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 skills/pixel-process-ug/superkit-agents/database-schema-designnpx skills add Pixel-Process-UG/superkit-agents --skill database-schema-designgit clone --depth 1 https://github.com/Pixel-Process-UG/superkit-agentsWrote 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/skills/pixel-process-ug/superkit-agents/database-schema-design)<a href="https://agentmods.dev/skills/pixel-process-ug/superkit-agents/database-schema-design"><img src="https://agentmods.dev/badge/skills/pixel-process-ug/superkit-agents/database-schema-design.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 | $0.00032 | $0.02893 |
| Opus 5 | $0.00016 | $0.01447 |
| Sonnet 5 | $0.00006 | $0.00579 |
| Haiku 4.5 | $0.00003 | $0.00289 |
Grade A, and why
database-schema-design 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Schema Design
Overview
Guide the design, implementation, and optimization of database schemas with sound data modeling, safe migrations, effective indexing, and appropriate query patterns. This skill covers the full lifecycle from conceptual modeling through physical optimization, ensuring schemas that are normalized, performant, and safely evolvable.
Announce at start: "I'm using the database-schema-design skill to design the database schema."
Phase 1: Discovery and Conceptual Model
Ask these questions to understand the data requirements:
| # | Question | What It Determines |
|---|---|---|
| 1 | What entities does the system manage? | Table names |
| 2 | What are the relationships between entities? | Foreign keys, join tables |
| 3 | What are the key attributes of each entity? | Column definitions |
| 4 | What are the primary query patterns? | Index strategy |
| 5 | What is the expected data volume? (rows, growth rate) | Partitioning, scaling |
| 6 | What is the read/write ratio? | Normalization vs denormalization |
| 7 | SQL or NoSQL? (or both?) | Storage engine selection |
Storage Engine Decision Table
| Factor | Choose SQL (PostgreSQL, MySQL) | Choose Document (MongoDB) | Choose Key-Value (Redis) |
|---|---|---|---|
| Data shape | Structured, relational | Semi-structured, nested | Simple lookups, caching |
| Query complexity | Complex joins, aggregations | Document-level queries | Key-based access only |
| Consistency needs | ACID required | Eventual consistency OK | Ephemeral or cached data |
| Schema evolution | Migrations manageable | Schema-free flexibility | No schema |
| Scale pattern | Vertical first, then read replicas | Horizontal sharding | In-memory, limited size |
STOP after discovery — present the conceptual model (entities, relationships, cardinality) for confirmation.
Phase 2: Logical Model Design
Translate the conceptual model into tables, columns, types, and constraints.
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.
- yesterday First seen · 279 lines · 32 tokens per session scan A f21c998c0005
database-schema-design is a skill published in the GitHub repository Pixel-Process-UG/superkit-agents (1 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 2,893 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 2026-09-03.
Other skills, from other repositories
postgres-ops
Operate a production Postgres database — backup strategy, point-in-time recovery, restore drills, connection pooling for serverless, and a disaster-recovery runbook. Use when asked to set up Postgres backups, plan disaster recovery, configure connection pooling, restore a database, or harden Postgres for production.…
mongodb-atlas-checker
Verify MongoDB Atlas setup and configuration for backend applications. Checks connection strings, environment variables, connection pooling, and ensures proper setup for Next.js and NestJS applications. Use when verifying MongoDB Atlas setup, checking connection strings or environment variables, or troubleshooting…
mongodb-natural-language-querying
Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with…
mongodb-migration-expert
Database schema design, indexing, and migration guidance for MongoDB-based applications. Use when adding or changing MongoDB collections, indexes, or fields, designing schema for multi-tenant or large datasets, or planning forward-only migrations.
mongodb-atlas-stream-processing
Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for…
mongodb-connection
Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling connect()), configuring connection pools, troubleshooting connection errors…