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Agent Skill · 待分类

curriculum-iterate-feedback(课程迭代反馈)

curriculum-iterate-feedback 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

curriculum-iterate-feedback 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 9,872。

总安装 220周安装 9GitHub Stars 1下载 71核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:curriculum-iterate-feedback(课程迭代反馈)
来源仓库:https://github.com/pauljbernard/content
仓库路径:skills/curriculum-iterate-feedback
安装命令:
npx skills add https://github.com/pauljbernard/content --skill curriculum-iterate-feedback
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/pauljbernard/content --skill curriculum-iterate-feedback

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

curriculum-iterate-feedback 用于综合分析多源反馈,识别课程改进机会并制定实施计划。适用于分析学生反馈、成果数据和改进建议,规划课程修订和版本跟踪。需输入反馈来源、当前课程和历史数据,系统将输出高影响力改进建议和版本策略。安装前建议确认权限范围、维护状态,以及是否会触发联网或文件读写。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/curriculum-iterate-feedback

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/pauljbernard/content --skill curriculum-iterat…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

curriculum-iterate-feedback 怎么安装?

在终端执行 npx skills add https://github.com/pauljbernard/content --skill curriculum-iterate-feedback。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

curriculum-iterate-feedback 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

curriculum-iterate-feedback 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

curriculum-iterate-feedback 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

curriculum-iterate-feedback 用的人多吗?

公开数据是累计安装 220 次,近一周安装 9 次,下载 71 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

curriculum-iterate-feedback 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
curriculum-iterate-feedback

课程迭代反馈 · 本页

2201只读MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Feedback Analysis & Revision Recommendations

Synthesize multiple feedback sources to identify high-impact curriculum improvements with implementation guidance and version tracking.

When to Use

  • Analyze student feedback
  • Review outcome data for patterns
  • Synthesize improvement opportunities
  • Plan curriculum revisions
  • Track version effectiveness

Required Inputs

  • Feedback Sources: Student surveys, peer reviews, outcome data
  • Current Curriculum: Materials to potentially revise
  • Historical Data (optional): Previous version effectiveness
  • Context: Constraints, resources, timeline

Workflow

1. Gather All Feedback Sources

Collect:

  • Student Feedback: Surveys, course evaluations, informal comments
  • Outcome Data: From /curriculum.analyze-outcomes
  • Peer Review: Other educator observations
  • Self-Reflection: Instructor notes, observations
  • Stakeholder Input: Admin, parents, industry partners

2. Synthesize Feedback by Theme

# Feedback Synthesis: [COURSE/UNIT]

**Review Period**: [Date Range]
**Feedback Sources**: [List]
**Current Version**: [Version number]

## Feedback Themes

### Theme 1: Content Pacing Too Fast

**Sources**:
- Student surveys: 18/30 students (60%) reported feeling rushed
- Outcome data: Unit 2 objectives only 45% mastery (lowest in course)
- Instructor observation: "Struggled to finish Unit 2 in time"

**Specific Comments**:
- "We moved through Unit 2 so quickly I didn't understand photosynthesis before the test."
- "Need more practice time before assessments."
- "Felt like we skipped over important concepts."

**Evidence Strength**: ⭐⭐⭐⭐⭐ (Strong - multiple convergent sources)

**Impact Assessment**: HIGH - Directly affects learning outcomes

### Theme 2: Lack of Real-World Applications

**Sources**:
- Student feedback: "Why does this matter?"
- Peer review: "Could benefit from authentic tasks"

**Specific Comments**:
- "I don't understand why we need to know this."
- "When will I use this in real life?"

**Evidence Strength**: ⭐⭐⭐ (Moderate - consistent but limited sources)

**Impact Assessment**: MEDIUM - Affects engagement and transfer

### Theme 3: Assessment Too Memorization-Heavy

**Sources**:
- Student feedback: "Just memorize and forget"
- Outcome data: High Remember-level performance (85%) but low Apply-level (58%)
- Bloom's analysis: 70% of items at Remember/Understand level

