Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Content Creation
Curriculum Designer
Design customized curricula for PODs with REAL resource links. Staged implementation with checkpointing and fallback logic. Use when user says 'Design curric...
skill openclawclawhub Free
Design customized curricula for PODs with REAL resource links. Staged implementation with checkpointing and fallback logic. Use when user says 'Design curric...
โฌ 0 downloads โ
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, curriculum-designer.sh
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.1
Provenance
- Publisher
- tarasinghrajput
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Curriculum Designer
Design customized curricula for Apni Pathshala PODs with real YouTube video links. FEATURES: โ Staged execution with checkpointing (recovery from failures) โ YouTube link verification with fallback logic (no blank URLs) โ Context capping per lesson (reduced token usage) โ Every topic gets a valid video OR search query fallback
How This Skill Works
When invoked, the agent follows a 5-stage workflow with checkpointing: StageWhat HappensCheckpoint File1Gather requirementsrequirements.json2Research YouTube videosresearch-results.json3Verify videos + fallback logicvalidated-resources.json4Design curriculum (one lesson at a time)curriculum-structure.json5Create Google Sheetfinal-sheet-url.txt
Checkpoint Behavior
Each stage saves its output to a checkpoint file If checkpoint exists, stage loads it and skips processing If checkpoint doesn't exist, stage runs from scratch Re-running resumes from first incomplete stage
Trigger
User message contains: "Design curriculum" โ Start curriculum creation "Create curriculum for [POD name]" โ Start with POD context "Build learning plan" โ Start curriculum creation "Curriculum for [subject/topic]" โ Start with topic context
Target User
This skill is designed for Madhur (Academic Associate) who designs curricula for PODs.
Configuration
API Keys: Stored locally in ~/.openclaw/workspace/skills/curriculum-designer/.env (NOT in git) Output Folder: 1upJQu-IVmZRJQsNGmJNRzq9IwL67MVL9 (Curriculum Designer) Checkpoint Directory: ~/.openclaw/workspace/curriculum-designer-checkpoints/ YouTube API Key: YOUTUBE_API_KEY=your_key_here Get from: https://console.cloud.google.com/apis/credentials
Model Allocation for Stages
Action: Use different LLM models for different stages to optimize cost and performance.
Stage-Specific Model Assignment
StageRecommended ModelReasonStage 1: Requirements Collectionglm-4.7Quick reasoning, sufficient for form fillingStage 2: YouTube Researchglm-5Fast research, needs latest web knowledgeStage 3: Video Validationglm-4.7Pattern matching, simple logicStage 4: Curriculum Designglm-4.7Structured generation, cost-effective for lessonsStage 5: Sheet Creationglm-4.7JSON formatting, simple transformations
How to Set Models
Option 1: Specify model when calling agent # Use glm-5 for research stage agent.chat --model glm-5 --message "Research YouTube videos for..." # Use glm-4.7 for design stage agent.chat --model glm-4.7 --message "Generate lesson structure..." Option 2: Configure in SKILL.md Each stage should include model recommendation in its instructions: ### Stage 2: Research YouTube Resources **Action:** Search YouTube for videos based on requirements **Recommended Model:** glm-5 (fast research, latest web knowledge) **Why:** Research needs up-to-date information and fast processing.
