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chapter-evaluator

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Chapter Evaluator Skill

章节评估技能

Evaluate educational chapters through dual lenses: the Student Experience (engagement, clarity, confidence) and the Teacher Perspective (pedagogy, objectives, assessment). Output structured analysis with ratings, gaps, and actionable improvements.
从双重视角评估教育类章节：学生体验（参与度、清晰度、自信心）和教师视角（教学法、教学目标、评估方式）。输出包含评分、缺口分析及可落地改进建议的结构化分析结果。

When to Use

适用场景

  • Analyzing a chapter's overall quality before publication
  • Identifying why content "feels off" (too short, boring, disconnected)
  • Planning improvements to existing chapters
  • Comparing chapters against quality standards
  • User asks to "evaluate", "review", "analyze", or "assess" a chapter
  • 发布前分析章节整体质量
  • 识别内容“违和感”的原因（过短、枯燥、关联性弱）
  • 规划现有章节的优化方案
  • 对照质量标准对比不同章节
  • 用户要求“评估”“审阅”“分析”或“评定”某一章节时

Evaluation Process

评估流程

Step 1: Gather Chapter Content

步骤1：收集章节内容

Read all lesson files in the chapter directory:
bash
ls -la <chapter-path>/*.md | grep -v summary | grep -v README | grep -v quiz
For each lesson file, extract:
  • YAML frontmatter (learning objectives, cognitive load, skills, layer)
  • Word count
  • Section structure (headings)
  • Try With AI prompts
  • Hands-on exercises
  • Code examples
读取章节目录下的所有课程文件：
bash
ls -la <chapter-path>/*.md | grep -v summary | grep -v README | grep -v quiz
针对每个课程文件，提取以下信息：
  • YAML前置元数据（学习目标、认知负荷、技能、层级）
  • 字数统计
  • 章节结构（标题层级）
  • Try With AI提示语
  • 实操练习
  • 代码示例

Step 2: Student Perspective Analysis

步骤2：学生视角分析

Evaluate as a beginner encountering this content for the first time.
以首次接触内容的初学者身份进行评估。

2.1 Engagement Score (1-10)

2.1 参与度评分（1-10分）

ScoreCriteria
9-10Compelling hook, real-world relevance clear, I want to keep reading
7-8Interesting enough, some engaging moments, minor dry spots
5-6Functional but forgettable, reads like documentation
3-4Boring, walls of text, no compelling reason to continue
1-2Would abandon after first section
Check for:
  • Opening hook (does first paragraph grab attention?)
  • Real-world scenarios (why does this matter to ME?)
  • Story/narrative flow vs disconnected facts
  • Visual breaks (diagrams, tables, code blocks)
  • Pacing variety (concept → hands-on → concept)
  • Comparative Value (vs alternatives like VS Code/Copilot)
分数评估标准
9-10开篇引人入胜，与现实场景关联明确，让人想继续阅读
7-8整体有趣，有部分吸引人的内容，存在少量枯燥段落
5-6内容可用但平淡，读起来像技术文档
3-4枯燥乏味，大段文字堆砌，没有继续阅读的动力
1-2看完第一部分就想放弃
检查要点：
  • 开篇吸引力（第一段能否抓住注意力？）
  • 现实场景关联（这对我来说有什么意义？）
  • 叙事连贯性 vs 零散知识点
  • 视觉分隔（图表、表格、代码块）
  • 节奏变化（概念讲解 → 实操 → 概念讲解）
  • 对比价值（与VS Code/Copilot等工具的对比优势）

2.2 Length Assessment

2.2 篇幅评估

VerdictCriteria
Too ShortMissing examples, concepts unexplained, abrupt endings, "I don't understand"
Just RightEach concept has sufficient depth, examples clarify, natural flow
Too LongRepetitive explanations, over-elaborated points, could cut 30%+
Word count benchmarks:
  • Conceptual lesson: 1,000-1,400 words
  • Hands-on lesson: 1,200-1,600 words
  • Installation/setup: 800-1,200 words (focused)
  • Capstone: 1,400-1,800 words
结论评估标准
过短缺少示例、概念未解释、结尾突兀，让人产生“我没看懂”的感受
适中每个概念讲解深度足够，示例清晰，过渡自然
过长解释重复、细节冗余，可精简30%以上内容
字数基准：
  • 概念类课程：1000-1400字
  • 实操类课程：1200-1600字
  • 安装/配置类：800-1200字（内容聚焦）
  • 综合项目：1400-1800字

