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get_users_worklog

Retrieve total work hours logged by specified users within a date range. Optionally break down hours per day, project, or issue, all in a single API call.

Instructions

Total hours a group of users logged in a date range, per user.

Uses the Tempo Timesheets API: one search covers every user in usernames for [date_from, date_to] (both inclusive) — a single request, regardless of team size or breakdown. by_user always lists each worker's total; breakdown nests that worker's own day/project/ issue split inside their entry (still one request — never call this once per user).

Args: usernames: Tempo workers (Jira usernames / keys). date_from: Start date, inclusive, YYYY-MM-DD. date_to: End date, inclusive, YYYY-MM-DD. project: Optional project key to restrict to (e.g. PROJ). breakdown: Optional per-worker grouping — day, project, issue, both (=project+issue), all, or a comma combo like day,project. Each requested dimension appears as by_day / by_project / by_issue inside every user's entry (e.g. day → hours-per-day per worker in one call).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
date_toYes
projectNo
breakdownNo
date_fromYes
usernamesYes
exclude_absenceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries full disclosure burden. It explains the single-request behavior, inclusive date range, and breakdown nesting. While it lacks details on authentication, rate limits, or error handling, the core behavioral traits are adequately covered.

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 efficiently structured with a brief summary, behavioral explanation, and parameter list. Every sentence adds value, and the format is easy to parse. No redundancy or unnecessary verbosity.

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 tool's complexity (6 parameters, no annotations, output schema exists), the description covers most aspects: core function, comparison with siblings, and parameter details. The missing 'exclude_absence' parameter and lack of response structure summary (though output schema exists) prevent a perfect score.

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?

The description explains 5 of 6 parameters with added context (e.g., breakdown options, date format). However, it omits the 'exclude_absence' parameter, which is present in the schema but undocumented. Despite this gap, the description adds significant meaning beyond the schema's property titles.

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's function: retrieving total hours logged by a group of users within a date range, per user. It distinguishes from siblings like get_user_worklog (singular) and get_team_worklog by emphasizing it handles multiple users in a single request, eliminating ambiguity.

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

Usage Guidelines5/5

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

The description explicitly advises when to use this tool (e.g., for multiple users) and warns against common misuse (e.g., 'never call this once per user'). It also implicitly suggests alternatives for single users or teams, providing clear context for tool selection.

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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