Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Database expert including Prisma, Supabase, SQL, and NoSQL patterns
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
When reviewing or writing code, apply these guidelines:
When reviewing or writing code, apply these guidelines:
When interacting with databases:
When reviewing or writing code, apply these guidelines:
When reviewing or writing code, apply these guidelines:
When reviewing or writing code, apply these guidelines:
When reviewing or writing code, apply these guidelines:
When reviewing or writing code, apply these guidelines:
You are familiar with latest features of supabase and how to integrate with Next.js application.
When reviewing or writing code, apply these guidelines:
When reviewing or writing code,
</instructions> <examples> Example usage: ``` User: "Review this code for database best practices" Agent: [Analyzes code against consolidated guidelines and provides specific feedback] ``` </examples>This expert skill consolidates 1 individual skills:
| Anti-Pattern | Why It Fails | Correct Approach |
|---|---|---|
| String-concatenated SQL queries | SQL injection vector; one unsanitized input compromises the database | Use ORM query builders or parameterized prepared statements |
| No RLS on multi-tenant tables | Any authenticated user can read/write other users' data | Enable RLS policies scoped to auth.uid() on all user-scoped tables |
Unbounded .findAll() / SELECT * without LIMIT | Returns entire table; causes timeouts and memory spikes on large datasets | Always paginate with LIMIT/OFFSET or cursor-based pagination |
| No connection pooling | Serverless functions exhaust database connections under load | Use PgBouncer / Supavisor in transaction mode |
| Logging full query strings with values | Leaks PII and credentials into log aggregators | Log query templates only; redact all bound parameter values |
Use official MCP servers to give agents direct database access without writing custom integration code.
# Quick start — no install required
npx -y @modelcontextprotocol/server-postgres postgresql://user:pass@localhost/mydb
# Claude Desktop / agent-studio settings.json
{
"mcpServers": {
"postgres": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-postgres", "${DATABASE_URL}"]
}
}
}
Available tools: query (read-only SELECT), list_tables, describe_table
Key design: read-only enforcement
The PostgreSQL MCP server wraps queries in BEGIN READ ONLY transactions, preventing accidental mutations. For write operations, build a custom MCP server with explicit write tools annotated destructiveHint: true.
Agent workflow pattern:
1. list_tables → discover available tables
2. describe_table → understand schema before querying
3. query → run SELECT with explicit column list + LIMIT
npx -y @modelcontextprotocol/server-sqlite /path/to/database.db
# settings.json
{
"mcpServers": {
"sqlite": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-sqlite", "/path/to/database.db"]
}
}
}
Available tools: read_query, write_query, create_table, list_tables, describe_table, insert_row, delete_rows
SQLite MCP usage patterns:
-- Discover schema
list_tables()
describe_table({ table_name: "users" })
-- Safe read pattern
read_query({ query: "SELECT id, name, email FROM users WHERE active = 1 LIMIT 100" })
-- Write with explicit columns (never INSERT SELECT *)
insert_row({ table_name: "users", data: { name: "Alice", email: "alice@example.com" } })
-- Conditional delete (always use WHERE)
delete_rows({ table_name: "sessions", where: "expires_at < datetime('now')" })
Security rules for SQLite MCP:
write_query and delete_rows calls in audit trail| Scenario | Use MCP Server | Build Custom |
|---|---|---|
| Agent needs to query a DB for context | MCP (postgres/sqlite) | No |
| Read-only exploration / analysis | MCP | No |
| Complex business logic + DB writes | No | Custom MCP with validated tools |
| Multiple DB operations in one transaction | No | Custom (MCP is single-op) |
| DB + external API in one workflow | No | Custom orchestration |
Before starting:
cat .claude/context/memory/learnings.md
After completing: Record any new patterns or exceptions discovered.
ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
日本語の概要は準備中です。原文の説明を表示しています。
N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
日本語の概要は準備中です。原文の説明を表示しています。
Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
日本語の概要は準備中です。原文の説明を表示しています。
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
日本語の概要は準備中です。原文の説明を表示しています。