law-student-exam-forecast SKILL.md skillA

law-student-exam-forecast from yuandian-ailaw/agent-for-legal-cn is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add yuandian-ailaw/agent-for-legal-cn/law-student-exam-forecast@git:20260529.efece30

Pins git:20260529.efece30 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
yuandian-ailaw/agent-for-legal-cn
Path
legal-skillpack-law-student/skills/law-student-exam-forecast/SKILL.md
Versions recorded
1
Latest version
git:20260529.efece30, committed May 29, 2026
Size
11,517 bytes
Repository stars
16
License
a license file GitHub does not identify

分析同一教师的历年试题以揭示模式——科目权重、反复出现的高频考点、 偏好的假设类型、政策vs法条比例——并预测考试重点。当用户说"考试考什么"、 "分析历年试题"、"预测考试"或分享历年试题时触发。.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# /exam-forecast

1. 加载 `$LEGAL_AGENT_PROFILE_HOME/law-student/profile.md` → 课程、考试形式、教学大纲。
2. 应用下方工作流。
3. 接收历年试题(粘贴或路径)。确认样本量。
4. 分析每份历年试题:形式、科目覆盖、题型、知识点密度、高频考点。
5. 交叉试题模式分析——哪些稳定、哪些变化。
6. 结合当前教学大纲产出预测:科目权重、形式、教师偏好、学习重点。
7. 写入 `exam-forecasts/[课程]/forecast-[YYYY-MM-DD].md`。框定为权重启发式,非确定性预测。

---

## 目的

每个教师的考试都有指纹。同样的假设结构反复出现。同样的考点反复回来。同样的科目比例重复。有历年试题的学生学得更聪明;没有的学得更苦。本技能分析你手中历年试题并揭示模式。

不是魔法。是预测框架,不是确定性预测。技能不能告诉你考试考什么——能告诉你历年考过什么以及基于教学大纲覆盖什么可能再次出现。

## 两种考试模式

本技能支持两类预测,通过标记切换:

**法学院期末考试模式(`--期末`,默认):** 基于同一教师历年试题分析。
**法考预测模式(`--法考`):** 基于历年法考真题考点分布分析客观题/主观题重点。

## 置信度标注

- 模式分析(什么科目出现、每主题多少题、法条分析vs论述频率)——试题在面前时可信。
- 考试重点推论——`[不确定]` 是默认;这是预测框架。明确框定为"基于你分享的[N]份历年试题,[主题]出现了[M]次。考试可能强调它,教师也可能轮换——用于复习时间权重,非确定性预测。"
- 仅1-2份历年试题→视为"珍贵样本"而非"薄样本"。1-2份试题虽然无法做统计意义上的频率推断,但仍能提供教师出题风格、题型偏好和难度定位等关键定性信息。标注为"基于珍贵样本(N=1或2)——以下分析侧重题型风格和难度定位,不做频率推断。"
- 教师是新的(无历年试题)→切换到下方的"教学大纲推断模式",基于教学大纲结构和课程类型进行推断。标注 `[不确定 —— 教学大纲推断模式]`。
- 法考预测基于历年分值分布,但每年的具体分值可能变化,标记 `[不确定——法考命题趋势]`。

## 加载上下文

- `profile.md` → 当前课程、考试形式、教学大纲
- 用户提供的历年试题
- 可选:当前课程教学大纲(用于"当前已覆盖什么")

## 工作流

### 第1步:接收

- 预测哪个课程?
- 该教师有多少份历年试题?
- 同一课程还是不同课程?
- 有当前课程教学大纲吗?

如需法考预测模式:获取法考历年真题考点分布数据(通过 web_fetch 或用户提供)。
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add yuandian-ailaw/agent-for-legal-cn/law-student-exam-forecast@sha256:cb0c4a9845d3e53a

The line at the top of this page pins the label git:20260529.efece30, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_ixx3m6b7h3xzrmse.svg)](https://markdownregistry.com/a/art_ixx3m6b7h3xzrmse)

4 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on May 29, 2026.

versioncommittedcommitsizeaudit
git:20260529.efece30 latest2026-05-29 efece30 11,517 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (11517 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

yuandian-ailaw/agent-for-legal-cn · 16 stars · license a license file GitHub does not identify · pushed 2026-09-10 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_ixx3m6b7h3xzrmse
GET https://markdownregistry.com/api/v1/resolve?ref=yuandian-ailaw/agent-for-legal-cn/law-student-exam-forecast
GET https://markdownregistry.com/api/v1/blob/cb0c4a9845d3e53a7bb5e94f49eb31633fcaca254ad2481874ad0fc57c04ac06

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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