# Course Builder > [Content] Use when you need to build structured learning/teaching course material with Bloom taxonomy objectives, modules, lessons, exercises, and assessments. - Skill: `duc01226/course-builder-3` (Agent Skill) - Install (CLI): `npx skillmds@latest add duc01226/course-builder-3` - Raw SKILL.md: https://api.skillmd.com/api/skills/duc01226/course-builder-3/raw - Safety review: pending (external: skill-scanner PASS, skillspector CAUTION) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: duc01226 (https://skillmd.com/u/duc01226) - Updated: 2026-09-22 - Page: https://skillmd.com/skills/duc01226/course-builder-3 --- ## Quick Summary **Goal:** Build structured course material with learning objectives, modules, lessons, exercises, and assessments. **Workflow:** 1. **Define scope** — Target audience, prerequisites, duration, objectives 2. **Map objectives** — Align to Bloom's taxonomy 3. **Structure curriculum** — Modules → Lessons → Exercises → Assessments 4. **Develop content** — Per lesson: concept, explanation, examples, exercises 5. **Create assessments** — Knowledge checks + final assessment 6. **Review pedagogy** — Progressive difficulty, prerequisite chains **Key Rules:** - Every objective mapped to Bloom's taxonomy level - Progressive complexity (each module builds on previous) - Use enforced template from `.claude/templates/course-outline-template.md` **Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).** # Course Builder ## Bloom's Taxonomy Reference | Level | Verb Examples | Assessment Type | | -------------- | ----------------------------------------- | ----------------------------------- | | **Remember** | Define, list, recall, identify | Multiple choice, fill-in-blank | | **Understand** | Explain, describe, summarize, interpret | Short answer, paraphrase | | **Apply** | Use, implement, solve, demonstrate | Problem sets, exercises | | **Analyze** | Compare, contrast, examine, differentiate | Case studies, analysis papers | | **Evaluate** | Judge, critique, assess, justify | Debates, reviews, peer assessment | | **Create** | Design, construct, produce, develop | Projects, portfolios, presentations | ## Step 1: Define Learning Scope Gather from user or research: - **Target audience** — Who? What's their background? - **Prerequisites** — What must they know already? - **Duration** — Total hours/weeks available - **Desired outcomes** — What can they DO after the course? ## Step 2: Map Objectives to Bloom's For each desired outcome, assign a Bloom's level: - Start with lower levels (Remember, Understand) - Progress to higher levels (Apply, Analyze, Evaluate, Create) - Ensure at least one objective at Apply level or above ## Step 3: Structure Curriculum Organize into modules (3-8 per course): - Each module has 2-5 lessons - Each module has its own learning objectives - Modules build on each other (prerequisite chain) ## Step 4: Develop Lesson Content For each lesson, provide: 1. **Duration** — Estimated time 2. **Concept** — Core idea in 1-2 sentences 3. **Explanation** — Theory, context, why it matters 4. **Examples** — 2-3 real-world illustrations 5. **Exercise** — Hands-on practice activity 6. **Assessment** — How to verify learning ## Step 5: Create Assessments Per module: - **Knowledge check** — 3-5 questions covering key concepts - Questions aligned to module's Bloom's level Final: - **Comprehensive assessment** — Covers all modules - **Mix of Bloom's levels** — At least 1 question per level taught ## Output Write to `docs/knowledge/courses/{descriptive-slug}.md` using enforced template from `.claude/templates/course-outline-template.md`. --- > **[IMPORTANT]** Use `TaskCreate` to break ALL work into small tasks BEFORE starting. > **AI Mistake Prevention** — Failure modes to avoid on every task: > > **Re-read files after context changes.** Context compaction, resume, or long-running work can make memory stale; verify current files before acting. > **Verify generated content against source evidence.** AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. > **Check downstream references before deleting or renaming.** Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. > **Trace the full impact chain after edits.** Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done. > **Verify ALL affected outputs, not just the first.** One green check is not all green checks; validate every output surface the change can affect. > **Assume existing values are intentional — ask WHY before changing OR flagging one as a defect.