Stage 1: Gather Requirements
Action: Ask the user these questions (from SOP): Basic Information POD Name - Which POD is this curriculum for? Target Audience - Grade level or age group of students? Subject Areas - What subjects/topics should be covered? Duration - How long is the program? (e.g., 1 month, 3 months, 6 months) Frequency - How many classes per week? Daily Lab Hours - How many hours will the lab operate? Previous Exposure - Have students done digital learning before? Teacher Context Teacher Capability - Can teachers operate computers independently? Teacher Training Needed - Do teachers need any training? Learning Outcomes Learning Area Focus - Which area(s) to prioritize? Digital Literacy Academic Empowerment Skill Development Employment Readiness Specific Skills - What specific skills should students acquire? Assessment Method - How will learning be measured? Output: Save to checkpoint as JSON: { "pod_name": "Example POD", "target_audience": "Grade 8-10", "subject_areas": ["Digital Literacy", "Computer Basics"], "duration": "1 month", "frequency": "3 days/week", "daily_lab_hours": 2, "previous_exposure": "None", "teacher_capability": "Basic", "teacher_training_needed": true, "learning_area_focus": ["Digital Literacy"], "specific_skills": ["Basic computer operations", "Internet safety"], "assessment_method": "Practical exercises and quizzes" } Checkpoint: ~/.openclaw/workspace/curriculum-designer-checkpoints/<timestamp>-<session-id>/requirements.json
Stage 2: Research YouTube Resources
Action: Search YouTube for videos based on requirements API: Use YouTube Data API v3 with key from .env Search Queries (Default): search_queries = [ "computer basics tutorial hindi beginners", "typing practice hindi tutorial", "internet browser basics hindi", "gmail email tutorial hindi beginners", "google docs tutorial hindi", "google sheets tutorial hindi", "chatgpt tutorial hindi beginners 2024", "ai tools for students hindi" ] Search Parameters: part=snippet q=<query> type=video maxResults=5 videoDuration=medium (5-10 minutes preferred) relevanceLanguage=hi (Hindi preference) Output Structure: { "resources": [ { "topic": "computer basics", "videos": [ { "title": "Computer Basics for Beginners in Hindi", "channel": "TechGuruji", "url": "https://youtube.com/watch?v=ABC123", "video_id": "ABC123" } ] } ] } Research Summary (Before Validation) After completing all searches, summarize the research results before passing to validation stage. Why summarize? Reduces token usage when passing to Stage 3 (validation) Provides cleaner input for validation logic Allows easy review of what was researched Summary Structure: { "research_summary": { "total_searches": 8, "topics_researched": [ "computer basics", "typing practice", "internet browser basics", "gmail email tutorial", "google docs tutorial", "google sheets tutorial", "chatgpt tutorial", "ai tools for students" ], "total_videos_found": 24, "video_channels": ["TechGuruji", "LearnWithMe", "DigitalSkills", "HindiTechTutorials"], "search_language": "Hindi preference", "video_duration_preference": "5-10 minutes", "notes": "Most videos from 2023-2024. Good variety of channels. Some topics have fewer results, may need fallback search." } } Save summary: Append research_summary to research-results.json Validation stage uses summary for context, not raw results Checkpoint: ~/.openclaw/workspace/curriculum-designer-checkpoints/<timestamp>-<session-id>/research-results.json
Stage 3: Verify Videos + Fallback Logic
