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confluence_user_get

Resolve Atlassian account IDs to user records including display name, email, and account type. Handles missing or permission-denied IDs by returning stub records with error fields.

Instructions

Resolve one or more Atlassian account_ids (as emitted by author fields in confluence_comment_list, confluence_history, confluence_read, etc.) to user records — the reverse of confluence_user_search. Returns YAML with one entry per requested ID: account_id, display_name, email (when accessible), and account_type. Pass every distinct author ID from a batch in one call. Unknown, anonymised, or permission-denied IDs come back as a stub record with an error field (the batch never fails). Mirrors omni-dev atlassian confluence user get.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_idsYesOne or more Atlassian account IDs to resolve (e.g. `557058:00ce7e71-9edc-47da-a0c6-f796533ae2cd`).
Behavior5/5

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

No annotations provided, so the description carries full burden. It discloses error handling (stub record with error field, batch never fails), permission sensitivity (email when accessible), and output format. No contradictions.

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?

Concise yet comprehensive: each sentence adds value, purpose is front-loaded, and structure is clear. No redundant information.

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?

With a single simple parameter and no output schema, the description fully covers input, output, error behavior, and relationship to other tools. No gaps identified.

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% for the single parameter, and the description adds a usage optimization (batch all IDs) but does not provide additional semantic detail beyond what the schema already offers.

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 resolves account IDs to user records, specifies the return fields (account_id, display_name, email, account_type), and distinguishes it from the sibling tool confluence_user_search by calling itself the reverse.

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?

Implies usage via reverse relationship with confluence_user_search and suggests batching IDs in one call, but does not explicitly state when to use versus alternatives or provide exclusion criteria.

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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