**Specific Comments**:
- "Tests are all memorization, not understanding."
- "I got an A but still don't really get it."

**Evidence Strength**: ⭐⭐⭐⭐ (Strong - multiple objective sources)

**Impact Assessment**: HIGH - Shallow learning, not meeting objectives

[Continue for all themes identified]

3. Identify Root Causes

For each theme, analyze WHY:

## Root Cause Analysis: Pacing Too Fast

**Symptoms**:
- Low mastery rates in Unit 2
- Student complaints about speed
- Not enough practice time

**Possible Causes**:
1. ✅ **Too much content in Unit 2** (5 objectives in 2 weeks)
   - Evidence: Unit 1 had 3 objectives in 2 weeks (80% mastery)
   - Evidence: Unit 3 had 4 objectives in 3 weeks (70% mastery)
2. ✅ **Insufficient scaffolding**
   - Evidence: Direct transition from simple to complex concepts
   - Evidence: No intermediate practice activities
3. ⚠️  **Prerequisites not mastered** (possible but less clear)
   - Evidence: Unit 1 had good mastery (80%), so prerequisites likely OK
4. ❌ **Ineffective instruction** (unlikely)
   - Evidence: Other units performing adequately with same methods

**Most Likely Root Causes**:
1. Content overload (5 objectives too many for 2 weeks)
2. Insufficient scaffolding and practice

**Recommended Fixes**:
1. Split Unit 2 into two 2-week units (2.A and 2.B)
2. Add intermediate practice activities between concepts
3. Include more worked examples and guided practice

4. Generate Prioritized Recommendations

# Curriculum Revision Recommendations

**Course**: [Name]
**Current Version**: 1.0
**Next Version**: 1.1 (or 2.0 if major changes)
**Recommendation Date**: [Date]

## Priority 1: Critical Revisions (Must Do)

### Recommendation 1.1: Extend Unit 2 Timeline

**Issue**: Content pacing too fast in Unit 2, leading to low mastery (45%)

**Root Cause**: 5 objectives in 2 weeks is too much content

**Proposed Change**: Split Unit 2 into two units:
- Unit 2A: LO-2.1, LO-2.2 (2 weeks)
- Unit 2B: LO-2.3, LO-2.4, LO-2.5 (2 weeks)

**Expected Impact**:
- Increase mastery rate from 45% to target 70%
- Reduce student stress and rushing
- Allow adequate practice time

**Implementation Effort**: MEDIUM
- Restructure 2 lessons
- Adjust pacing guide
- Create new formative assessment

**Implementation Timeline**: 2 weeks before next course iteration

**Success Metrics**:
- Unit 2A mastery ≥70%
- Unit 2B mastery ≥70%
- Student feedback: <30% report feeling rushed

### Recommendation 1.2: Increase Higher-Order Assessments

**Issue**: Too much emphasis on memorization (70% Remember/Understand items)

**Root Cause**: Assessment items don't match Apply/Analyze objectives

**Proposed Change**: Revise assessment blueprint:
- Reduce Remember items from 14 to 7
- Increase Apply items from 5 to 10
- Add 3 Analyze items

**Expected Impact**:
- Better measure of true understanding
- Force deeper learning (not just memorization)
- Align assessment to stated objectives

**Implementation Effort**: HIGH
- Rewrite 10-15 assessment items
- Update rubrics
- Field test new items

**Implementation Timeline**: 4 weeks

**Success Metrics**:
- Apply-level performance ≥70% (currently 58%)
- Student feedback: <20% report "just memorization"

## Priority 2: Important Improvements (Should Do)

### Recommendation 2.1: Add Real-World Applications

[Same structure: Issue, Root Cause, Proposed Change, Impact, Effort, Timeline, Metrics]

### Recommendation 2.2: Enhance Visual Supports

[Same structure]

## Priority 3: Nice-to-Have Enhancements

### Recommendation 3.1: Add Student Choice Options

[Same structure]

## Implementation Plan

### Phase 1: Critical Fixes (Weeks 1-4)
- [ ] Week 1-2: Split Unit 2, restructure
- [ ] Week 3-4: Revise assessment items

### Phase 2: Important Improvements (Weeks 5-8)
- [ ] Week 5-6: Add real-world applications
- [ ] Week 7-8: Create visual supports

