Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/swoopeagle/standardgraph/claude-mdgit clone --depth 1 https://github.com/swoopeagle/standardgraphWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/swoopeagle/standardgraph/claude-md)<a href="https://agentmods.dev/instructions/swoopeagle/standardgraph/claude-md"><img src="https://agentmods.dev/badge/instructions/swoopeagle/standardgraph/claude-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.02930 | $0.02930 |
| Opus 5 | $0.01465 | $0.01465 |
| Sonnet 5 | $0.00586 | $0.00586 |
| Haiku 4.5 | $0.00293 | $0.00293 |
Grade B, and why
standardgraph CLAUDE.md scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
`UserName: devos` set (without it they run as root and the venv/DB paths break). How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
StandardGraph — Claude Code context
What this is
FastMCP server exposing 175,000+ education standards across 310 curriculum systems as six MCP tools for Claude Desktop. Standards cover Math, Science, ELA, Social Studies, CS, Arts, and World Languages.
Architecture
packages/
common-core/ → PyPI package "standardgraph" — the MCP server
src/common_core/
server.py → all six MCP tools (search, lookup, progression, learning_path, map, list)
config.py → DB_PATH resolution (~/.standardgraph/common_core.db)
ingestion/ → pipeline: fetchers → embed → relate → crosswalk
shared/ → shared DB helpers
data/common_core.db → dev/pipeline DB (used by overnight_run.sh)
~/.standardgraph/common_core.db → installed user DB (used by MCP server)
scripts/
mcp_test.py → 333-test suite (imports server directly, no MCP protocol)
overnight_run.sh → full ingestion pipeline (run on Mac Studio overnight)
dashboard.sh → hardware + pipeline progress dashboard
progress.sh → pipeline-only progress view
Key facts
- DB size: ~1.9 GB
- Standards: 175,738 across 310 systems (incl. CCSS sub-standard decomposition, source-side decomposition of 11 high-bundling systems, CCSS Mathematical Practice standards, the 2026-07 international expansion incl. 10 African systems, and the 2026-07-15 math grade-coverage fill-in for 11 countries)
- Crosswalk rows: ~208,442 — hub-centric (CCSS for math, NGSS for science, etc.) PLUS ~88,944 direct within-family country-to-country math edges (see
crosswalk_engine/direct_family.py; taggeddirect_familyin notes). map_standard serves direct edges automatically, two-hop-via-CCSS is the fallback. - Crosswalk quality scores: ALL 208,442 crosswalks now carry a 1–5 LLM quality score (100%) — completed 2026-07-18 via two overnight Ollama fleet runs (Studio + Mini 2 + IWPC GPU, qwen2.5:14b): the 88,944 direct-family math edges, then the 41,697 hub-centric edges (mostly ELA/Sci/SS). 37,335 edges carry
flagged_for_review=1and are suppressed from defaultmap_standardresults. Flagging policy differs by layer: direct-family flags score ≤2; hub-centric flags only score 1 (hub 2s are often valid-but-grade-shifted, and map_standard already ranks by score). Non-math hub rationales were re-scored with a subject-neutral prompt (the initial fleet prompt said "math", polluting ~2,520 non-math rationales — fixed). Note: scores span calibration regimes (earlier Sonnet mode=4; fleet 14b generous top-end) — directional weak/strong signal intact. - Relationships: ~3.79M rows (prerequisites/successors)
- Ollama host:
http://169.254.1.1:11434(Mac Studio via Thunderbolt Bridge from Mini 2 — 0.4ms RTT) - HuggingFace dataset:
swoopeagle/standardgraph(file:common_core.db) - PyPI package:
standardgraph
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 199 lines · 2,930 tokens per session scan B 2ea2f81b1899
standardgraph CLAUDE.md is an instructions file published in the GitHub repository swoopeagle/standardgraph (5 stars, last pushed 1mo ago), licensed MIT. It adds 2,930 tokens to every session, about $0.0146 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
exam-revision-handbook AGENTS.md
Instructions for mianbaofang/exam-revision-handbook, covering project agent guidance, start here, single canonical skill, product boundaries and change discipline.
AI-learning-by-claude-code CLAUDE.md
Claude Code instructions for CyrusZhang23/AI-learning-by-claude-code, covering ai-learning-by-claude-code — teaching interface, teaching protocol (most important — always follow it), course scope (locked), course index and command interface.
AI-learning-by-claude-code AGENTS.md
AGENTS.md instructions for CyrusZhang23/AI-learning-by-claude-code, covering ai-learning-by-claude-code — codex entry point, 给 codex 的首要指令(每次会话开始执行), codex 用户怎么开课, 命令语法差异(速查) and codex 教学执行规则.
ab900 CLAUDE.md
Instructions for timothywarner-org/ab900, covering claude.md, repository purpose, architecture, commands and 2. non-ascii punctuation -- must return zero.
obsidian-university-workflow CLAUDE.md
Instructions for ABO896/obsidian-university-workflow, covering obsidian university workflow, project structure, rules for working on this project, templater api — always read the docs first and config alignment.
anki-mcp-server CLAUDE.md
Claude Code instructions for nailuoGG/anki-mcp-server, covering claude.md, repository overview, development commands, build & development and install dependencies.