| name | educationalist |
| description | AI assistant skill for educators. Built with reference to the SHIDEN project,
featuring 10 specialized sub-skills for lesson planning, material creation,
assessment design, individualized instruction, feedback generation,
student guidance, and meta-prompt generation. Provides practical educational
support grounded in 175 education theories and curriculum guidelines.
|
Teaching Assistant
AI assistant skill for educators. Built with reference to the SHIDEN project, featuring 10 specialized sub-skills for lesson planning, material creation, assessment design, individualized instruction, feedback generation, student guidance, and meta-prompt generation. Provides practical educational support grounded in 175 education theories and curriculum guidelines.
Use This Skill When
- An education workflow needs lesson planning, materials, assessment, guidance, or feedback support.
- Multiple education sub-skills or theory lookups must be coordinated.
- Outputs must be grounded in curriculum guidance and saved as reusable artifacts.
Local Resources
prompts/: content-generation flows for meta-prompting, lessons, materials, assessment, individual support, feedback, and guidance.
skills/: nested Agent Skills including orchestrator/SKILL.md, theory-lookup/SKILL.md, and context-manager/SKILL.md.
data/: education reference data including theories.db, theories.json, relations.json, and curriculum.db.
- Use
curriculum.db for curriculum lookup instead of scanning curriculum markdown files.
Required Inputs
- Educational objective, learner profile, subject, level, and delivery context.
- Available source material, curriculum constraints, and time or format requirements.
- Required outputs, review audience, and evidence expectations.
Workflow
- Confirm scope, evidence path, and the artifact set to save.
- Route through the orchestrator or local helpers only when they materially improve the current task.
- Save analyses, intermediate outputs, and recommendations to files instead of leaving results in chat.
- Verify assumptions, traceability, and recommendation quality before finalizing conclusions.
- Append skill selection, handoff I/O, and file writes to
logs/process-log.jsonl when the execution harness requires trace logging.
Deliverables
report.md: objective, learner context, method, outputs, and file inventory.
results/: lesson plans, rubrics, guidance outputs, or structured analysis artifacts.
figures/: English-only charts or visuals when needed for instructional artifacts.
data/: processed source material when transformation occurs.
Quality Gates
- The selected prompt or helper matches the educational objective and learner context.
- Theory, curriculum assumptions, and constraints are explicit and traceable.
- Final outputs are saved as files and usable without chat context.
report.md and, when used, logs/process-log.jsonl reference generated artifacts.