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solve_degree_plan

Creates a semester-by-semester course plan from completed courses to a target graduation term, accommodating preferences and pinned courses.

Instructions

Plan remaining semesters from now to target_term. completed: list of course strings the student has finished. target_term: {'year': 2028, 'term': 1} where term 1=spring, 9=fall. preferences: optional dict with max_credits_per_term (int, default 18), min_credits_per_term (int, default 12), current_year, current_term. pins: optional dict mapping course_string to {'year': Y, 'term': T} to force placement. Returns a semester-by-semester plan or a structured infeasibility explanation. Always call get_requirements_progress first to show the student their remaining requirements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pinsNo
completedYes
preferencesNo
target_termYes
Behavior3/5

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

No annotations provided, so description carries full burden. It explains return behavior (plan or infeasibility explanation) and parameter effects, but lacks disclosure on side effects, idempotency, authentication needs, or behavior for past target terms.

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?

Four focused sentences: purpose, parameter explanations, output type, usage guideline. No fluff, front-loaded with intent, every sentence earns its place.

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?

Covers parameters, return type, and prerequisite call. Missing details about the structure of the returned plan or infeasibility explanation (no output schema). Also lacks behavioral notes like rate limits or mutability, but overall sufficient given tool complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet description fully explains all four parameters: completed (list of strings), target_term (dict with year/term mapping), preferences (optional with defaults), pins (optional mapping). This adds significant meaning beyond the bare schema.

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?

Description states 'Plan remaining semesters from now to target_term', clearly indicating the verb (plan) and resource (degree plan). It distinguishes from sibling tools like solve_semester_schedule (single semester) and check_eligibility.

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

Usage Guidelines4/5

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

Explicitly instructs to call get_requirements_progress first, providing a clear usage guideline. However, it does not explicitly state when not to use this tool or compare directly to alternatives.

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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