2.3 Clarity Score (1-10)

2.3 清晰度评分（1-10分）

ScoreCriteria
9-10Crystal clear, no re-reading needed, "aha" moments
7-8Mostly clear, occasional re-read for complex parts
5-6Understandable with effort, some confusing sections
3-4Frequently confused, missing context, jargon unexplained
1-2Cannot follow, assumes knowledge I don't have
Check for:
  • Jargon introduced before defined
  • Logical flow between paragraphs
  • Transitions between sections
  • Prerequisites assumed vs stated
  • Safety Checks: No concatenated commands or risky copy-pastes
分数评估标准
9-10非常清晰，无需反复阅读，有“豁然开朗”的时刻
7-8整体清晰，复杂内容偶尔需要重读
5-6需花精力理解，存在部分易混淆章节
3-4频繁产生困惑，缺少上下文，术语未解释
1-2完全无法跟上，默认读者掌握了未提及的前置知识
检查要点：
  • 术语先定义后使用
  • 段落间逻辑连贯
  • 章节间过渡自然
  • 前置知识的默认假设 vs 明确说明
  • 安全检查：没有拼接命令或有风险的复制粘贴内容

2.4 Hands-On Effectiveness (1-10)

2.4 实操有效性评分（1-10分）

ScoreCriteria
9-10Clear steps, achievable, builds confidence, "I did it!"
7-8Mostly clear, minor ambiguity, successful completion likely
5-6Workable but confusing steps, may need to troubleshoot
3-4Missing steps, unclear what to do, likely to get stuck
1-2Cannot complete without external help
Check for:
  • Step-by-step instructions (numbered, clear)
  • Expected output/results shown
  • Troubleshooting guidance
  • Connection to concepts just learned
分数评估标准
9-10步骤清晰，可完成度高，能提升自信心，让人产生“我做到了！”的成就感
7-8整体清晰，存在少量歧义，大概率能成功完成
5-6可操作但步骤模糊，可能需要自行排查问题
3-4步骤缺失，不清楚要做什么，很容易卡住
1-2没有外部帮助无法完成
检查要点：
  • 分步说明（编号、清晰明确）
  • 展示预期输出/结果
  • 故障排除指导
  • 与刚学过的概念关联

2.5 Progression Clarity (1-10)

2.5 进阶连贯性评分（1-10分）

ScoreCriteria
9-10Clear path from start to mastery, each lesson builds on previous
7-8Generally progressive, minor jumps between lessons
5-6Some logical progression, noticeable gaps
3-4Disconnected lessons, unclear how they relate
1-2Random ordering, no clear learning path
Check for:
  • Opening connections ("In Lesson N-1, you learned X. Now...")
  • Running example threaded through chapter
  • Skills building on each other
  • Clear "what's next" at lesson end
分数评估标准
9-10从入门到精通的路径清晰，每节课都基于前序内容展开
7-8整体进阶合理，课程间存在少量跳跃
5-6有一定逻辑进阶，但存在明显缺口
3-4课程间关联性弱，不清楚彼此的联系
1-2顺序混乱，没有清晰的学习路径
检查要点：
  • 开篇关联（“在第N-1课中，你学习了X。现在我们将...”）
  • 贯穿章节的示例项目
  • 技能的逐步构建
  • 课程结尾明确说明“下一步内容”

2.6 Confidence Score (1-10)

2.6 自信心评分（1-10分）

ScoreCriteria
9-10"I can definitely do this now" - ready to apply independently
7-8"I mostly understand and could figure out the rest"
5-6"I kind of get it but would need help applying it"
3-4"I'm confused about when/how to use this"
1-2"I have no idea what I just read"
Check for:
  • Practice opportunities before moving on
  • Verification steps ("you should see X")
  • Real-world application examples
  • "Try it yourself" prompts
分数评估标准
9-10“我现在肯定能独立完成了”——已准备好独立应用所学内容
7-8“我大概懂了，剩下的可以自己摸索”
5-6“我有点懂，但应用时需要帮助”
3-4“我不清楚何时/如何使用这些内容”
1-2“我完全不知道自己刚读了什么”
检查要点：
  • 进入下一阶段前的练习机会
  • 验证步骤（“你应该看到X”）
  • 现实场景应用示例
  • “自己试一试”的提示

