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 jeecgboot/skills --skill jeecg-systemgit clone --depth 1 https://github.com/jeecgboot/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/jeecgboot/skills/jeecg-system)<a href="https://agentmods.dev/skills/jeecgboot/skills/jeecg-system"><img src="https://agentmods.dev/badge/skills/jeecgboot/skills/jeecg-system/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/jeecgboot/skills/jeecg-system"><img src="https://agentmods.dev/badge/skills/jeecgboot/skills/jeecg-system.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00162 | $0.04836 |
| Opus 5 | $0.00081 | $0.02418 |
| Sonnet 5 | $0.00032 | $0.00967 |
| Haiku 4.5 | $0.00016 | $0.00484 |
Grade A, and why
jeecg-system 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 10d 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 — 396 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JeecgBoot 系统主数据查询与管理
查询和管理 JeecgBoot 系统中的角色、用户、部门、字典等主数据。遵循"先查后建"原则:优先使用系统已有数据,没有才创建。
前置条件
用户必须提供以下信息(或由 AI 引导确认):
- API 地址:JeecgBoot 后端地址(如
https://boot3.jeecg.com/jeecgboot) - X-Access-Token:JWT 登录令牌(从浏览器 F12 获取)
如果用户未提供,提示:
请提供 JeecgBoot 后端地址和 X-Access-Token(从浏览器 F12 → Network → 任意请求的 Request Headers 中复制)。
核心原则:先查后建
在任何 skill(流程设计、表单设计、代码生成等)需要使用主数据时,必须先查询系统已有数据,确认不存在后才创建新数据。
| 数据类型 | 查询函数 | 创建函数 | 一站式函数 |
|---|---|---|---|
| 角色 | query_roles() / find_role() |
create_role() |
find_or_create_role() |
| 角色绑定用户 | — | add_users_to_role(role_id, user_ids) |
— |
| 审批角色 | query_approval_roles() / find_approval_role() |
create_approval_role_group() + create_approval_role() |
find_or_create_approval_role() |
| 审批角色绑定用户 | — | add_users_to_approval_role(role_id, user_ids) |
— |
| 用户 | query_users() / find_user() |
— | — |
| 部门 | query_depts() / find_dept() |
— | — |
| 岗位 | query_dept_positions() |
— | — |
| 字典(普通) | query_dict() / search_dict() / find_dict() |
create_dict() |
find_or_create_dict() |
| 字典(SQL表) | query_sql_table_dict() |
— | — |
使用方式
脚本位置
scripts/system_creator.py— 通用命令行脚本(推荐,无需生成临时 .py)scripts/system_utils.py— 工具库(供其他 skill 脚本 import)
方式一:通用脚本 + 命令行(推荐)
单项查询(直接命令行,无需配置文件):
SCRIPT="<skill目录>/jeecg-system/scripts/system_creator.py"
API="<api_base>"
TOKEN="eyJ..."
# 查询角色列表
python "$SCRIPT" --api-base $API --token $TOKEN --action query-roles
python "$SCRIPT" --api-base $API --token $TOKEN --action query-roles --keyword 经理
# 查询用户列表
python "$SCRIPT" --api-base $API --token $TOKEN --action query-users --keyword 张
# 查询部门树
python "$SCRIPT" --api-base $API --token $TOKEN --action query-depts
python "$SCRIPT" --api-base $API --token $TOKEN --action query-depts --keyword 研发
# 查询字典列表
python "$SCRIPT" --api-base $API --token $TOKEN --action query-dicts --keyword 请假
# 查询字典项
python "$SCRIPT" --api-base $API --token $TOKEN --action query-dict --code sex
# 查询职务列表
python "$SCRIPT" --api-base $API --token $TOKEN --action query-positions
# 查询部门+岗位树
python "$SCRIPT" --api-base $API --token $TOKEN --action query-dept-positions
# 查询审批角色
python "$SCRIPT" --api-base $API --token $TOKEN --action query-approval-roles
# 查询租户列表
python "$SCRIPT" --api-base $API --token $TOKEN --action query-tenants
# 查询数据源
python "$SCRIPT" --api-base $API --token $TOKEN --action query-datasources
# 查询定时任务
python "$SCRIPT" --api-base $API --token $TOKEN --action query-quartz-jobs
# 查询分类字典
python "$SCRIPT" --api-base $API --token $TOKEN --action query-categories --code B01
# 输出结果到 JSON 文件
python "$SCRIPT" --api-base $API --token $TOKEN --action query-roles --output roles.json
What ships with it
3 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.
- 10d ago First seen · 396 lines · 162 tokens per session scan A 67d5d53c75d2
jeecg-system is a skill published in the GitHub repository jeecgboot/skills (227 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 162 tokens to every session and 4,836 once invoked, about $0.0008 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.
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