form-app

助力考生精准匹配理想院校与专业。

Security Scan

An instruction-only university/major recommendation skill whose declared behavior, requirements, and runtime instructions are internally consistent and do not request credentials or install code.

Purpose & Capability

The name/description (college/major recommendations) match the SKILL.md content. No unexpected binaries, credentials, or config paths are requested — nothing disproportionate for an advice/recommendation skill.

Instruction Scope

SKILL.md contains only prompts and example outputs for recommending schools as '冲档/稳档/保档' and handling follow-up questions. It does not instruct reading system files, environment variables, or transmitting data externally. Note: the skill does not specify where admission rank/capacity data comes from, so recommendation accuracy depends on external data sources not described in the instructions.

Install Mechanism

No install spec and no code files — instruction-only. This has minimal installation risk because nothing is written to disk or fetched during install.

Credentials

The skill declares no required environment variables, credentials, or config paths, which is proportionate for an advice-only skill.

Persistence & Privilege

always is false and the skill does not request persistent system privileges or to modify other skills. The default ability for the agent to invoke the skill autonomously is normal and not in itself a concern.

Assessment

This skill appears coherent and low-risk: it only contains runtime instructions for producing college/major recommendations and asks users to provide their exam details. Before installing, consider: (1) the skill's source/homepage is unknown — if provenance matters, prefer skills with a known author or documentation; (2) do not enter highly sensitive personal identifiers (ID numbers, full identity documents) into the skill prompts — only provide the minimal academic info needed (scores, rank, subject choices, location and preferences); (3) recommendations depend on data not described in the SKILL.md (admission ranks, last-year cutoffs). Verify any suggested schools against official admissions sources before acting; (4) test with non-sensitive or dummy inputs first to confirm the style and accuracy of outputs.

操作步骤

步骤1：用户输入关键信息 示例提问：“我的高考分数是620分，全省排名3500名，选科是物理+化学+生物，想去北京或上海，对计算机和电子信息类专业感兴趣，未来想考研，该怎么填志愿？”

步骤2：智能分析与推荐 系统输出： 冲档院校：推荐2-3所录取位次略高于用户排名的院校（如“北京航空航天大学（计算机科学与技术，去年录取位次3200名）”“上海交通大学（电子信息类，去年录取位次3000名）”），标注风险（“需服从专业调剂，避免退档”）。 稳档院校：推荐3-4所匹配度高的院校（如“华中科技大学（计算机科学与技术，去年录取位次3600名）”“同济大学（电子信息工程，去年录取位次3400名）”），说明优势（“学科评估A+，保研率25%”）。 保档院校：推荐2-3所保底院校（如“西安电子科技大学（计算机科学与技术，去年录取位次4000名）”“南京邮电大学（通信工程，去年录取位次3800名）”），强调“录取概率95%以上”。

步骤3：深度答疑与调整 用户追问：“华中科技大学的计算机和同济大学的电子信息类，哪个更适合考研？” 系统回应：“华中科技大学计算机学科评估A+，有国家重点实验室，考研方向可衔接人工智能、网络安全；同济大学电子信息类偏重通信与集成电路，与上汽、华为有合作项目，若倾向硬件领域更优。建议结合考研目标院校（如清华、浙大）的考试科目匹配度选择。