Step 3: Teacher Perspective Analysis

步骤3：教师视角分析

Evaluate as an instructional designer assessing pedagogical soundness.
以教学设计者的身份评估教学方法的合理性。

3.1 Learning Objectives Quality (1-10)

3.1 学习目标质量评分（1-10分）

ScoreCriteria
9-10SMART objectives, measurable, aligned to content and assessment
7-8Clear objectives, mostly measurable, good alignment
5-6Objectives present but vague or partially aligned
3-4Weak objectives, not measurable, poor alignment
1-2Missing or meaningless objectives
Check for:
  • Bloom's taxonomy verb alignment (Remember → Create)
  • Measurable criteria ("can explain", "can create", "can distinguish")
  • Assessment method specified
  • Objectives actually taught in lesson content
分数评估标准
9-10符合SMART原则，可衡量，与内容和评估方式匹配
7-8目标清晰，基本可衡量，匹配度良好
5-6有目标但模糊或部分匹配
3-4目标薄弱，不可衡量，匹配度差
1-2缺少目标或目标无意义
检查要点：
  • 与Bloom's taxonomy动词层级匹配（记忆 → 创造）
  • 可衡量的标准（“能够解释”“能够创建”“能够区分”）
  • 指定评估方法
  • 目标内容确实在课程中有所讲授

3.2 Cognitive Load Management (1-10)

3.2 认知负荷管理评分（1-10分）

ScoreCriteria
9-10Appropriate concepts for level, well-scaffolded, no overload
7-8Generally appropriate, minor overload moments
5-6Some cognitive overload, too many concepts at once
3-4Significant overload, concepts piled without consolidation
1-2Overwhelming, no chance of retention
Benchmarks by proficiency:
  • A1-A2: 3-5 new concepts per lesson
  • B1-B2: 5-7 new concepts per lesson
  • C1-C2: 7-10 new concepts per lesson
Check for:
  • New concepts counted in frontmatter
  • Concepts introduced one at a time
  • Practice before new concept introduced
  • Chunking of complex procedures
分数评估标准
9-10概念难度符合目标水平，分层合理，无过载情况
7-8整体难度合适，存在少量负荷过载的时刻
5-6存在部分认知过载，同时讲解的概念过多
3-4严重过载，概念堆砌且未进行巩固
1-2内容过于庞杂，完全无法吸收
不同熟练度的基准：
  • A1-A2水平：每节课3-5个新概念
  • B1-B2水平：每节课5-7个新概念
  • C1-C2水平：每节课7-10个新概念
检查要点：
  • 前置元数据中统计的新概念数量
  • 概念逐一引入
  • 引入新概念前有练习环节
  • 复杂流程的拆分讲解

3.3 Scaffolding Quality (1-10)

3.3 分层教学质量评分（1-10分）

ScoreCriteria
9-10Perfect progression, each concept builds on previous, no gaps
7-8Good scaffolding, minor jumps that students can bridge
5-6Some scaffolding gaps, requires prior knowledge not taught
3-4Significant gaps, assumes knowledge not in prerequisites
1-2No scaffolding, concepts appear randomly
Check for:
  • Prerequisites listed and actually prerequisite
  • Concepts introduced before used
  • Increasing complexity curve
  • Prior knowledge activated before new content
分数评估标准
9-10进阶完美，每个概念都基于前序内容，无缺口
7-8分层良好，存在少量学生可自行弥补的跳跃
5-6存在部分分层缺口，需要未讲授的前置知识
3-4缺口明显，默认学生掌握了未列入前置要求的知识
1-2无分层设计，概念随机呈现
检查要点：
  • 前置要求已列出且确实是必要的
  • 先引入概念再进行应用
  • 难度逐步提升
  • 学习新内容前激活已有知识

