Gsd-skill-creator kp-content-authoring
Generates knowledge pack content suites: vision documents, modules YAML, activities JSON, assessment frameworks, resource catalogs, and .skillmeta files. Shared by all 3 tier-specific author agents. Use when creating or updating pack content files.
git clone https://github.com/Tibsfox/gsd-skill-creator
T=$(mktemp -d) && git clone --depth=1 https://github.com/Tibsfox/gsd-skill-creator "$T" && mkdir -p ~/.claude/skills && cp -r "$T/infra/packs/knowledge/skills/kp-content-authoring" ~/.claude/skills/tibsfox-gsd-skill-creator-kp-content-authoring && rm -rf "$T"
infra/packs/knowledge/skills/kp-content-authoring/SKILL.mdContent Authoring
Purpose
Provides the content generation methodology for all 35 knowledge packs. This is the shared authoring skill loaded by KP-02 (core), KP-03 (applied), and KP-04 (specialized). It defines the pack file structure, content templates, quality standards, and parallel instruction patterns that enable token caching across packs.
Capabilities
- Vision document generation following PACK-TEMPLATE.md structure (~40 pages per pack)
- Modules YAML with learning outcomes, topics, grade levels, time estimates, and prerequisite chains
- Activities JSON with grade-appropriate hands-on activities per module
- Assessment framework with rubric levels (Beginning, Developing, Proficient, Advanced)
- Resource catalog with categorized links by audience and grade level
- .skillmeta YAML generation with full KnowledgePackSchema compliance
- Grade level spanning: PreK through College+ with appropriate content differentiation
- Learning pathway support: Maker, Academic, Curiosity, Social, Parent-Guided
Parallel Instruction Patterns (NFR-06)
The following instruction sections are identical across all 35 packs and should be cached:
- Pack file structure template -- the 6-file directory layout is the same for every pack
- Vision document skeleton -- section headings (Vision, Problem Statement, Core Concepts, Skill Tree, Modules, Assessment Framework, Parent Guidance, Resources) are reused
- Modules YAML schema -- PackModuleSchema structure with time_estimates, prerequisite_modules, activities sub-objects
- Activities JSON schema -- PackActivitySchema with grade_range, duration_minutes, materials, learning_objectives
- Assessment rubric template -- 4-level rubric (Beginning, Developing, Proficient, Advanced) with formative/summative sections
- Resource catalog template -- categorized sections (Young Learners, Older Learners, Parents, Deeper Study)
- .skillmeta boilerplate -- common fields (version, status, copyright, gsd_integration, accessibility stubs, translation stubs)
- Grade level bands -- Foundation (PreK-K), Elementary (1-5), Middle School (6-8), High School (9-12), College (13-16)
These 8 patterns are loaded once and reused across all pack generation sessions, reducing per-pack token overhead by ~60%.
Key Modules
| Module | Purpose |
|---|---|
| Zod schemas defining pack data structures |
| Validates generated .skillmeta against KnowledgePackSchema |
| Validates generated vision documents |
| Validates generated activities JSON |
| Validates generated assessment markdown |
| Validates generated resource catalogs |
Usage Examples
Generate a pack content suite:
For each pack (e.g., MATH-101): 1. Create src/knowledge/packs/math-101/ directory 2. Write vision.md using pack-specific content + shared template sections 3. Write modules.yaml matching ModulesFileSchema 4. Write activities.json as PackActivity[] array 5. Write assessment.md with 4-level rubric 6. Write resources.md with categorized links 7. Write .skillmeta matching KnowledgePackSchema
Apply parallel instruction patterns:
Before generating any pack, load: - Pack file structure template (shared) - Vision document skeleton (shared) - Modules YAML schema (shared) - Activities JSON schema (shared) - Assessment rubric template (shared) - Resource catalog template (shared) - .skillmeta boilerplate (shared) - Grade level bands (shared) Then inject pack-specific: subject content, domain activities, subject-specific resources
Dependencies
- Pack runtime API (src/knowledge/) for schema validation
- Domain-specific skill (core, applied, or specialized) for subject matter knowledge
- Pack template structure from delivery package
Token Budget Rationale
2.0% budget reflects the comprehensive authoring methodology covering 6 file types, 8 parallel instruction patterns, and the pack generation workflow. This is the largest knowledge pack skill because it provides the reusable templates that reduce per-pack generation cost. Shared across 3 agents but loaded once per session.