bytedance/agentkit-samples is a collection of examples and tutorials for Volcengine AgentKit, an AI-agent development platform for building, deploying, and operating agent applications. Developers use the samples to learn agent creation, multi-agent collaboration, memory, retrieval, MCP integrations, media generation, customer service, and other workflows. The catalogue skills provide agent workflows based on these examples.
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 bytedance/agentkit-samples --skill byted-vedb-mysqlgit clone --depth 1 https://github.com/bytedance/agentkit-samplesWrote 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/bytedance/agentkit-samples/byted-vedb-mysql)<a href="https://agentmods.dev/skills/bytedance/agentkit-samples/byted-vedb-mysql"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-vedb-mysql/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/bytedance/agentkit-samples/byted-vedb-mysql"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-vedb-mysql.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 75 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 76 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00096 | $0.07623 |
| Opus 5 | $0.00048 | $0.03811 |
| Sonnet 5 | $0.00019 | $0.01525 |
| Haiku 4.5 | $0.00010 | $0.00762 |
Grade A, and why
byted-vedb-mysql 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 1,072 lines — stays where its author put it; the contents beside it link to each section on GitHub.
火山引擎 VEDBM 管理技能
本技能用于管理火山引擎 VEDBM（云数据库）实例，包含以下功能：
- 创建实例：支持用户自定义实例规格，默认使用 2C8G 规格，用户名 root，密码随机生成
- 查看实例列表：查询指定地域下的所有 VEDBM 实例
- 查看数据库账号列表：查询指定实例中的所有数据库账号及其状态
- 查看实例连接地址：查询指定实例的连接地址信息（域名、端口、IP等）
✨ 新特性
- 智能规格匹配：支持用户输入简单格式（如 "2c8g"、"4c16g"）
- 灵活默认值：默认使用 2C8G 规格
- 自动降级/升级：如果用户提供的规格不存在，自动选择最接近的可用规格
使用流程
第一步：收集必要信息
当用户触发此技能时，先检查是否有必要信息。如果没有，引导用户提供：
| 信息 | 必填 | 说明 |
|---|---|---|
| VPC ID | ✅ | 虚拟私有云 ID |
| 子网 ID | ✅ | 子网 ID |
| 可用区 ID | ✅ | 可用区（如 cn-guangzhou-a） |
| AccessKey ID | ✅ | 火山引擎访问密钥 ID |
| Secret Access Key | ✅ | 火山引擎秘密访问密钥 |
第二步：信息收集方式
方式 A：对话引导（推荐首次使用）
询问用户：
"好的，我来帮你创建 VEDBM 实例！需要你提供一些信息：
- VPC ID 是什么？
- 子网 ID 是什么？
- 想用哪个可用区？（如 cn-guangzhou-a）
- AccessKey ID 是什么？
- Secret Access Key 是什么？"
方式 B：环境变量配置（推荐频繁使用）
提示用户配置环境变量：
# 配置环境变量
export VOLCENGINE_ACCESS_KEY="你的AccessKeyId"
export VOLCENGINE_SECRET_KEY="你的SecretAccessKey"
export VEDBM_VPC_ID="你的VPC ID"
export VEDBM_SUBNET_ID="你的子网 ID"
export VEDBM_ZONE_ID="cn-guangzhou-a"
或者使用 .env 文件：
cd scripts
cp .env.example .env
# 编辑 .env 文件填入真实信息
第三步：执行创建
收集完信息后，执行创建命令。
访问密钥配置
方式 1：命令行参数
python scripts/create_vedbm_instance.py \
--vpc-id <你的VPC ID> \
--subnet-id <你的子网 ID> \
--zone-id cn-guangzhou-a \
--access-key-id <你的AccessKeyId> \
--secret-access-key <你的SecretAccessKey>
方式 2：环境变量
export VOLCENGINE_ACCESS_KEY="your-access-key-id"
export VOLCENGINE_SECRET_KEY="your-secret-access-key"
export VEDBM_VPC_ID="your-vpc-id"
export VEDBM_SUBNET_ID="your-subnet-id"
export VEDBM_ZONE_ID="cn-guangzhou-a"
python scripts/create_vedbm_instance.py
方式 3：混合使用
可以部分用环境变量，部分用命令行参数：
export VOLCENGINE_ACCESS_KEY="your-access-key-id"
export VOLCENGINE_SECRET_KEY="your-secret-access-key"
python scripts/create_vedbm_instance.py \
--vpc-id <你的VPC ID> \
--subnet-id <你的子网 ID> \
--zone-id cn-guangzhou-a
可用区说明
广州区域可用区：
cn-guangzhou-a- 可用区 Acn-guangzhou-c- 可用区 C
What ships with it
12 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.
- .gitignore 64 B
- LICENSE 9.9 KB
- scripts/.env.example 1.2 KB
- scripts/create_vedbm_instance.py 17 KB runs code
- scripts/describe_instance.py 11 KB runs code
- scripts/downgrade_instance_spec.py 27 KB runs code
- scripts/get_instance_endpoint.py 7.5 KB runs code
- scripts/list_db_accounts.py 6.7 KB runs code
- scripts/list_instances.py 7.4 KB runs code
- scripts/requirements.txt 29 B
- scripts/test_spec_matching.py 2.3 KB runs code
- scripts/upgrade_instance_spec.py 27 KB runs code
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.
- 5d ago First seen · 1,072 lines · 96 tokens per session scan A 047b95077746
byted-vedb-mysql is a skill published in the GitHub repository bytedance/agentkit-samples (450 stars, last pushed 4d ago), licensed Apache-2.0. It adds 96 tokens to every session and 7,623 once invoked, about $0.0005 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.
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