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klax_build_assignment_checklist

Extract submission requirements from assignment descriptions or indexed lecture materials to create a checklist with source locators.

Instructions

과제 설명(task_id) 또는 로컬에 색인된 강의자료(material_id)에서 제출 요구사항으로 보이는 문장만 규칙 기반으로 추려 locator/출처가 표시된 체크리스트를 만듭니다.

생성형 요약이나 완성 답안을 만들지 않으며, 원문 줄을 그대로 보존한 결정론적 구조화입니다. task_id와 material_id 중 최소 하나를 지정해야 합니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idNo
course_idYes
yearhakgiNo
material_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is deterministic, rule-based, preserves original lines, does not generate summaries or complete answers, and produces a checklist with locator/source information. This is a meaningful behavioral profile, though it does not mention side effects or permissions.

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 compact and front-loaded: the main action is stated first, followed by behavioral constraints and input requirements. Every sentence earns its place with no redundant or vague filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core behavior, output nature, and input constraint, and an output schema exists. However, it omits the required course_id from the usage explanation and gives no explicit guidance on when to prefer this tool over sibling tools, so the agent may under-specify the call.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It adds meaning for task_id and material_id as the two input sources and states the at-least-one requirement. However, the required course_id is not mentioned at all, and yearhakgi is also unexplained, leaving a significant gap for a required parameter.

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 states a specific verb and resource: it builds a checklist by rule-based extraction of submission-requirement sentences from task_id or material_id. It also explicitly distinguishes itself from generative summaries or complete answers, which helps differentiate it from sibling tools like klax_generate_quiz or klax_generate_study_guide_html.

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 gives clear source context (assignment description or indexed materials) and a hard usage constraint: at least one of task_id and material_id must be specified. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for basic routing.

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