended batch size, and output summary. It is adequate for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description only provides minimal clarification for the single parameter 'document_ids: List of document IDs to archive.' This adds little beyond the schema's property title and type.

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 clearly states the tool archives multiple documents in a single batch operation, using specific verbs and resource. It distinguishes from sibling tools like 'archive_document' and other batch 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?

Explicit use cases are listed (archive multiple outdated documents, clean up collections, batch hide without deleting) and recommended batch size is provided. It does not explicitly state when not to use, but context 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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