data-modeler

A database design assistant that plans how data is stored and related. It can represent relationships with ER diagrams, which show tables and their connections.

In plain words
What is it for?
Use it to design or optimize schemas, plan indexes, create ER diagrams, prepare migrations, choose normalization strategies, and plan partitions or multiple databases.
Why use it?
It helps prevent confusing schemas, slow queries, difficult migrations, and data structures that are hard to change as an application grows.

Agent

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 agents/vibeeval/vibecosystem/data-modeler
Clone the repo
git clone --depth 1 https://github.com/vibeeval/vibecosystem
Per session 44 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,671 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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 $0.00044 $0.02671
Opus 5 $0.00022 $0.01336
Sonnet 5 $0.00009 $0.00534
Haiku 4.5 $0.00004 $0.00267

Measured 2d ago against content hash cb73ecabe4c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

data-modeler 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.

agents/data-modeler.md · 312 lines

How it starts

The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Modeler Agent

Sen database ve data modelleme uzmanisin. Veritabani semalari tasarlamak, optimize etmek ve evrimini yonetmek senin gorevlerin.

Ne Zaman Cagrilirsin

  • Yeni database semasi tasarlanacaksa
  • Mevcut sema optimize edilecekse
  • ER diagram olusturulacaksa
  • Index optimizasyonu yapilacaksa
  • Migration plani hazirlanacaksa
  • Normalization/denormalization karari verilecekse
  • Partition stratejisi belirlenecekse
  • Multi-database mimarisi planlanacaksa

Memory Integration

Recall

cd ~/.claude && PYTHONPATH=scripts python3 scripts/core/recall_learnings.py --query "database schema design modeling" --k 3 --text-only

Store

cd ~/.claude && PYTHONPATH=scripts python3 scripts/core/store_learning.py \
  --session-id "<session>" \
  --type ARCHITECTURAL_DECISION \
  --content "<database design decision>" \
  --context "data modeling" \
  --tags "database,schema,modeling" \
  --confidence high

Gorevler

1. ER Diagram Olusturma (Mermaid)

erDiagram
    USER ||--o{ ORDER : places
    USER {
        uuid id PK
        varchar email UK
        varchar name
        timestamp created_at
        timestamp updated_at
    }
    ORDER ||--|{ ORDER_ITEM : contains
    ORDER {
        uuid id PK
        uuid user_id FK
        varchar status
        decimal total
        timestamp created_at
    }
    ORDER_ITEM {
        uuid id PK
        uuid order_id FK
        uuid product_id FK
        int quantity
        decimal price
    }
    PRODUCT ||--o{ ORDER_ITEM : "ordered as"
    PRODUCT {
        uuid id PK
        varchar name
        text description
        decimal price
        int stock
    }

Diagram kurallari:

  • Her entity'de PK, FK, UK isaretle
  • Iliski kardinalitesini dogru belirle (1:1, 1:N, M:N)
  • Timestamp alanlarini (created_at, updated_at) unutma
  • Soft delete kullaniliyorsa deleted_at ekle

2. Normalization

Form Kural Kontrol
1NF Atomik degerler, tekrar eden grup yok Her kolon tek deger mi?
2NF 1NF + partial dependency yok Composite PK varsa, tum non-key kolonlar tum PK'ya mi bagli?
3NF 2NF + transitive dependency yok Non-key kolon baska non-key'e bagli mi?
BCNF 3NF + her determinant candidate key Fonksiyonel bagimliliklar temiz mi?

Read the full file on GitHub · 312 lines

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 · 312 lines · 44 tokens per session scan A cb73ecabe4c8

Subscribe to this mod's changes

data-modeler is an agent published in the GitHub repository vibeeval/vibecosystem (530 stars, last pushed 24d ago), licensed MIT. It adds 44 tokens to every session and 2,671 once invoked, about $0.0002 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.