Action: Verify each video via YouTube oEmbed API. If invalid, retry with alternative search terms. Verification Method Use oEmbed endpoint (fast, lightweight): https://www.youtube.com/oembed?url=https://youtube.com/watch?v=VIDEO_ID HTTP 200 = Valid video HTTP 404 = Invalid/deleted video HTTP 4xx/5xx = Try again (rate limit or temporary error) Fallback Logic (CRITICAL) For each topic, follow this logic: For each video in topic: 1. Verify via oEmbed 2. If valid โ Add to validated list, done with topic 3. If invalid โ Try next video in topic If NO valid videos found for topic: 1. Retry search with alternative queries: - Original query + "part 2" - Original query + "for students" - Original query + "in english" (if Hindi failed) 2. Verify new results 3. If still no valid videos โ ADD FALLBACK: - "search_query": "<original query> tutorial hindi beginners" - "fallback_reason": "No valid videos found, please search manually" Output Structure (With Fallbacks) { "resources": [ { "topic": "computer basics", "video": { "title": "Computer Basics for Beginners in Hindi", "channel": "TechGuruji", "url": "https://youtube.com/watch?v=ABC123", "video_id": "ABC123", "status": "valid" } }, { "topic": "advanced excel", "fallback": { "search_query": "advanced excel tutorial hindi beginners", "reason": "No valid videos found after 3 retry attempts" } } ] } IMPORTANT: Every topic MUST have either: A valid video URL, OR A search query fallback Checkpoint: ~/.openclaw/workspace/curriculum-designer-checkpoints/<timestamp>-<session-id>/validated-resources.json
Stage 4: Design Curriculum (Context Capping + Summarization)
Action: Generate curriculum structure, processing one lesson at a time with summarization and context cleanup. How Context Capping + Summarization Works Instead of: Pass entire curriculum (all lessons) to LLM at once โ High token usage Do this: For each lesson (1, 2, 3, ... N): 1. Load lesson N context only (this lesson's topic + resources) 2. Generate lesson content 3. SUMMARIZE lesson N context 4. Save lesson + summary to curriculum structure 5. WIPE lesson N context from memory 6. Continue to next lesson When all lessons complete: 1. Summarize entire curriculum 2. Save summary to curriculum structure 3. Save summary to Stage 2 checkpoint (research-results.json) Lesson-by-Lesson Process For lesson N: Load context: Lesson N topic Lesson N resources (from validated-resources.json) Previous lesson summary (if N > 1) Generate lesson: Daily learning objectives Daily assessment Module content YouTube link/fallback Summarize lesson: Create concise summary of lesson N Focus on: key skills, tools used, assessment type Save to curriculum: Full lesson details Lesson summary (for next lesson's context) Context cleanup: Remove lesson N's full context from memory Keep only lesson N's summary for N+1 Lesson Summary Template { "lesson_number": 1, "summary": "Students learned basic computer components, mouse/keyboard operations, and system navigation. Introduced primary computer parts and basic troubleshooting. Assessment involved identifying components and practicing typing.", "key_skills": [ "Identifying computer parts", "Mouse and keyboard basics", "System navigation" ], "tools_used": ["Computer", "Mouse", "Keyboard"], "assessment_type": "Practical exercise and observation" } Lesson Generation Template For each lesson, generate: FieldDescriptionDayLesson number (1, 2, 3, ...)SubjectSubject area / Learning areaModuleModule/Topic nameDaily Learning ObjectivesWhat students learn that dayDaily AssessmentHow to assess understandingYouTube LinkValid video URL OR search query fallbackYouTube TitleVideo title (if applicable)Tools UsedRequired software/platformsFallback Search QuerySearch query if no valid video (or blank)Lesson SummaryConcise summary for next lesson's context Sample Lesson Output (With Summary) { "day": 1, "subject": "Digital Literacy", "module": "Module 1: Introduction to Computers", "daily_learning_objectives": "Understand basic computer components, learn to use mouse and keyboard", "daily_assessment": "Practical exercise: Identify computer parts, practice typing", "youtube_link": "https://youtube.com/watch?v=ABC123", "youtube_title": "Computer Basics for Beginners in Hindi", "tools_used": "Computer, Mouse, Keyboard", "fallback_search_query": "", "lesson_summary": { "summary": "Students learned basic computer components, mouse/keyboard operations, and system navigation.", "key_skills": ["Identifying computer parts", "Mouse and keyboard basics", "System navigation"], "tools_used": ["Computer", "Mouse", "Keyboard"], "assessment_type": "Practical