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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It explains that the tool submits a job and returns {job_id, status}, and mentions privacy requirements. However, it lacks details on potential side effects, long-running nature, error conditions, or permissions needed, which limits transparency.

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 information-dense and each sentence adds value. It opens with the core action, then details the payload, and ends with privacy and cross-reference. While well-organized for plain text, it could be slightly more scannable (e.g., using bullet points for the field list), but overall it's appropriately sized.

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 complexity (many nested parameters, optional fields, special rules) and the existence of an output schema, the description covers all necessary aspects: purpose, required vs. optional fields, data format (ISO dates, IDs), edge case (vacations after end_date), and response structure. It is fully sufficient for an agent to use the tool correctly.

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?

With only one parameter 'payload' having a schema that is an open object (additionalProperties: true, 0% coverage), the description fully compensates by listing all required fields (start_date, end_date, department, employees, shifts) and many optional ones (planning_rules, wishes, etc.), plus special notes on data types and constraints. This adds significant meaning beyond the schema.

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 clearly states the tool's action: submitting a scheduling solve job ('Reicht einen Dienstplan-Solve-Job ein'). It distinguishes from siblings like 'solve_result' and 'solve_status' which are for querying results, and 'example_payload' for examples, making its unique purpose obvious.

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 detailed guidance on payload content (required and optional fields), privacy (use IDs), and a special case (vacations may contain dates after end_date). It references 'Instructions' for further context, implying when to use this tool versus others. However, it does not explicitly state when not to use it or contrast with sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.