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ars-nova-wordpress-mcp

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Bulk Update Posts from CSV

wp_bulk_update_posts
DestructiveIdempotent

Update many WordPress posts from a CSV file, setting fields like title, content, status, categories, and tags. Empty cells preserve existing values, and dry-run mode previews changes before applying.

Instructions

Update many posts from a CSV. Required column: id. Optional: title, content, status, slug, excerpt, categories (comma-separated IDs), tags (comma-separated IDs), featured_media. Empty cells are SKIPPED (no change to that field). Defaults to dry_run=true.

Args:

  • csv_path (string): Path to CSV file. Required.

  • dry_run (boolean): Default true. Set false to apply changes.

  • stop_on_error (boolean): Default false.

  • response_format (enum): markdown | json. Default 'markdown'.

Use case: backfill categories on the 45 "Uncategorized" posts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoDefault true. Set false to actually write.
csv_pathYesPath to CSV. Required columns: id. Optional columns: title, content, status, slug, excerpt, categories (comma-sep IDs), tags (comma-sep IDs), featured_media.
stop_on_errorNoDefault false (continue on errors). True = stop at first error.
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readable.markdown
Behavior4/5

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

Annotations indicate a destructive, write operation. The description adds valuable behavior: empty cells are skipped, defaults to dry_run=true, and explains parameters like stop_on_error. This context goes beyond the annotations without contradicting them.

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?

The description is compact yet thorough, with a clear intro, an args list, and a relevant use case. Every sentence adds value, and the structure is easy to parse.

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?

Despite no output schema, the description covers the input format, key behaviors, and output format options. It is complete for a bulk update tool but omits details about error reporting beyond stop_on_error and what the response contains.

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 coverage is 100%, so baseline is 3. The description adds meaningful context about the CSV format (required id, optional columns, empty-cell skipping) that clarifies parameter behavior beyond individual schema descriptions, especially the combined effect of csv_path and dry_run.

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 updates many posts from a CSV, listing the specific fields and required column. It distinguishes itself from sibling bulk operations by targeting posts specifically and using CSV input, with a concrete use case.

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?

Provides a clear use case (backfill categories on 45 'Uncategorized' posts) and conveys the tool is for bulk CSV-based updates. It does not explicitly exclude alternatives like single-post updates or term-only bulk assignment, so it falls short of full alternative guidance.

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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