3.4 Pedagogical Layer Appropriateness (1-10)

3.4 教学层级适配性评分（1-10分）

LayerExpected Characteristics
L1 (Foundation)Manual-first, understand before automate, no AI shortcuts
L2 (Collaboration)AI as Teacher/Student/Co-Worker, learning through interaction
L3 (Intelligence)Pattern recognition, creating reusable intelligence (skills/subagents)
L4 (Orchestration)Capstone, combining components, spec-driven development
Check for:
  • Layer declared in frontmatter
  • Content matches layer expectations
  • Layer progression through chapter (L1 → L2 → L3 → L4)
  • No premature automation (L3 content in early lessons)
层级预期特征
L1（基础层）优先手动操作，先理解再自动化，无AI捷径
L2（协作层）AI作为教师/学生/同事，通过互动学习
L3（智能层）模式识别，创建可复用的智能体（skills/subagents）
L4（编排层）综合项目，整合各组件，基于规范的开发
检查要点：
  • 前置元数据中声明的层级
  • 内容与层级预期匹配
  • 章节内的层级进阶（L1 → L2 → L3 → L4）
  • 无提前自动化的情况（如在早期课程中出现L3内容）

3.5 Try With AI Effectiveness (1-10)

3.5 Try With AI有效性评分（1-10分）

ScoreCriteria
9-10Prompts directly extend lesson, specific, build skills
7-8Good prompts, mostly connected to content
5-6Generic prompts, loosely connected
3-4Copy-paste prompts, don't match lesson
1-2Missing or irrelevant prompts
Check for:
  • 2-3 prompts per lesson (not 1, not 5+)
  • Prompts reference lesson content specifically
  • Progressive difficulty across prompts
  • "What's you're learning" explanations present
分数评估标准
9-10提示语直接延伸课程内容，具体明确，可提升技能
7-8提示语质量好，大部分与内容关联
5-6提示语通用，与内容关联较弱
3-4复制粘贴的提示语，与课程不匹配
1-2缺少提示语或提示语无关
检查要点：
  • 每节课2-3个提示语（不是1个，也不超过5个）
  • 提示语明确参考课程内容
  • 提示语难度逐步提升
  • 包含“你正在学习的内容”的解释

3.6 Assessment/Verification Quality (1-10)

3.6 评估/验证质量评分（1-10分）

ScoreCriteria
9-10Clear verification at each step, students know if they succeeded
7-8Good verification for most exercises
5-6Some verification, students may be unsure of success
3-4Weak verification, students can't tell if they're on track
1-2No verification, students have no idea if they succeeded
Check for:
  • "Expected output" shown for commands
  • "You should see X" confirmations
  • Error states explained
  • End-of-lesson checkpoint
分数评估标准
9-10每个步骤都有明确的验证方式，学生能知道自己是否成功
7-8大部分练习有良好的验证方式
5-6有部分验证环节，学生可能不确定自己是否成功
3-4验证环节薄弱，学生无法判断自己是否在正确的轨道上
1-2没有验证环节，学生完全不知道自己是否成功
检查要点：
  • 展示命令的“预期输出”
  • 包含“你应该看到X”的确认提示
  • 解释错误状态
  • 课程结尾的检查点

Dimension Criticality & Publication Gate

维度重要性与发布门槛

CRITICAL: Not all dimensions are equally important for publication. Use this gate to determine if content is ready.
关键说明：并非所有维度对发布的重要性都相同。使用以下门槛判断内容是否可发布。

Gate Dimensions (MUST BE 7+)

核心维度（必须≥7分）

These dimensions BLOCK publication if below 7/10. Fix these first.
DimensionWhy CriticalRemediation
ClarityIf unclear, nothing works. Confused students abandon.Use 
technical-clarity
skill
ScaffoldingPoor progression breaks learning. Students can't build on prior knowledge.Use 
concept-scaffolding
skill
Layer AppropriatenessWrong layer means students lack prerequisites or are under-challenged.Redesign layer; check prerequisites
如果这些维度得分低于7/10，将阻止内容发布，需优先修复。
维度重要原因修复建议
清晰度内容模糊的话，其他一切都失去意义，困惑的学生会放弃学习使用
technical-clarity
技能
分层教学进阶逻辑混乱会破坏学习体验，学生无法基于已有知识构建新技能使用
concept-scaffolding
技能
层级适配性层级错误意味着学生缺少前置知识或内容难度不足重新设计层级；检查前置要求

Important Dimensions (6+)

