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list_tasks

Retrieve student tasks for the current semester with optional filters for subject, type, and status, showing deadlines, points, and teacher details.

Instructions

List tasks assigned to the student. Returns task id, discipline, name, status, points (earned/max), type, deadline, and teacher. All filters are optional and default to showing everything for the current semester. semester: numeric semester ID (e.g. 27 = '2025/2026 весенний'). subject_id: numeric discipline ID to show tasks for one subject only. task_type: 0=все, 1=Курсовой проект, 2=Лабораторная работа, 3=Реферат, 4=Контрольная работа, 5=Расчетно-графическая работа, 6=Расчетное задание, 7=Эссе, 8=Отчет о практике, 9=Проверочная работа, 10=Индив. задание по ин. яз., 11=Текущее тестирование, 12=Научный доклад, 13=Отчет о науч. исслед., 14=Индивидуальное задание, 15=Практические задания, 16=Работа на занятии. show_status: 0=все, 1=только без отчета, 2=ожидающие проверки, 3=только принятые, 4=только непринятые, 5=все кроме принятых.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
semesterNo
task_typeNo
subject_idNo
show_statusNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the burden. It discloses the default semester scope and explains filter behaviors, which adds value. However, it does not explicitly state that the operation is read-only, nor does it mention pagination, ordering, or authentication requirements. Some gaps exist, but the key behavioral aspects are covered.

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?

The description is dense but well-structured: first the core purpose and return fields, then parameter details. Every sentence adds information, and the parameter mappings are comprehensive without redundancy. No fluff.

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?

The description covers all parameter semantics and defaults, making the tool usable without deeper investigation. The return field list is also mentioned, though the output schema exists. Minor gaps like pagination or empty-list behavior are not addressed, but overall completeness is high.

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?

The schema has 0% description coverage, so the description must fully compensate. It does so excellently by explaining each parameter's meaning, providing an example for semester, and listing complete numeric code mappings for task_type and show_status. This is far beyond baseline.

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?

The description begins with a specific verb and resource: 'List tasks assigned to the student.' This clearly distinguishes it from siblings like get_task (which likely retrieves a single task) and list_materials. The purpose is unambiguous.

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?

The description states that all filters are optional and default to showing everything for the current semester, giving clear context for typical usage. However, it does not explicitly mention alternatives or when not to use this tool, but the context is sufficient for basic tool selection.

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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