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 skills add huangzt/my-agent-skills --skill mysql-toolsgit clone --depth 1 https://github.com/huangzt/my-agent-skillsWrote 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/huangzt/my-agent-skills/mysql-tools)<a href="https://agentmods.dev/skills/huangzt/my-agent-skills/mysql-tools"><img src="https://agentmods.dev/badge/skills/huangzt/my-agent-skills/mysql-tools/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/huangzt/my-agent-skills/mysql-tools"><img src="https://agentmods.dev/badge/skills/huangzt/my-agent-skills/mysql-tools.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00086 | $0.00807 |
| Opus 5 | $0.00043 | $0.00404 |
| Sonnet 5 | $0.00017 | $0.00161 |
| Haiku 4.5 | $0.00009 | $0.00081 |
Grade A, and why
mysql-tools 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 12d 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.
What it actually says
MySQL 工具 Skill
用于操作 MySQL 数据库的工具集,提供连接测试、表管理和 SQL 执行功能。
快速开始
前置要求
pip install pymysql
平台兼容性
- ✅ Windows
- ✅ macOS
- ✅ Linux
连接参数
所有脚本支持以下参数:
| 参数 | 说明 | 默认值 |
|---|---|---|
--host |
数据库主机地址 | localhost |
--port |
数据库端口 | 3306 |
--user |
数据库用户名 | root |
--password |
数据库密码 | 必填 |
--database |
数据库名称 | 必填 |
可用脚本
1. 测试数据库连接
验证数据库连接参数是否正确:
python scripts/mysql_connect.py --host 127.0.0.1 --port 3306 --user root --password YOUR_PASSWORD --database YOUR_DB
2. 列出所有表
获取数据库中的所有表名:
python scripts/mysql_tables.py --host 127.0.0.1 --user root --password YOUR_PASSWORD --database YOUR_DB
输出格式:表名列表,包含表类型(BASE TABLE / VIEW)
3. 查看表结构
显示指定表的字段信息:
python scripts/mysql_schema.py --host 127.0.0.1 --user root --password YOUR_PASSWORD --database YOUR_DB --table TABLE_NAME
输出格式:字段名、类型、是否可空、键类型、默认值、额外信息
4. 执行 SQL 查询
运行任意 SQL 语句:
python scripts/mysql_query.py --host 127.0.0.1 --user root --password YOUR_PASSWORD --database YOUR_DB --query "SELECT * FROM users LIMIT 10"
支持 SELECT、INSERT、UPDATE、DELETE 等所有 SQL 语句。
5. 查看数据库信息
获取数据库版本、大小等信息:
python scripts/mysql_info.py --host 127.0.0.1 --user root --password YOUR_PASSWORD --database YOUR_DB
输出格式
所有脚本输出 JSON 格式数据,便于解析:
{
"success": true,
"data": [...],
"message": "操作成功"
}
错误时返回:
{
"success": false,
"error": "错误信息",
"message": "操作失败"
}
常见用例
探索新数据库
- 测试连接:
mysql_connect.py - 列出所有表:
mysql_tables.py - 查看关键表结构:
mysql_schema.py --table TABLE_NAME - 查询示例数据:
mysql_query.py --query "SELECT * FROM TABLE_NAME LIMIT 5"
数据分析
- 获取表记录数:
mysql_query.py --query "SELECT COUNT(*) FROM TABLE_NAME" - 分析数据分布:
mysql_query.py --query "SELECT column, COUNT(*) FROM TABLE_NAME GROUP BY column"
参考更多 SQL 示例
查看 references/common_queries.md 获取常用 SQL 查询模板。
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 123 lines · 86 tokens per session scan A 171a21fe13be
mysql-tools is a skill published in the GitHub repository huangzt/my-agent-skills (20 stars, last pushed 8mo ago), licensed MIT. It adds 86 tokens to every session and 807 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.
Other skills, from other repositories
database-expert
Advanced database design and administration for PostgreSQL, MongoDB, and Redis. Use when designing schemas, optimizing queries, managing database performance, or implementing data patterns.
clickhouse-architect
ClickHouse schema design and optimization. TRIGGERS - ClickHouse schema, compression codecs, MergeTree, ORDER BY tuning, partition key.
imessage-query
Query macOS iMessage database (chat.db) via SQLite. Decode NSAttributedString messages, handle tapbacks, search conversations.
backtesting-py-oracle
Configuration and anti-patterns for using backtesting.py to validate ClickHouse SQL sweep results. Ensures bit-atomic replicability between SQL and Python trade evaluation.
ml-data-pipeline-architecture
Patterns for efficient ML data pipelines using Polars, Arrow, and ClickHouse. TRIGGERS - data pipeline, polars vs pandas, arrow format.
multi-agent-e2e-validation
Multi-agent parallel E2E validation for database refactors. TRIGGERS - E2E validation, schema migration testing, database refactor validation.