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-bytehouse-data-quality-inspectorgit 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-bytehouse-data-quality-inspector)<a href="https://agentmods.dev/skills/bytedance/agentkit-samples/byted-bytehouse-data-quality-inspector"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-bytehouse-data-quality-inspector/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-bytehouse-data-quality-inspector"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-bytehouse-data-quality-inspector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Privilege Escalation · line 25 Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.Fix: Avoid sudo/root unless strictly required. Prefer least-privilege patterns. If elevation is needed, document the justification and scope.
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 | $0.00119 | $0.01683 |
| Opus 5 | $0.00060 | $0.00842 |
| Sonnet 5 | $0.00024 | $0.00337 |
| Haiku 4.5 | $0.00012 | $0.00168 |
Grade B, and why
byted-bytehouse-data-quality-inspector scanned grade B with 1 finding 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 9d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
- `jq`（`export_config.sh` 依赖，用于解析 JSON 配置。安装方式：`brew install jq` 或 `sudo apt install jq`） How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ByteHouse 数据质量检查工具
描述
本 Skill 用于对 ByteHouse 表的关键键列（分区键、排序键、主键）进行快速数据质量分析，识别空值、零值、异常分布以及重复键等常见质量问题。
当以下情况时使用此 Skill：
- 用户需要检查 ByteHouse 中某个表的数据质量。
- 用户需要分析表的排序键、主键或分区键的空值、零值情况。
- 用户想了解键列的数据分布情况（Top N 值及占比）。
- 用户需要检查排序键 / 主键组合是否存在重复记录。
- 用户提到 "数据质量"、"空值检查"、"零值检查"、"主键重复"、"排序键重复"、"分区键异常" 等关键词。
前置条件
- Python 3.8+
clickhouse-connect库（未安装时执行pip install clickhouse-connect）jq（export_config.sh依赖，用于解析 JSON 配置。安装方式：brew install jq或sudo apt install jq）- 有效的 ByteHouse 连接信息（保存于
~/.bytehouse_config.json）
📁 文件说明
- SKILL.md — 本文件，技能主文档。
- scripts/inspector.py — 数据质量检查主程序。
- scripts/export_config.sh — 从
~/.bytehouse_config.json加载配置到环境变量（依赖jq）。
配置说明
配置保存在 ~/.bytehouse_config.json。如果该文件存在且非空，直接使用文件中的配置；如果不存在，则向用户索要 ByteHouse 连接信息（可以把 ByteHouse 连接信息获取指引 一并发给用户），拿到后写入 JSON 文件，避免重复询问。当用户切换 ByteHouse 集群时，一并更新该文件。
{
"BYTEHOUSE_HOST": "<ByteHouse-host>",
"BYTEHOUSE_PASSWORD": "<ByteHouse-password>"
}
BYTEHOUSE_HOST（主机地址）与BYTEHOUSE_PASSWORD（密码）必须由用户提供。
加载配置：
source scripts/export_config.sh
🧭 智能体使用指引
- 确认配置：
source scripts/export_config.sh，确保BYTEHOUSE_HOST与BYTEHOUSE_PASSWORD已就绪。 - 确认目标表：向用户确认要检查的库名（
--database）和表名（--table）。多张表可以循环调用脚本。 - 执行检查：
python3 scripts/inspector.py --database <库名> --table <表名>。 - 解读结果：脚本会分别输出「空值/零值/分布」和「主键/排序键重复情况」两大部分。若用户没有明确关注点，重点关注空值占比 > 1%、零值占比 > 5%、Top1 占比 > 20%、重复键行数占比 > 0.5% 等异常。
- 禁止越权操作：本 Skill 只做只读的统计查询，不要触发 DELETE / OPTIMIZE / DROP 等 DML/DDL 操作。修复数据应由用户在评估后单独操作。
🎯 功能特性
-
自动识别键列
- 从
system.columns自动获取表的分区键、排序键和主键列。
- 从
-
空值与零值检查
- 统计键列的 Null 值数量和占比。
- 数值类型统计 0 值数量和占比；字符串类型统计空字符串数量和占比。
-
异常分布分析
- 统计键列出现频率最高的 Top 5 值及占比。
-
重复情况检查
- 分别针对主键组合、排序键组合，统计存在重复的唯一键组数以及涉及的总行数。
🚀 快速开始
# 加载配置
source scripts/export_config.sh
# 检查单张表
python3 scripts/inspector.py --database default --table my_table
What ships with it
2 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.
- 9d ago First seen · 138 lines · 119 tokens per session scan B caa6390d15b1
byted-bytehouse-data-quality-inspector is a skill published in the GitHub repository bytedance/agentkit-samples (450 stars, last pushed 5d ago), licensed Apache-2.0. It adds 119 tokens to every session and 1,683 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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