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getWorklogAnalytics

Aggregate worklogs by issue, account, user, day, week, or month to get hours, count, and percentage per group, sorted by hours descending. Supports analyzing worklogs for users, teams, or programs.

Instructions

Aggregate worklogs in a date range and return hours, worklog count, and percentage per group, sorted by hours descending. groupBy options: 'issue' (default), 'account', 'user', 'day', 'week' (ISO 8601), 'month'. Pass 'users' / 'program' / 'team' to analyze other people's worklogs (e.g. groupBy 'user' + program gives a per-person report for the whole program; requires 'View Worklogs' permission). Note: 'account' grouping reads the Account work attribute on each worklog — worklogs without an account attribute are bucketed as 'No account', so this grouping is only meaningful if your team uses Tempo accounts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamNoFetch worklogs of all current members of this Tempo Team (name or numeric id).
usersNoFetch worklogs of these users instead of your own. Each entry may be an email, a display name, or a Jira accountId.
endDateYes
groupByNoissue
programNoFetch worklogs of all current members of this Tempo Program (name or numeric id).
startDateYes
Behavior4/5

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

With no annotations, the description provides key behavioral details: it returns hours, count, percentage, sorted descending; explains grouping options; and notes the dependency on Tempo accounts for 'account' grouping. It mentions the 'View Worklogs' permission for accessing others' data, which adds transparency.

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 yet informative, with each sentence adding value. It is well-structured: purpose, grouping options, additional parameters with example, and a caveat. No unnecessary words.

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?

Given the absence of an output schema, the description explains the return values (hours, count, percentage) and grouping behavior. It covers the main use cases and potential pitfalls (e.g., account grouping). Minor gap: does not describe the exact format of returned data, but it's sufficient for an aggregation tool.

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 description coverage is 50% (3 of 6 parameters have descriptions). The description adds significant meaning: it elaborates on groupBy options (including default and ISO 8601 for week), clarifies the use of users/program/team, and provides a critical note about the 'account' grouping and the 'No account' bucket.

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 it aggregates worklogs over a date range and returns specific metrics (hours, count, percentage) grouped and sorted. It distinguishes itself from sibling CRUD and retrieval tools by focusing on analytics.

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?

The description explains when to use the tool (to get aggregated worklog data) and how to use additional parameters (users, program, team) to analyze others' worklogs, including the required permission. It does not explicitly state when not to use it, but the context is clear.

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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