重要维度（≥6分）

These should be strong but minor issues are fixable.
DimensionTargetRemediation
Engagement6+Use 
code-example-generator
for better examples
Learning Objectives6+Use 
learning-objectives
skill
Assessment/Verification6+Add verification steps; clarity checks
Cognitive Load6+Reduce concepts per lesson; add practice
这些维度需保持良好，小问题可后续修复。
维度目标分数修复建议
参与度6+使用
code-example-generator
技能优化示例
学习目标6+使用
learning-objectives
技能
评估/验证6+添加验证步骤；进行清晰度检查
认知负荷6+减少每节课的概念数量；增加练习环节

Enhancement Dimensions (5+)

优化维度（≥5分）

These are nice-to-have; publication doesn't require perfection here.
  • Progression Clarity (5+)
  • Hands-On Effectiveness (5+)
  • Confidence (5+)
  • Try With AI Effectiveness (5+)
这些维度属于锦上添花，发布时无需做到完美。
  • 进阶连贯性（5+）
  • 实操有效性（5+）
  • 自信心（5+）
  • Try With AI有效性（5+）

Publication Decision Logic

发布决策逻辑

Use this decision tree AFTER scoring all dimensions:
IF any gate dimension (Clarity, Scaffolding, Layer) < 7:
  → REVISE: Content not ready
  → Fix the failing dimension(s)
  → Re-evaluate

ELSE IF (Engagement < 6) AND (Hands-On < 6):
  → CONDITIONAL PASS: Functional but needs improvement
  → Content is usable; improvements recommended
  → Can publish with revision plan

ELSE IF any important dimension (Objectives, Assessment, Load) < 5:
  → CONDITIONAL PASS: Missing elements but learnable
  → Flag for revision; can publish

ELSE:
  → PASS ✅: Ready for publication
  → All gate dimensions 7+
  → Most important dimensions 6+
完成所有维度评分后，使用以下决策树判断：
IF 任一核心维度（清晰度、分层教学、层级适配性） <7:
  → 需修订：内容未准备好
  → 修复不达标的维度
  → 重新评估

ELSE IF (参与度 <6) AND (实操有效性 <6):
  → 有条件通过：内容可用但需优化
  → 内容可使用，同时给出改进建议
  → 可发布并制定修订计划

ELSE IF 任一重要维度（学习目标、评估/验证、认知负荷） <5:
  → 有条件通过：缺少部分元素但可学习
  → 标记需修订；可发布

ELSE:
  → 通过 ✅：可发布
  → 所有核心维度≥7分
  → 大部分重要维度≥6分

Example Decision

决策示例

Chapter Evaluation Results:
  • Clarity: 8 ✅
  • Scaffolding: 7 ✅
  • Layer Appropriateness: 8 ✅
  • Engagement: 5 (below ideal)
  • Cognitive Load: 7 ✅
  • Learning Objectives: 6 ✅
  • Assessment: 7 ✅
Decision: PASS ✅ — All gate dimensions 7+. Engagement is low, but structure is solid. Recommend: Add more compelling examples in next revision.
章节评估结果：
  • 清晰度：8 ✅
  • 分层教学：7 ✅
  • 层级适配性：8 ✅
  • 参与度：5（低于理想值）
  • 认知负荷：7 ✅
  • 学习目标：6 ✅
  • 评估：7 ✅
决策：通过 ✅ —— 所有核心维度均≥7分。参与度较低，但整体结构扎实。建议：下次修订时添加更吸引人的示例。

Step 4: Gap Analysis

步骤4：缺口分析

After scoring, identify specific missing elements:
完成评分后，识别具体缺失的元素：

Content Gaps

内容缺口

  • Missing examples (concept taught but not demonstrated)
  • Missing hands-on (theory without practice)
  • Missing "why" (what but not why it matters)
  • Missing troubleshooting (happy path only)
  • Missing transitions (lessons don't connect)
  • 缺少示例（讲解了概念但未演示）
  • 缺少实操环节（只有理论没有练习）
  • 缺少“为什么”（只讲是什么，没讲重要性）
  • 缺少故障排除（只讲顺利流程）
  • 缺少过渡（课程间无关联）

Structural Gaps

结构缺口

  • Missing opening hook
  • Missing running example continuity
  • Missing "What's Next" closure
  • Missing visual elements (all text, no diagrams/tables)
  • Missing code examples for technical content
  • 缺少开篇吸引力
  • 缺少贯穿章节的示例连贯性
  • 缺少“下一步”的收尾
  • 缺少视觉元素（全是文字，无图表/表格）
  • 技术内容缺少代码示例

