solve_semester_schedule

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

With no annotations, the description carries full burden. It discloses the use of CP-SAT optimization, return of penalty_score, and that caveats are always surfaced. However, it does not detail failure modes, side effects, auth needs, or performance impacts, leaving gaps in 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 a single paragraph of four sentences, front-loaded with the main purpose, then detailing preferences and output, and ending with a usage note. Every sentence adds value with no redundancy or fluff.

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 complexity of an optimization tool with 4 parameters (2 required) and no output schema, the description covers the primary use case and mentions get_sections as a prerequisite. However, it lacks details on error handling, preference interaction, and output format specifics, making it moderately complete for an agent.

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 adds significant value by explaining k's default, that preferences may include earliest_start, latest_end, days_off, campus_preference, and that course_strings is a list. This compensates for the bare schema, though preferences structure remains loosely defined.

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 function: given course strings and a term, return conflict-free schedules using CP-SAT optimization. It specifies output includes schedules, summary, penalty_score, and caveats, distinguishing it from sibling tools like solve_degree_plan by focusing on semester scheduling.

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 explicitly instructs to use get_sections first to confirm sections exist, providing a clear prerequisite. It implies the tool is for generating conflict-free schedules with preferences, but does not explicitly state when not to use or list alternatives beyond get_sections.

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