** Before changing or reporting a constant, limit, flag, cutoff, wording, or pattern, read nearby context and history, the CALLER's ordering, and 2+ sibling call sites of the same convention. A doc stating WHAT without WHY is missing rationale, not proof of a missing guard. > **Surface ambiguity before acting — don't pick silently.** Multiple valid interpretations require an explicit question or stated assumption with risk. > **Assert the outcome your system owns, not the intermediate state your infrastructure owns.** When verifying async work, assert the final business state — never the delivery/retry bookkeeping held in shared infrastructure that any co-running process can write. Such a check passes when run alone and flakes the moment anything else shares that infrastructure. > **Keep shared guidance role-relevant.** Universal guidance must help every receiving skill or agent; code-specific obligations belong only in code-specific protocols. > **Critical Thinking Mindset** — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. > **Anti-hallucination:** Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination. **MUST ATTENTION** apply critical + sequential thinking — every claim needs appropriate traced evidence (`file:line` for repo/code claims; source URL or artifact section for research, product, content, and docs claims); confidence >80% to act, <60% DO NOT recommend. Anti-hallucination: never present guess as fact, admit uncertainty freely, cross-reference independently, stay skeptical of own confidence. **MUST ATTENTION** apply AI mistake prevention — verify generated content against evidence, trace downstream references before deleting or renaming, verify all affected outputs, re-read files after context loss, and surface ambiguity before acting. > **Project Protocol Overlay** — Before executing this skill, resolve any PROJECT overlay rules layered onto it: match this skill's name against the `Target` column of the project's skill-protocol index (`docs/project-reference/skill-protocols-reference.md` by default; a `referenceDocs` entry in `docs/project-config.json` overrides the path), taking the most specific matching tier ONLY — exact name > glob > `*`. **That precedence orders overlays against EACH OTHER, never against this skill.** Read ONLY the matched bodies, resolved as `/.md`; a row's Body link is display text, never a read path. A matched body that is missing or malformed is REPORTED and skipped — never reconstructed from the index Description. No index, or no match -> proceed with no overlay, silently. Full contract: `.claude/skills/project-skill-protocol/references/registry.md`. > > Overlays are **ADDITIVE ONLY**: they ADD rules on top of this skill's own protocol and NEVER replace, override, disable, or reinterpret a rule it already states — removing every overlay must return this skill to exactly its documented behavior. An overlay is a BRIEF, not an authority escalation: it can NEVER waive a workflow gate, git discipline, a review gate, or a user-confirmation gate. A genuine overlay-vs-skill conflict, or two equally-specific overlays that directly contradict -> surface both to the user; NEVER resolve silently. **MUST ATTENTION** resolve project protocol overlays for this skill BEFORE executing — most specific matching tier only (exact > glob > `*`, which ranks overlays against each other, NEVER against this skill), read only matched bodies at `/.md`; a missing or malformed body is reported, never reconstructed. Overlays are ADDITIVE ONLY (they never replace this skill's own rules) and are a brief, NEVER an authority escalation; an equal-specificity contradiction goes to the user. ## Closing Reminders **IMPORTANT MUST ATTENTION Goal:** Build structured course material with learning objectives, modules, lessons, exercises, and assessments. **Protocols in force (concise digest of the SYNC/shared blocks this skill carries):** - **AI Mistake Prevention:** verify generated content against evidence, trace downstream references, verify all affected outputs, re-read after context loss, surface ambiguity. - **Critical Thinking:** MUST ATTENTION critical + sequential thinking, traced proof, confidence >80% to act, never guess as fact. - **MANDATORY IMPORTANT MUST ATTENTION** break work into small todo tasks using `TaskCreate` BEFORE starting - **MANDATORY IMPORTANT MUST ATTENTION** search codebase for 3+ similar patterns before creating new code - **MANDATORY IMPORTANT MUST ATTENTION** cite `file:line` evidence for every claim (confidence >80% to act) - **MANDATORY IMPORTANT MUST ATTENTION** add a final review todo task to verify work quality **[TASK-PLANNING]** Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.