Educational Assessment AI Agent Platform — AI skill for Claude Code
AI agent platform for K-12 assessment: standards-aligned item authoring with RAG and self-review, rubric-based scoring with human review, and a tutoring agent with persistent memory.
How to install Educational Assessment AI Agent Platform
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open mthatipamula/educational-assessment-ai-agent-platform and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Educational Assessment AI Agent Platform does
AI agent platform for K-12 assessment: standards-aligned item authoring with RAG and self-review, rubric-based scoring with human review, and a tutoring agent with persistent memory. Safety guardrails for student input, sandboxed code grading, evals and observability. Claude on AWS Bedrock, Python, React, pgvector, MCP.
Alternatives in AI
- Nexscope Ecommerce Skills — Ready-to-use AI agent skills for e-commerce intelligence 55 ★
- Creative Director Skill — AI creative director with recursive self-assessment: 20+ methodologies (SIT, TRIZ, Bisociation, SCAMPER, Synec 32 ★
- Claude Code Prompting 101 — A comprehensive educational repository for mastering prompt engineering with Anthropic's Claude AI, from basic 29 ★
README
Educational Assessment AI Agent Platform
AI agents for K-12 assessment, built to be **reliable and responsible**:
- teachers author standards-aligned items with an agent that researches, drafts, reviews and revises its own work;
- a scoring agent scores written answers against a rubric, with evidence and confidence, and sends uncertain cases to a teacher;
- a tutor agent with persistent memory helps students with hints, never the answer;
- student code runs in an isolated sandbox;
- every agent is measured by an evaluation framework and visible in an observability view.
**Stack:**
- Python 3.12 (FastAPI) with the Anthropic Python SDK, calling Claude on Amazon Bedrock, with the Anthropic API as fallback;
- Amazon Titan embeddings on Bedrock, with Voyage AI as fallback;
- PostgreSQL + pgvector;
- MCP server;
- React + TypeScript;
- Docker.
Demo data only: synthetic students and items; standard descriptions are paraphrased. No real student data.
Architecture
Teacher / student (React) ──▶ nginx :8070 ──▶ FastAPI :8071 ───────────────┐
│ │
┌─────────────────────────────────────────┼───────────────┐ │ MCP (/mcp): search_standards,
▼ ▼ ▼ ▼ │ list_items, student_progress
Authoring agent Scoring agent Tutor agent Safety layer │
(Opus: research, (Sonnet: rubric, (Sonnet: hints, (regex + Haiku │
draft, self-review, evidence, tools, memory, classifier, │
revise) confidence) leak guard) PII redaction) │
│ │ │ │ │
└────────── Claude gateway: Bedrock ─▶ Anthropic API (fallback) ◀─────┘
Embeddings: Titan V2 (Bedrock) ─▶ Voyage voyage-3.5 (fallback)
Related Skills
Deeptutor Claude Skill
Claude Code skill adapting DeepTutor's graph-enhanced RAG tutoring methodology. Knowledge graphs, dual-loop so
Prompt Architecture
Reference guide for designing production LLM prompt systems in this codebase. Covers the Two-Pass Gap Analysis
Agentic Job Search
Agentic job-application system built AI-first with Claude Code: hourly watcher over 46 job boards with qualifi
AI Readiness Assessment
Free companion skill for Viksya's AI Transformation Readiness Scoring Model — runs the scoring interview and g
Hands
Cross-platform computer-use agent. Your LLM on your mouse, keyboard, and screen. Windows (PowerShell), macOS (
AI Engineering Workspace
One engineering workflow across Claude Code, Codex, Copilot, and Gemini CLI. A portable persona canon, process
Related Agents
Lite Scan
Low-cost read-only scanner for mechanical lookups — file/symbol inventory, grep/stats aggregation, fixture sam
Blind Evaluator
Structurally separate eval agent. Receives ONLY the problem statement + rubric, NEVER the solution or the impl
Agentic AI Dev
Expert Agentic AI developer with Python 3.14, LangChain v1.2.8, LangGraph v1.0.7, and FastAPI 0.135.2. Use for