Get an employee's timesheet report showing target hours, actual hours logged, and variance. Can look up by employee name or default to the requesting user.
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | Yes | End date in YYYY-MM-DD format | |
| start_date | Yes | Start date in YYYY-MM-DD format | |
| employee_name | No | Name of the employee to look up. Leave empty or say 'me' for your own timesheet. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the tool returns a report with target/actual/variance, implying read-only behavior. But it does not explicitly disclose access requirements, rate limits, or potential errors. For a data retrieval tool, the transparency is adequate but could be improved.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the purpose, report contents, and parameter usage efficiently. No unnecessary words, and the essential information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 params, no output schema), the description covers the main purpose and parameter usage. However, it lacks details about the response format or what happens if no data exists. For a complete description, additional context about the return value would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by clarifying the employee_name semantics: 'look up by employee name or default to the requesting user' and reinforcing that it can be empty or 'me'. This goes beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('employee's timesheet report') and lists the report contents (target hours, actual hours, variance). It also differentiates from sibling tools like 'get_my_time_entries' by allowing lookup by employee name or default to self.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool (to get an employee's timesheet) and how to use the employee_name parameter (lookup by name or default to requesting user). However, it does not mention alternatives or when not to use this tool among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes, e.g., create_time_report and log_time both create a single time entry with near-identical descriptions. There are also many similar getter/list tools that blur together, making it hard for an agent to select the right one.
Most tool names use snake_case, but verbs are inconsistent: 'list' vs 'get' for similar operations, 'manage' combines create/update/delete, and 'use_favorite' is an outlier. This pattern reduces predictability.
With 114 tools, the set is extremely large and far beyond a well-scoped server (typical 3-15). This overwhelms agents and suggests many tools could be consolidated or removed.
The tool surface covers a broad domain including customers, projects, tasks, time tracking, invoicing, and user management, but there are gaps like no list_users or direct user listing, and some operations seem redundant rather than filling missing functionality.