optimize_schedule

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

With no annotations, the description fully discloses default behavior, override logic, and return values. It even characterizes each algorithm (e.g., 'greedy (front-load)') and notes the start_date default to server time. This is comprehensive behavioral disclosure.

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 well-structured with a clear purpose statement, followed by behavior explanations and Args/Returns sections. Every sentence adds value, and the long algorithm list is necessary for correct tool use.

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 (6 parameters, 9 algorithms, no schema descriptions or annotations), the description covers all necessary aspects: parameters, defaults, edge cases, and output structure. It also directs users to list_algorithms() for further discovery, completing the contextual picture.

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 description coverage is 0%, so the description compensates fully by explaining every parameter in Args, including examples, formats, and defaults. The algorithm parameter lists all accepted values with brief semantic descriptions, far exceeding schema capabilities.

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 opening line 'Auto-generate optimal task schedules' clearly states the verb and resource. The description goes on to detail scheduling behavior, algorithm options, and exceptions, making it distinct from sibling task CRUD tools.

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 explains defaults ('weekdays only', 'skips tasks that already have a planned_start') and conditional parameter usage (force_override, include_all_days). It references list_algorithms() for discovery but does not explicitly compare with alternative scheduling approaches or tools.

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