Pedagogical Gaps

教学缺口

  • Objectives not assessed
  • Cognitive overload unaddressed
  • Layer mismatch (content doesn't match declared layer)
  • Prerequisites not actually prerequisite
  • Try With AI prompts disconnected from content
  • 学习目标未对应评估
  • 认知过载未处理
  • 层级不匹配（内容与声明的层级不符）
  • 前置要求并非必要
  • Try With AI提示语与内容无关

Step 5: Generate Improvement Recommendations

步骤5：生成改进建议

For each gap, provide:
  1. Problem: What's missing or wrong
  2. Impact: How it affects learning (high/medium/low)
  3. Fix: Specific action to address
  4. Effort: Estimated work (low: <30min, medium: 30-90min, high: >90min)
  5. Priority: 1 (critical), 2 (important), 3 (nice-to-have)
针对每个缺口，提供以下信息：
  1. 问题：缺失或错误的内容
  2. 影响：对学习的影响程度（高/中/低）
  3. 修复方案：具体的改进动作
  4. 工作量：预估耗时（低：<30分钟，中：30-90分钟，高：>90分钟）
  5. 优先级：1（关键），2（重要），3（锦上添花）

Output Format

输出格式

Generate analysis in this structure:
markdown
undefined
按照以下结构生成分析结果：
markdown
undefined

Chapter Evaluation: [Chapter Name]

章节评估：[章节名称]

Executive Summary

执行摘要

[1 paragraph: Overall quality assessment, key strengths, critical issues, recommendation]
[1段话：整体质量评估、核心优势、关键问题、建议]

Student Analysis

学生视角分析

Scores

评分

DimensionScoreVerdict
EngagementX/10[One-line summary]
Length[Short/Right/Long][One-line summary]
ClarityX/10[One-line summary]
Hands-OnX/10[One-line summary]
ProgressionX/10[One-line summary]
ConfidenceX/10[One-line summary]
Overall Student Experience: X/10
维度分数结论
参与度X/10[一句话总结]
篇幅[过短/适中/过长][一句话总结]
清晰度X/10[一句话总结]
实操有效性X/10[一句话总结]
进阶连贯性X/10[一句话总结]
自信心X/10[一句话总结]
整体学生体验评分：X/10

Detailed Findings

详细发现

[Specific observations per dimension with examples from content]
[每个维度的具体观察，结合内容中的示例]

Student Pain Points

学生痛点

  1. [Specific issue from student perspective]
  2. [Specific issue from student perspective] ...
  1. [学生视角的具体问题]
  2. [学生视角的具体问题] ...

Teacher Analysis

教师视角分析

Scores

评分

DimensionScoreVerdict
Learning ObjectivesX/10[One-line summary]
Cognitive LoadX/10[One-line summary]
ScaffoldingX/10[One-line summary]
Layer AppropriatenessX/10[One-line summary]
Try With AIX/10[One-line summary]
AssessmentX/10[One-line summary]
Overall Pedagogical Quality: X/10
维度分数结论
学习目标X/10[一句话总结]
认知负荷X/10[一句话总结]
分层教学X/10[一句话总结]
层级适配性X/10[一句话总结]
Try With AIX/10[一句话总结]
评估/验证X/10[一句话总结]
整体教学质量评分：X/10

Detailed Findings

详细发现

[Specific observations per dimension with examples from content]
[每个维度的具体观察，结合内容中的示例]

Pedagogical Concerns

教学问题

  1. [Specific issue from teacher perspective]
  2. [Specific issue from teacher perspective] ...
  1. [教师视角的具体问题]
  2. [教师视角的具体问题] ...

Gap Analysis

缺口分析

Content Gaps

内容缺口

GapLesson(s)Impact
[Missing element]L0XHigh/Med/Low
...
缺口涉及课程影响程度
[缺失元素]L0X高/中/低
...

Structural Gaps

结构缺口

GapLesson(s)Impact
[Missing element]L0XHigh/Med/Low
...
缺口涉及课程影响程度
[缺失元素]L0X高/中/低
...

Pedagogical Gaps

教学缺口

GapLesson(s)Impact
[Missing element]L0XHigh/Med/Low
...
缺口涉及课程影响程度
[缺失元素]L0X高/中/低
...

