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Bulk Update Content

bulk_update_content
Destructive

Update multiple content items simultaneously in LightCMS. Modify titles, tags, metadata, or clear fields for up to 100 items per batch operation.

Instructions

Update up to 100 content items in a single call. Use instead of calling update_content in a loop.

Each update in the array specifies the content ID and only the fields you want to change (merge semantics on data). Use clear_fields to explicitly clear field values to empty string. Set dry_run: true to validate all IDs exist without committing changes.

Returns: total attempted, succeeded, failed counts, and per-item success/error details.

Tip: call list_content with include_data: true first to get IDs + current field values, transform as needed, then submit here. Recommended batch size: up to 50 per call for optimal performance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoIf true, validate all IDs exist without saving
updatesYesArray of content updates (max 100),required
version_commentNoVersion comment applied to all updates
Behavior4/5

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

Annotations establish destructiveHint=true (mutation), while description adds merge semantics ('only the fields you want to change'), explains dry_run validation behavior, distinguishes clear_fields from merge updates, and details return structure ('total attempted, succeeded, failed counts') compensating for lack of output schema.

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?

Front-loaded with core purpose and sibling distinction; structured logically from operation definition → semantics → return values → workflow tip → optimization. No wasted words; each sentence advances understanding of how to invoke correctly.

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?

Despite lacking output_schema, description fully specifies return values ('total attempted, succeeded, failed counts, and per-item success/error details'). Covers batch limits (100 max, 50 recommended), destructive behavior (annotations + merge semantics), and workflow integration for a complex nested update operation.

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?

With 100% schema coverage, description adds crucial semantic context: explains merge semantics on data field vs explicit clearing via clear_fields, clarifies dry_run validates 'IDs exist without committing', and contextualizes version_comment as applying to 'all updates' in the batch.

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 opens with specific verb ('Update') and resource ('content items'), explicitly quantifies scope ('up to 100'), and immediately distinguishes from sibling tool 'update_content' by stating 'Use instead of calling update_content in a loop'.

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 identifies when to use this tool versus alternative ('Use instead of calling update_content in a loop'), provides workflow prerequisites ('Tip: call list_content...first'), and includes performance guidance ('Recommended batch size: up to 50 per call').

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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