README.md

---
license: cc-by-4.0
language:
- en
tags:
- education
- curriculum
- standards
- mathematics
- science
- ela
- social-studies
- computer-science
- embeddings
- sqlite
pretty_name: StandardGraph — K-12 Curriculum Standards Graph
size_categories:
- 100K<n<1M
---

# StandardGraph — K-12 Curriculum Standards Graph

A unified, embedding-indexed SQLite database of **146,525 K-12 curriculum standards** across **256 systems** and **5 subjects**, with semantic crosswalk mappings linking every standard to its corresponding hub framework.

Built for AI tutoring systems, curriculum alignment tools, and LLM context retrieval. Ships as a [Model Context Protocol (MCP) server](https://github.com/swoopeagle/standardgraph) for use directly in Claude, Cursor, and other MCP-compatible tools.

---

## What's inside

| Subject | Hub | Systems | Standards |
|---|---|---|---|
| Mathematics | CCSS (343) | 82 | 22,543 |
| ELA / Literacy | CCSS ELA (504) | 52 | 46,062 |
| Science | NGSS (208) | 59 | 34,011 |
| Social Studies | C3 Framework (232) | 51 | 42,711 |
| Computer Science | CSTA (92) | 12 | 1,198 |
| **Total** | **5 hubs** | **256** | **146,525** |

**Additional tables:**
- `embeddings` — 768-dim `nomic-embed-text` vectors for all 146,525 standards
- `crosswalk_mappings` — 97,949 semantic mappings linking every non-hub standard to its nearest hub equivalent (cosine ≥ 0.70)

---

## Coverage

### Mathematics
All 50 US states + DC, plus:
- **International:** Singapore MOE, Japan MEXT, Hong Kong EDB, New Zealand, Australia (ACARA + Victoria), India NCERT (grades 1-12), Quebec MEES, Scotland CfE, Ireland NCCA, Ghana NaCCA, South Africa CAPS, Rwanda REB
- **Other US:** AERO (DoD Dependents Schools), DoDEA, Cambridge IGCSE, IB MYP/DP, AP Calculus AB/BC, AP Statistics, AP Precalculus, UK AQA / National Curriculum
- **Hub:** CCSS (343 standards, exact count)

### Science
All 50 US states + DC, AP Biology, AP Chemistry, AP Environmental Science, AP Physics 1/2/C
- **Hub:** NGSS (208 standards)

### ELA / Literacy
All 50 US states + DC
- **Hub:** CCSS ELA (504 standards)

### Social Studies
All 50 US states + DC, including California, Illinois, and Massachusetts full H-SS frameworks
- **Hub:** C3 Framework (232 indicators)

### Computer Science
CSTA K-12 hub + 11 US state standards (CT, IA, ID, KY, MA, MD, NH, UT, WI, WV, and more)
- **Hub:** CSTA 2017 (92 standards)

---

## Database schema

```sql
-- Core standards table
CREATE TABLE standards (
    id                TEXT PRIMARY KEY,   -- e.g. "CCSS.MATH.6.RP.A.3", "sg-moe.P5.NS.1"
    system            TEXT NOT NULL,      -- e.g. "ccss", "sg-moe", "ngss"
    subject           TEXT NOT NULL,      -- "mathematics" | "science" | "ela" | "social-studies" | "cs"
    grade             TEXT NOT NULL,      -- "6", "K", "HS", "9-12"
    grade_band        TEXT,              -- "6-8" where applicable
    domain            TEXT NOT NULL,      -- strand or domain label
    cluster           TEXT,              -- CCSS-specific grouping; NULL for other systems
    standard_text     TEXT NOT NULL,      -- verbatim official text
    last_verified_date TEXT NOT NULL,
    source_url        TEXT NOT NULL,
    created_at        TEXT NOT NULL,
    updated_at        TEXT NOT NULL
);

-- 768-dim nomic-embed-text vectors (float32, little-endian BLOBs)
CREATE TABLE embeddings (
    standard_id  TEXT PRIMARY KEY REFERENCES standards(id),
    model        TEXT NOT NULL,          -- "nomic-embed-text"
    vector       BLOB NOT NULL,          -- float32 little-endian
    dimensions   INTEGER NOT NULL        -- 768
);

-- Semantic crosswalk mappings (non-hub → hub)
CREATE TABLE crosswalk_mappings (
    id               INTEGER PRIMARY KEY,
    source_id        TEXT NOT NULL REFERENCES standards(id),
    source_system    TEXT NOT NULL,
    target_id        TEXT NOT NULL REFERENCES standards(id),
    target_system    TEXT NOT NULL,
    confidence_score REAL NOT NULL,      -- cosine similarity [0.70, 1.00]
    method           TEXT NOT NULL       -- "nlp-cosine"
);
```

