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Add Label

confluence_add_label
Idempotent

Add labels to Confluence pages, blog posts, or attachments to categorize content, track review status, and filter by topic or version.

Instructions

Add label to Confluence content (pages, blog posts, or attachments).

Useful for:

  • Categorizing attachments (e.g., 'screenshot', 'diagram', 'legal-doc')

  • Tracking status (e.g., 'approved', 'needs-review', 'archived')

  • Filtering content by topic or version

Input Schema

NameRequiredDescriptionDefault
nameYesLabel name to add (lowercase, no spaces). Examples: 'draft', 'reviewed', 'confidential', 'v1.0'. Labels help organize and categorize content.
page_idYesConfluence content ID to label. For pages/blogs: numeric ID (e.g., '123456789'). For attachments: ID with 'att' prefix (e.g., 'att123456789'). Use get_attachments to find attachment IDs.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.4.1
    • addedInput schema / additionalProperties
      Added value: +false
    • removedOutput schema / description
      Removed value: -"Generic wrapper for non-object return types."
  2. Addedv1.0.1

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnly=false, destructive=false, idempotent=true and openWorld=true, so the safety and repeatability profile is covered. The description adds the useful fact that attachments are also labelable, but says nothing about permission requirements or what happens when a label already exists on the content.

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 core action and its target are front-loaded in one sentence, and the bullet list is short. The three example bullets lean toward illustration rather than information, but nothing is long-winded.

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?

With an output schema present, annotations covering mutability/idempotency, and full schema descriptions, the description needs only to establish scope and it does. The missing piece is permission/prerequisite context for a write operation on restricted content.

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 itself is unusually rich, spelling out the numeric vs 'att'-prefixed ID formats and giving label naming conventions. The description adds no parameter detail beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Add label') and enumerates the exact resource types affected: pages, blog posts, and attachments. That scope detail is enough to separate it from confluence_get_labels in the sibling list, though the description never names that read counterpart explicitly.

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

Usage Guidelines3/5

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

The 'Useful for' bullets imply usage contexts (categorization, status tracking, topic filtering) but give no explicit when-to-use/when-not-to-use rule and never point to an alternative such as confluence_get_labels for reading existing labels. Usage is inferable rather than directed.

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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