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confluence_search_user

Search Confluence users using CQL queries and retrieve a JSON list of simplified user profiles matching your criteria.

Instructions

Search Confluence users using CQL.

Args: ctx: The FastMCP context. query: Search query - a CQL query string for user search. limit: Maximum number of results (1-50).

Returns: JSON string representing a list of simplified Confluence user search result objects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results (1-50)
queryYesSearch query - a CQL query string for user search. Examples of CQL: - Basic user lookup by full name: 'user.fullname ~ "First Last"' Note: Special identifiers need proper quoting in CQL: personal space keys (e.g., "~username"), reserved words, numeric IDs, and identifiers with special characters.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the CQL query format, includes quoting examples, and specifies a JSON return value. However, it does not mention read-only status, authentication requirements, potential errors, or pagination behavior beyond the limit parameter.

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 concise and includes a clear Returns line. However, the Args section duplicates the parameter information already present in the schema, adding minor redundancy. It remains appropriately sized and well-structured.

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

Completeness3/5

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

For a relatively simple search tool, the description covers purpose, parameters, and return format. However, it lacks usage guidance and deeper behavioral context, such as read-only status or how it handles invalid CQL. The presence of an output schema reduces the need for return structure details, but the description could be more complete.

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?

The input schema already provides detailed descriptions for both parameters (100% coverage), so the description's Args block adds little new meaning beyond restating the schema. The schema itself includes examples and quoting guidance, making the description redundant in this dimension.

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 'Search Confluence users using CQL' which identifies a specific verb+resource and distinguishes it from sibling content search tools like confluence_search. The Returns line further clarifies that it produces a list of user search result objects, making the purpose unambiguous.

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?

No explicit guidance is given on when to use this tool versus alternatives like confluence_search or jira_get_user_profile. The usage context is implied by the tool name and description, but there are no named alternatives or exclusion criteria, leaving the agent to infer the appropriate scenario.

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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