---

## Quick start

```python
import sqlite3
import numpy as np

conn = sqlite3.connect("common_core.db")

# Look up a standard by ID
row = conn.execute(
    "SELECT grade, domain, standard_text FROM standards WHERE id=?",
    ("CCSS.MATH.6.RP.A.3",)
).fetchone()
print(row)
# ('6', 'Ratios and Proportional Relationships',
#  'Use ratio and rate reasoning to solve real-world and mathematical problems...')

# Find the CCSS equivalent of a Singapore standard
sg_id = "sg-moe.P5.NS.1"
crosswalk = conn.execute(
    "SELECT target_id, confidence_score FROM crosswalk_mappings WHERE source_id=?",
    (sg_id,)
).fetchone()
# ('CCSS.MATH.5.NBT.A.1', 0.87)

# List all systems
systems = conn.execute(
    "SELECT system, subject, COUNT(*) FROM standards GROUP BY system, subject ORDER BY subject, system"
).fetchall()
```

### Semantic search

Embed queries with [nomic-embed-text](https://ollama.com/library/nomic-embed-text) via Ollama, then compare against stored vectors:

```python
import httpx, numpy as np, sqlite3

def embed(text: str) -> np.ndarray:
    resp = httpx.post("http://localhost:11434/api/embed",
                      json={"model": "nomic-embed-text", "input": [text]})
    return np.array(resp.json()["embeddings"][0], dtype=np.float32)

def search(query: str, system: str, k: int = 5, conn=conn):
    rows = conn.execute(
        "SELECT s.id, e.vector FROM standards s JOIN embeddings e ON e.standard_id=s.id WHERE s.system=?",
        (system,)
    ).fetchall()
    ids  = [r[0] for r in rows]
    vecs = np.array([np.frombuffer(r[1], dtype=np.float32) for r in rows])
    vecs /= np.linalg.norm(vecs, axis=1, keepdims=True) + 1e-9
    q    = embed(query)
    q   /= np.linalg.norm(q) + 1e-9
    sims = vecs @ q
    top  = np.argsort(sims)[::-1][:k]
    return [(ids[i], float(sims[i])) for i in top]

search("adding fractions with unlike denominators", "ccss")
# [('CCSS.MATH.5.NF.A.2', 0.91), ('CCSS.MATH.5.NF.A.1', 0.88), ...]
```

---

## MCP server

StandardGraph ships as a [Model Context Protocol](https://modelcontextprotocol.io) server for direct use inside Claude, Cursor, and other MCP-compatible AI tools.

```bash
git clone https://github.com/swoopeagle/standardgraph
cd standardgraph
uv run python -m common_core.server
```

Tools: `search_standards`, `get_standard`, `find_crosswalk`, `list_systems`, `get_system_overview`.

See the [GitHub repo](https://github.com/swoopeagle/standardgraph) for the one-line installer for Claude Desktop.

---

## Evaluation

Run the automated eval suite against the DB:

```bash
git clone https://github.com/swoopeagle/standardgraph
cd standardgraph
uv run python scripts/eval/run_all.py
```

Current results (June 2026):
| Check | Result |
|---|---|
| Coverage (15 required IDs + hub counts) | ✅ Pass |
| Crosswalk quality (confidence distribution + routing) | ✅ Pass |
| Search quality — Recall@5 on 15 golden queries | ✅ 93% (threshold: 70%) |
| Duplicate detection | ✅ Pass (WARNs are intentional cross-grade text sharing in source standards) |

---

## Sources

| System | Source |
|---|---|
| CCSS Math & ELA, NGSS, CSTA, C3 | Common Standards Project API (achieve.org) |
| US state standards (50 states + DC, 5 subjects) | Common Standards Project API |
| Singapore MOE | Ministry of Education Singapore (official syllabi PDFs) |
| Japan MEXT | Ministry of Education, Culture, Sports, Science and Technology |
| Hong Kong EDB | Education Bureau Hong Kong |
| Australia ACARA | Australian Curriculum, Assessment and Reporting Authority |
| New Zealand | Ministry of Education New Zealand |
| Scotland CfE | Education Scotland (Curriculum for Excellence) |
| Ireland NCCA | National Council for Curriculum and Assessment |
| India NCERT | National Council of Educational Research and Training (grades 1-12) |
| Quebec MEES | Ministère de l'Éducation et de l'Enseignement supérieur |
| Ghana NaCCA | National Council for Curriculum and Assessment |
| South Africa CAPS | Department of Basic Education |
| Rwanda REB | Rwanda Education Board |
| AP Courses | College Board (Course and Exam Descriptions, PDFs) |
| Cambridge IGCSE | Cambridge Assessment International Education |
| IB MYP/DP | International Baccalaureate Organization |
| New Hampshire CS | NH Department of Education CS Standards (2018) |
| Wisconsin CS | Wisconsin DPI CS Standards (December 2025) |

International and AP standards were extracted from official PDF documents using Gemma 4 31B (via Ollama).

---

## License

**Embeddings and crosswalk mappings:** original work, released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).

**Standards text:** reproduced from official public government and organizational documents. Each standard's `source_url` field links to the authoritative source. This compilation is released under CC BY 4.0; users should verify compliance with the originating body's terms for their use case.