exercise and observation" } } With Fallback Example { "day": 5, "subject": "Skill Development", "module": "Module 5: Advanced Spreadsheets", "daily_learning_objectives": "Learn Excel formulas and data analysis", "daily_assessment": "Create a budget spreadsheet using formulas", "youtube_link": "", "youtube_title": "", "tools_used": "Google Sheets", "fallback_search_query": "advanced excel formulas tutorial hindi beginners", "lesson_summary": { "summary": "Students advanced from basic Google Sheets to formulas and data analysis. Learned SUM, AVERAGE, IF functions, and chart creation.", "key_skills": ["Google Sheets formulas", "Data analysis basics", "Chart creation"], "tools_used": ["Google Sheets"], "assessment_type": "Project-based: Budget spreadsheet" } } Final Curriculum Summary (When All Lessons Complete) After generating all lessons: Summarize entire curriculum: Total lessons Subject areas covered Key skills progression Assessment approach Tools/software used Save to curriculum structure: { "curriculum_summary": { "total_lessons": 12, "duration": "1 month", "frequency": "3 days/week", "subject_areas": ["Digital Literacy", "Skill Development"], "skills_progression": [ "Week 1: Computer basics and navigation", "Week 2: Internet and email fundamentals", "Week 3: Document creation and editing", "Week 4: Spreadsheets and data analysis" ], "assessment_methods": ["Practical exercises", "Quizzes", "Projects"], "tools_used": ["Computer", "Google Docs", "Google Sheets", "YouTube videos"], "learning_outcomes": "Students will gain basic computer literacy, internet safety awareness, and productivity tool proficiency." } } Update Stage 2 checkpoint: Add curriculum_summary field to research-results.json This keeps summary alongside research results for reference Checkpoint: ~/.openclaw/workspace/curriculum-designer-checkpoints/<timestamp>-<session-id>/curriculum-structure.json Also updates: ~/.openclaw/workspace/curriculum-designer-checkpoints/<timestamp>-<session-id>/research-results.json (adds curriculum_summary)
Stage 5: Create Google Sheet
Action: Create Google Sheet with curriculum data using gog CLI. Step 1: Create Sheet # Use gog CLI to create new spreadsheet SHEET_ID=$(gog drive spreadsheet create \ --name "Curriculum_[POD]_[YYYY-MM-DD]" \ --parent-folder "$GOG_FOLDER_ID" \ --json | python3 -c "import sys, json; print(json.load(sys.stdin).get('id', ''))") echo "Sheet ID: $SHEET_ID" Step 2: Add Headers # Add header row gog sheets update "$SHEET_ID" "Sheet1!A1:H1" \ --values-json '[["Day","Subject","Module","Daily Learning Objectives","Daily Assessment","YouTube Link","YouTube Title","Tools Used","Fallback Search Query"]]' Step 3: Populate with Lessons # Read curriculum structure and convert to gog format # For each lesson, create a row array # Then append all rows at once # Format each lesson as: [Day, Subject, Module, Objectives, Assessment, URL, Title, Tools, Fallback] gog sheets append "$SHEET_ID" "Sheet1!A2:H" \ --values-json '[ ["1","Digital Literacy","Module 1: Introduction","Understand basic components","Practical exercise","https://youtube.com/watch?v=ABC123","Computer Basics","Computer,Mouse",""], ["2","Digital Literacy","Module 2: File Management","Learn to organize files","Create folders","https://youtube.com/watch?v=DEF456","File Management","File Explorer",""], ... ]' \ --insert INSERT_ROWS Data format: Column A: Day (1, 2, 3, ...) Column B: Subject Column C: Module Column D: Daily Learning Objectives Column E: Daily Assessment Column F: YouTube Link Column G: YouTube Title Column H: Tools Used Column I: Fallback Search Query Validation: One row per lesson Include fallback search queries (if any) Ensure no blank YouTube Links OR populated Fallback Search Query Step 4: Share Sheet # โ ๏ธ CRITICAL: Always share with public view access gog drive share "$SHEET_ID" --to anyone --role reader Step 5: Save URL # Construct public URL and save PUBLIC_URL="https://docs.google.com/spreadsheets/d/${SHEET_ID}" echo "$PUBLIC_URL" > "<checkpoint-dir>/final-sheet-url.txt" Checkpoint: ~/.openclaw/workspace/curriculum-designer-checkpoints/<timestamp>-<session-id>/final-sheet-url.txt