Improvement Recommendations

改进建议

Priority 1 (Critical)

优先级1（关键）

#ProblemFixEffortLesson(s)
1[Issue][Action]Low/Med/HighL0X
...
#问题修复方案工作量涉及课程
1[问题描述][改进动作]低/中/高L0X
...

Priority 2 (Important)

优先级2（重要）

#ProblemFixEffortLesson(s)
1[Issue][Action]Low/Med/HighL0X
...
#问题修复方案工作量涉及课程
1[问题描述][改进动作]低/中/高L0X
...

Priority 3 (Nice-to-Have)

优先级3（锦上添花）

#ProblemFixEffortLesson(s)
1[Issue][Action]Low/Med/HighL0X
...
#问题修复方案工作量涉及课程
1[问题描述][改进动作]低/中/高L0X
...

Publication Decision

发布决策

Gate Status

核心维度状态

GateDimensionScoreStatus
🚧 BLOCK if <7ClarityX/10✅/❌
🚧 BLOCK if <7ScaffoldingX/10✅/❌
🚧 BLOCK if <7Layer AppropriatenessX/10✅/❌
门槛维度分数状态
🚧 低于7分则阻止发布清晰度X/10✅/❌
🚧 低于7分则阻止发布分层教学X/10✅/❌
🚧 低于7分则阻止发布层级适配性X/10✅/❌

Publication Verdict

发布结论

Status: [PASS ✅ | CONDITIONAL | REVISE] Recommendation: [Ready for publication | Fix gates first | Needs revision plan]
状态：[通过 ✅ | 有条件通过 | 需修订] 建议：[可发布 | 先修复核心维度 | 需要制定修订计划]

Next Steps

下一步动作

If PASS:
  • Ready for publication
  • Note: Optional improvements in Priority 3 section above
If CONDITIONAL:
  • Content is functional
  • Recommended: Address Priority 1 issues in next iteration
  • Can publish now; plan revision cycle
If REVISE:
  • STOP: Fix gate dimensions first
  • [Gate dimension 1]: [Specific action]
  • [Gate dimension 2]: [Specific action]
  • Use remediation skills: [skill-1, skill-2]
  • Re-evaluate after fixes
如果通过：
  • 可发布
  • 备注：可参考优先级3的优化建议
如果有条件通过：
  • 内容可用
  • 建议：在下一版本中解决优先级1的问题
  • 可立即发布；制定修订周期
如果需修订：
  • 暂停发布：先修复核心维度
  • [核心维度1]：[具体动作]
  • [核心维度2]：[具体动作]
  • 使用修复技能：[skill-1, skill-2]
  • 修复后重新评估

Summary Metrics

汇总指标

MetricValue
Total LessonsX
Average Word CountX
Student ScoreX/10
Teacher ScoreX/10
Overall ScoreX/10
Gate Pass?Yes/No
Critical IssuesX
Estimated Fix TimeX hours
undefined
指标数值
课程总数X
平均字数X
学生视角评分X/10
教师视角评分X/10
整体评分X/10
核心维度通过？是/否
关键问题数量X
预估修复时间X 小时
undefined

Quality Reference

质量参考

Compare evaluated chapters against high-quality reference lessons. The skill should automatically identify and read a reference lesson from Part 1 or Part 6 for comparison when available.
Reference lesson patterns to look for:
  • 01-agent-factory-paradigm/01-digital-fte-revolution.md
  • 33-introduction-to-ai-agents/01-what-is-an-ai-agent.md
将评估的章节与高质量参考课程对比。当有可用参考课程时，本技能会自动识别并读取Part 1或Part 6中的参考课程进行对比。
参考课程的命名模式：
  • 01-agent-factory-paradigm/01-digital-fte-revolution.md
  • 33-introduction-to-ai-agents/01-what-is-an-ai-agent.md

Resources

资源

references/

references/

See 
references/
for detailed rubrics:
  • student-rubric.md
    - Detailed student perspective evaluation criteria
  • teacher-rubric.md
    - Detailed teacher perspective evaluation criteria
  • word-count-benchmarks.md
    - Word count guidelines by lesson type
查看
references/
目录获取详细评分标准：
  • student-rubric.md
    - 学生视角评估的详细标准
  • teacher-rubric.md
    - 教师视角评估的详细标准
  • word-count-benchmarks.md
    - 不同课程类型的字数指南