Agent skill

Jinshuju

by infometa in infometa/workbuddyskills

通过金数据(Jinshuju,jinshuju.net)MCP 操作用户托管在金数据平台上的在线表单:创建 / 复制 / 编辑表单与主题,含自动判分的考试表单、选项计分的测评表单;查询、新增(单条或批量)、更新、删除、批量修改数据;用上传凭证上传本地图片或文件;查询账户套餐额度与团队成员。仅在用户操作其金数据平台数据时使用——触发信号:提到 金数据 / Jinshuju /…

MITAuto-check passedDocuments & Office

Install Jinshuju

skills CLI
$ npx skills add infometa/workbuddyskills --skill jinshuju -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install infometa/workbuddyskills jinshuju --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/infometa/workbuddyskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/experts/jinshuju-expert/skills/jinshuju .claude/skills/jinshuju && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
jinshuju
GitHub stars
348
Token cost
~2k tokens
SKILL.md length
482 words
Files
5 (incl. scripts, references)
Skills in repo
218
Repo updated
First seen
Licence
MIT

At a glance

通过金数据(Jinshuju,jinshuju.net)MCP 操作用户托管在金数据平台上的在线表单:创建 / 复制 / 编辑表单与主题,含自动判分的考试表单、选项计分的测评表单;查询、新增(单条或批量)、更新、删除、批量修改数据;用上传凭证上传本地图片或文件;查询账户套餐额度与团队成员。仅在用户操作其金数据平台数据时使用——触发信号:提到 金数据 / Jinshuju /…

  • Works in 6 steps: 先看再动:操作未知表单前,先 get_form 拿字段结构——每个字段的… → filters 优先:list_entries 支持… → 先列再改:批量操作前先 list_entries… → …
  • Tasks that involve Excel spreadsheets
  • SKILL.md covers When to Use, When NOT to Use, Quick Reference and Procedure, plus 3 more sections
  • Runs Python scripts from its folder; reaches jinshuju.net

What it does

Jinshuju is an agent skill from infometa/workbuddyskills. 通过金数据(Jinshuju,jinshuju.net)MCP 操作用户托管在金数据平台上的在线表单:创建 / 复制 / 编辑表单与主题,含自动判分的考试表单、选项计分的测评表单;查询、新增(单条或批量)、更新、删除、批量修改数据;用上传凭证上传本地图片或文件;查询账户套餐额度与团队成员。仅在用户操作其金数据平台数据时使用——触发信号:提到 金数据 / Jinshuju / jinshuju.net、给出 formtoken,或要操作一张已托管在金数据上的表单或数据。不要用于:用代码开发表单 / 问卷系统、处理本地文件或表格(Excel / CSV)、图片 / 票据 OCR、物流或监控等与平台无关的自动化,以及与金数据平台无关的通用数据处理。

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/examples.md`, `references/guide.md` and `references/tools.md`).

It sits in Documents & Office, covering Excel spreadsheets and CSV and tabular files. It works with Model Context Protocol and Microsoft Excel. The repository describes itself as: WorkBuddy skills / connectors / experts archive for offline study. The licence is MIT.

When your agent uses it

  • Tasks that involve Excel spreadsheets
  • Tasks that involve CSV and tabular files

Example prompts

  • “/jinshuju”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. 先看再动:操作未知表单前,先 get_form 拿字段结构——每个字段的 api_code、选项的 choices[].api_code、表格的 dimensions[].api_code。create_entry / update_entry 的键必须是…
  2. filters 优先:list_entries 支持 filters=[{field, operator, value}] 下推过滤,比拉全量再本地筛选快几个数量级。单次上限 50 条,超过用 next(serial_number 游标)翻页。
  3. 先列再改:批量操作前先 list_entries 拉出命中记录展示给用户,用户确认后再逐条循环调用 update_entry / delete_entry,每 20 条汇报一次进度。
  4. 永不主动开 PUT:update_entry 默认 is_put=false(PATCH,只改提供的字段)。is_put=true 会把未提供字段全部清空,只有用户明确说"整条替换"且已列全所有字段时才允许,且需二次确认。
  5. 脱敏展示:输出手机号/邮箱/身份证默认打码(138****1234),除非用户明确要求原文。
  6. 不静默吞错:字段类型不支持、套餐限制、权限不足的报错原文回显并给出替代方案。

What it can do on your machine

Read from SKILL.md and the folder at commit 91b77ea. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • jinshuju.net

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Jinshuju loads about 2k tokens when it runs, and up to ~23k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 482 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~23k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from infometa/workbuddyskills at commit 91b77ea, republished under its MIT licence (© infometa). 482 words, ~2,023 tokens.