### Phase 3: Enhancements (Weeks 9-12)
- [ ] Week 9-12: Implement choice options

### Resources Needed

- **Time**: 40 hours total (10 hrs/week × 4 weeks)
- **Expertise**: Assessment design consultant for item revision
- **Materials**: $200 for new visual creation tools
- **Testing**: 30 students for field testing items

## Version Tracking

**Version 1.0** (Current):
- Created: Fall 2024
- Student Count: 30
- Average Performance: 72%
- Objective Mastery: 12/18 objectives (67%)
- Issues: Pacing, assessment depth

**Version 1.1** (Planned):
- Release: Spring 2025
- Changes: Unit 2 split, assessment revision
- Expected Performance: 78%
- Expected Mastery: 15/18 objectives (83%)

**Success Indicators for Version 1.1**:
✅ Increase average performance by 6+ percentage points
✅ Achieve ≥70% mastery on all objectives
✅ Reduce "feeling rushed" feedback to <30%
✅ Reduce "just memorization" feedback to <20%

## Next Review Cycle

**When**: End of Spring 2025 term
**Data to Collect**:
- Student performance on revised assessments
- Student feedback surveys
- Instructor observations
- Comparison to Version 1.0 baseline

**Questions to Answer**:
- Did splitting Unit 2 improve mastery?
- Did revised assessments better measure learning?
- What new issues emerged?
- What worked well and should be kept?

---

**Iteration Metadata**:
- **Current Version**: 1.0
- **Recommended Version**: 1.1
- **Change Type**: MINOR (improvements, not redesign)
- **Priority Issues**: 2 critical, 2 important, 1 enhancement
- **Implementation Timeline**: 12 weeks

5. Track Effectiveness Across Versions

## Version Comparison: 1.0 vs 1.1

| Metric | v1.0 (Baseline) | v1.1 (Revised) | Change | Status |
|--------|-----------------|----------------|--------|--------|
| Avg Performance | 72% | 78% | +6% | ✅ Target met |
| Unit 2 Mastery | 45% | 73% | +28% | ✅ Excellent |
| Apply-Level Perf | 58% | 72% | +14% | ✅ Target met |
| Feeling Rushed | 60% | 25% | -35% | ✅ Target met |
| Real-World Value | 45% agree | 78% agree | +33% | ✅ Improved |

**Analysis**:
Version 1.1 successfully addressed all critical issues. Unit 2 mastery increased dramatically (+28 percentage points) after splitting into two units. Assessment revisions led to deeper learning (Apply performance +14%). Student satisfaction improved significantly.

**New Issues Identified in v1.1**:
- Unit 3 now feels rushed by comparison (new pacing issue)
- Need more collaborative activities

**Recommendation for v1.2**:
Address Unit 3 pacing and add collaborative work.

6. CLI Interface

# Analyze all feedback
/curriculum.iterate-feedback --feedback "surveys/,outcomes/,reviews/" --curriculum "curriculum-artifacts/"

# Specific focus
/curriculum.iterate-feedback --focus "assessment" --outcomes "results.csv" --feedback "comments.txt"

# Version comparison
/curriculum.iterate-feedback --compare --v1 "v1.0-data/" --v2 "v1.1-data/"

# Generate revision plan
/curriculum.iterate-feedback --plan --feedback "all-feedback/" --timeline "12 weeks" --resources "medium"

# Help
/curriculum.iterate-feedback --help

Composition with Other Skills

Input from:

  • /curriculum.analyze-outcomes - Performance data
  • Student surveys and feedback
  • Peer review notes

Output to:

  • Educator for implementation
  • /curriculum.design - For redesign
  • /curriculum.develop-* - For revisions

Exit Codes

  • 0: Analysis complete, recommendations generated
  • 1: Cannot load feedback sources
  • 2: Insufficient data for analysis
  • 3: No patterns identified
  • 4: Invalid comparison versions

平台分布

Claude Code

28.7%
按下载量换算20

windsurf

22.13%
按下载量换算16

zencoder

16.43%
按下载量换算12

trae

13.51%
按下载量换算10

OpenCode

7.93%
按下载量换算6

Codex

3.81%
按下载量换算3

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

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