# Sql Reader

> Read database table structures and query data. Supports PostgreSQL, SQL Server, Oracle, SQLite. Trigger when user mentions: database query, table structure, SQL query, look up data, check database, 表结构, 查询数据, 数据库, SQL. Allows natural language queries where the LLM generates SQL automatically. Read-only (SELECT only) enforced at Python script level.

- **Type:** Skill
- **Install:** `agentstack add skill-yansijian-agent-skills-sql-reader`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [yansijian](https://agentstack.voostack.com/s/yansijian)
- **Installs:** 0
- **Category:** [Databases](https://agentstack.voostack.com/c/databases)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [yansijian](https://github.com/yansijian)
- **Source:** https://github.com/yansijian/agent-skills/tree/main/skills/sql-reader

## Install

```sh
agentstack add skill-yansijian-agent-skills-sql-reader
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# SQL Reader Skill

Read table structures and query data from PostgreSQL, SQL Server, Oracle, and SQLite. All queries are strictly read-only (SELECT only), enforced by the Python script with multi-layer security.

## Prerequisites

### Environment Setup

Before any database operation, ensure the Python virtual environment is ready. Run this ONCE per session (or when dependencies are missing):

```bash
py scripts/setup_env.py
```

This script:
1. Checks Python >= 3.8 (uses `py` launcher on Windows)
2. Creates `.venv/` in the skill folder (where SKILL.md is located)
3. Installs database drivers into the venv

If Python is not found or version  --db-type  [PARAMS]

# Linux/macOS
.venv/bin/python scripts/db_query.py --mode  --db-type  [PARAMS]
```

### test_conn — Test Database Connection

```bash
.venv/Scripts/python.exe scripts/db_query.py --mode test_conn --db-type pgsql --host localhost --port 5432 --user myuser --password mypass --database mydb
```

Use this to verify connectivity before running other operations.

### list_tables — List All Tables

```bash
.venv/Scripts/python.exe scripts/db_query.py --mode list_tables --db-type pgsql --host localhost --port 5432 --user myuser --password mypass --database mydb
```

Returns: `{"success": true, "data": [{"table_name": "...", "table_type": "BASE TABLE|VIEW"}], "row_count": N}`

### describe — Show Table Structure

```bash
.venv/Scripts/python.exe scripts/db_query.py --mode describe --db-type pgsql --host localhost --port 5432 --user myuser --password mypass --database mydb --table users
```

Returns column details: name, data type, max length, precision, nullable, default value, primary key.

### query — Execute SELECT Query

```bash
.venv/Scripts/python.exe scripts/db_query.py --mode query --db-type pgsql --host localhost --port 5432 --user myuser --password mypass --database mydb --sql "SELECT * FROM users WHERE age > 18"
```

Returns: `{"success": true, "data": [...], "columns": [...], "row_count": N}`

## Natural Language Query Workflow

When the user describes a query need in natural language (not raw SQL), follow this workflow:

### Step 1: Ensure Environment

Run `py scripts/setup_env.py` if not done yet. Capture the venv Python path from the output.

### Step 2: Collect Connection Info

Check if the user already provided connection details. If not, ask:
- Which database type? (pgsql / sqlserver / oracle / sqlite)
- Required parameters for that type (see table above)

### Step 3: List Tables

Run `list_tables` to discover available tables. This helps you understand the schema.

If the user's request is vague ("show me the data"), present the table list and ask what they want to see.

### Step 4: Describe Relevant Tables

Based on the user's intent, run `describe` on 1-3 tables most likely relevant. You can batch these calls.

If unsure which tables are relevant, describe tables whose names match keywords from the user's request.

### Step 5: Generate SQL

Using the table structure information, generate a SELECT query:
- Respect SQL dialect differences per database type
- Use correct column names and types from the describe output
- For time-relative conditions ("last month", "this week"), use appropriate database date functions
- The script will auto-append LIMIT/TOP if not present (default 200 rows)
- Only generate SELECT statements — any other statement type will be rejected by the script

SQL Dialect Notes:
- **PostgreSQL**: `LIMIT N`, `NOW()`, `EXTRACT()`, `ILIKE`
- **SQL Server**: `TOP N`, `GETDATE()`, `DATEPART()`, `NOLOCK`
- **Oracle**: `FETCH FIRST N ROWS ONLY`, `SYSDATE`, `TRUNC()`, `ROWNUM`
- **SQLite**: `LIMIT N`, `datetime('now')`, `strftime()`

### Step 6: Execute and Present

Run the generated query via `query` mode. Present results to the user in a readable format.

For complex queries (JOINs, subqueries, aggregations), show the generated SQL to the user first and briefly explain the logic before executing.

## Security

Read-only access is enforced at THREE levels in the Python script:

1. **Regex whitelist**: SQL must start with `SELECT`
2. **Keyword blacklist**: Scans for INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, TRUNCATE, EXEC, etc.
3. **Connection-level readonly**: Each database connection is set to read-only mode

The script will return `{"success": false, "error": "BLOCKED: ..."}` if any write operation is attempted.

## Error Handling

All errors are returned as JSON: `{"success": false, "error": "..."}`

Common errors:
- **Connection refused**: Wrong host/port or database not running
- **Authentication failed**: Wrong user/password
- **Database not found**: Wrong database name
- **Table not found**: Table name case sensitivity (Oracle stores uppercase)
- **BLOCKED**: Write operation attempted
- **Query timed out**: Query exceeds 30-second limit

When an error occurs, explain it to the user and suggest fixes.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [yansijian](https://github.com/yansijian)
- **Source:** [yansijian/agent-skills](https://github.com/yansijian/agent-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-yansijian-agent-skills-sql-reader
- Seller: https://agentstack.voostack.com/s/yansijian
- Browse the marketplace: https://agentstack.voostack.com/browse

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