Download SKILL.mdSave it as .claude/skills/jinshuju/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
jinshuju
description
通过金数据(Jinshuju,jinshuju.net)MCP 操作用户托管在金数据平台上的在线表单:创建 / 复制 / 编辑表单与主题,含自动判分的考试表单、选项计分的测评表单;查询、新增(单条或批量)、更新、删除、批量修改数据;用上传凭证上传本地图片或文件;查询账户套餐额度与团队成员。仅在用户操作其金数据平台数据时使用——触发信号:提到 金数据 / Jinshuju / jinshuju.net、给出 form_token,或要操作一张已托管在金数据上的表单或数据。不要用于:用代码开发表单 / 问卷系统、处理本地文件或表格(Excel / CSV)、图片 / 票据 OCR、物流或监控等与平台无关的自动化,以及与金数据平台无关的通用数据处理。
slug
jinshuju
displayName
金数据(Jinshuju)
version
1.6.1
author
Jinshuju
license
MIT
platforms
macos, linux, windows

金数据(Jinshuju)

金数据(jinshuju.net)是中国领先的在线表单与数据收集平台。通过金数据 MCP,你可以用自然语言完成表单搭建与数据管理的全流程,替代登录后台手动操作。

When to Use

本 skill 仅处理金数据线上表单平台(jinshuju.net) 的表单搭建与数据管理,且需满足以下任一平台信号才触发:

  • 用户明确提到"金数据"、"Jinshuju"、"jinshuju.net"
  • 用户给出了 form_token,或要操作一张已在金数据上的表单 / 数据(创建、复制、编辑、移动表单,修改主题,增删改查或批量修改 entries,导出数据)
  • 用户要查询本账户的套餐额度、团队成员

When NOT to Use

以下场景不要用本 skill,直接退出、交给通用能力处理:

  • 用代码 / 程序开发表单、问卷、评估系统(如在 Python / 前端项目里"做一个报名表 / 问卷")
  • 处理本地文件、Excel / CSV、文档分析
  • 图片、账单、票据的 OCR / 识别
  • 物流、监控等与金数据平台无关的业务自动化
  • 仅出现"表 / 表单 / 问卷"字眼,但并非操作金数据线上平台

判断不属于金数据平台操作时,不要调用任何 MCP 工具,按通用能力回答即可。

Quick Reference

场景MCP 工具
列出文件夹list_folders
列出表单list_forms
查看表单详情(字段结构)get_form
创建表单create_form
创建考试表单(答案 + 自动判分)create_exam_form
编辑考试表单edit_exam_form
创建测评表单(选项计分 / 维度报告)create_evaluation_form
编辑测评表单edit_evaluation_form
复制表单copy_form
移动表单到文件夹move_form
修改表单字段/设置edit_form
修改表单主题edit_theme
上传本地图片(头图 / 选项配图)prepare_form_image_upload
上传文件写入附件字段prepare_entry_attachment_upload
列出数据list_entries
列出我填写 / 提交过的表单list_my_submitted_forms
列出我在某表单提交的数据list_my_submitted_entries
查看单条数据get_entry
新建数据(单条)create_entry
批量新建数据(一次最多 200 条)create_entries
更新数据(单条)update_entry
删除数据(单条)delete_entry
当前用户信息get_current_user
当前企业账户/套餐get_current_billing_account
列出团队成员list_account_users

Procedure

原则

⚠️ 绝不绕过 MCP:金数据 MCP 工具不可用(未连接 / 授权失败 / 调用持续报错)时立即停止,禁止改用浏览器自动化(Playwright 等)、直接调 GraphQL / REST API、curl 或模拟后台操作来替代——这类非标方式会产出中文乱码、字段不兼容的错误表单。正确做法见下方「MCP 不可用时」。

  1. 先看再动:操作未知表单前,先 get_form 拿字段结构——每个字段的 api_code、选项的 choices[].api_code、表格的 dimensions[].api_code。create_entry / update_entry 的键必须是 api_code,传中文 label 会被服务端丢弃。