Learning Areas Framework
Learning AreaFocusDigital LiteracyBasic computer skills, internet safety, AI toolsAcademic EmpowermentStudy skills, exam prep, note-takingSkill DevelopmentProgramming, design, content creationEmployment ReadinessResume, communication, job skills
Video Selection Criteria
โ 5-10 minutes max - keeps engagement high โ Clear explanations - no jargon-heavy content โ Hindi or bilingual - accessible for all students โ Recent content - prefer 2023+ videos โ Long lectures - students lose interest โ Advanced content - match to target audience level
โ ๏ธ CRITICAL: Sharing Permissions
ALWAYS share sheet with --to anyone --role reader before returning link NEVER return a restricted link - user cannot view it Command: gog drive share <SHEET_ID> --to anyone --role reader
โ ๏ธ CRITICAL: No Blank URLs
Every topic MUST have either: A valid YouTube URL, OR A search query fallback Never leave both fields blank
Assessment Design
Formative (daily): Quick quizzes, practice exercises, short tasks Summative (end): Projects, presentations, comprehensive tests Keep assessments practical and hands-on
Folder Reference
ResourceLinkCurriculum Designer Folderhttps://drive.google.com/drive/folders/1upJQu-IVmZRJQsNGmJNRzq9IwL67MVL9Example Curriculum (AI Tools)https://docs.google.com/spreadsheets/d/1hYC2Q2KlW8dM71biC97RPSvFnxTQa-zNSOP Documenthttps://docs.google.com/document/d/1Y5qetW8S4RWsTg7hycIyujgTwTCFn9VV
Security Note
โ ๏ธ API keys are stored locally in .env file - NEVER commit this file to git!
Future Improvements
Resume from specific stage - Ability to jump to any stage, not just first failed one
Purpose
Delete checkpoint directories older than 7 days to prevent disk space bloat while keeping recent sessions for debugging.
Cron Job Configuration
Option 1: Add to User Crontab # Edit crontab crontab -e # Add this line (runs daily at midnight) 0 0 * * * find ~/.openclaw/workspace/curriculum-designer-checkpoints/ -type d -mtime +7 -exec rm -rf {} \; Option 2: Using OpenClaw Cron # Create cron job via OpenClaw openclaw cron create \ --name "checkpoint-cleanup" \ --schedule "0 0 * * *" \ --command "find ~/.openclaw/workspace/curriculum-designer-checkpoints/ -type d -mtime +7 -exec rm -rf {} \;" \ --description "Delete curriculum-designer checkpoints older than 7 days" Cron Schedule Options ScheduleCrontab FormatDescriptionDaily at midnight0 0 * * *Every day at 00:00Weekly on Sunday0 0 * * 0Every Sunday at 00:00Every 6 hours0 */6 * * *Every 6 hours (may be too frequent)Twice daily0 0,12 * * *At 00:00 and 12:00
Verification
After setting up cron, verify it's working: # List cron jobs (crontab) crontab -l # List cron jobs (OpenClaw) openclaw cron list
Manual Cleanup Test
Test the cleanup command manually before setting up cron: # Dry run (see what would be deleted) find ~/.openclaw/workspace/curriculum-designer-checkpoints/ -type d -mtime +7 -ls # Actual cleanup find ~/.openclaw/workspace/curriculum-designer-checkpoints/ -type d -mtime +7 -exec rm -rf {} \; # Verify ls ~/.openclaw/workspace/curriculum-designer-checkpoints/
Notes
-mtime +7: Files/directories modified more than 7 days ago -type d: Only directories (sessions), not individual files -exec rm -rf {} \;: Remove directory and all contents Checkpoints are preserved after completion for review, then auto-cleaned after 7 days Adjust +7 to a different value if you want different retention period (+3, +14, +30)
Notes
Always search for REAL video URLs before creating curriculum Save curriculum sheets in the designated folder Share viewable link at the end Consider teacher training needs if curriculum requires new tools Checkpoints are preserved after completion for review Every topic in final curriculum must have valid video OR search query fallback
Category context
Writing, remixing, publishing, visual generation, and marketing content production.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- curriculum-designer.sh