rushdb-data-modeling

A guide for organizing data in RushDB’s graph database, where records have properties and relationships to other records. It covers labels, fields, links, nested JSON, and agent memory.

In plain words
What is it for?
Designing or updating schemas, importing nested JSON, defining relationships, and structuring persistent agent memory.
Why use it?
It helps prevent unclear or inconsistent data structures as a project’s stored information grows or changes.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/rush-db/rushdb/rushdb-data-modeling
Any agent
npx skills add rush-db/rushdb --skill rushdb-data-modeling
Clone the repo
git clone --depth 1 https://github.com/rush-db/rushdb

Made for: Claude Code, Codex.

Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,714 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00071 $0.02714
Opus 5 $0.00036 $0.01357
Sonnet 5 $0.00014 $0.00543
Haiku 4.5 $0.00007 $0.00271

Measured 2d ago against content hash 9331047a0337, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

rushdb-data-modeling scanned grade A with 0 findings 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 2d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packages/skills/rushdb-data-modeling/SKILL.md · 278 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

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.

  1. 2d ago First seen · 278 lines · 71 tokens per session scan A 9331047a0337

Subscribe to this mod's changes

rushdb-data-modeling is a skill published in the GitHub repository rush-db/rushdb (323 stars, last pushed 6d ago), with no licence file. It adds 71 tokens to every session and 2,714 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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