  2. filters 优先:list_entries 支持 filters=[{field, operator, value}] 下推过滤,比拉全量再本地筛选快几个数量级。单次上限 50 条,超过用 next(serial_number 游标)翻页。

  3. 先列再改:批量操作前先 list_entries 拉出命中记录展示给用户,用户确认后再逐条循环调用 update_entry / delete_entry,每 20 条汇报一次进度。

  4. 永不主动开 PUT:update_entry 默认 is_put=false(PATCH,只改提供的字段)。is_put=true 会把未提供字段全部清空,只有用户明确说"整条替换"且已列全所有字段时才允许,且需二次确认。

  5. 脱敏展示:输出手机号/邮箱/身份证默认打码(138****1234),除非用户明确要求原文。

  6. 不静默吞错:字段类型不支持、套餐限制、权限不足的报错原文回显并给出替代方案。

典型任务流

① 新建表单

1. create_form,传字段列表 + setting
   (考试 / 测评场景改用 create_exam_form / create_evaluation_form,
    create_form 的 scene 已不支持 exam / evaluation)
2. 返回表单链接和 form_token
3. 如需特殊样式,追加 edit_theme(可用 generate_header_image 让 AI 生成头图,
   本地已有图片则先 prepare_form_image_upload(type=header)上传)

② 条件查询 / 导出

1. get_form → 记下字段 api_code 和选项 api_code
2. list_entries 用 filters 下推条件(选项字段传 api_code 不是 label)
3. next 翻页拿全部数据
4. Markdown 表格展示,表头用 get_form 的 label,关键字段脱敏
5. 询问用户是否需要生成 CSV artifact

③ 批量更新

1. get_form → 拿目标字段 api_code + 目标选项 api_code
2. list_entries + filters 拉出命中集,展示前 10 条 + 总数
3. 用户确认后,逐条循环 update_entry(is_put=false)
4. 每 20 条汇报进度,结束时汇总成功/失败数

④ 批量删除

1. list_entries + filters 拉出命中集,记录 serial_number
2. 必须得到用户显式"确认删除"
3. 逐条循环 delete_entry
4. 每 20 条汇报进度

⑤ 批量导入数据

1. get_form → 拿目标字段 api_code + 选项 api_code
2. 把每行整理成 { api_code: value } 对象(选项传 api_code)
3. create_entries 一次提交(每批 ≤200,超过自行分批循环)
4. 读返回的 created_count + errors(按下标),向用户汇总成功/失败
   注意:不幂等,重复提交会产生重复数据;失败后不要整批重发,按 errors 下标只补失败行
关键格式规范

entry payload 的键是 api_code,不是中文 label:

字段类型正确值格式
TextField / TextArea / NameField纯字符串 "张三"
MobileField纯字符串 "13812345678"
NumberField数字 123 或字符串 "123"
RadioButton / DropDown选项 api_code "city_sh"(不是 label "上海")
CheckBoxapi_code 数组 ["topic_a", "topic_b"]
DateTimeFieldISO 字符串 "2026-05-01 14:30"
TableField对象数组 [{"dim_api_code": value, ...}]

list_entries filters operator 速查:

operator适用字段value 形式
eq / ne所有标量
gt / gte / lt / lte数字、日期标量
between数字、日期[min, max]
any_in / none_in文本、选项数组
like / not_like文本、选项子串(不带 % 通配符)
null / not_null所有省略

特殊字段:created_at(创建时间,配 gte / between 等);creator_id(提交者用户 id,只支持 eq,value 是 entry 返回的 creator_id 字符串)——按提交者查数据用它。

Show full SKILL.md (226 more words)Show less

Pitfalls

  • entry 键写成中文 label → 服务端静默丢弃,报 "Entry attributes cannot be empty";键必须是 api_code
  • 选项字段传 label(如 "男" / "上海")→ 400 invalid choice;传 choices[].api_code
  • is_put=true 做部分更新 → 未提供字段全部清空;部分更新永远保持默认 is_put=false
  • like 带 SQL 通配符("张%" / "%张%")→ 按字面匹配 %,永远查不到;直接传 "张"
  • operator 与字段类型不匹配 → 400,错误信息会列出该字段的可用 operator,照着改
  • 简单字段包成对象({"value": "张三"})→ 直接传字符串
  • TableField 按二维数组传 → 必须是对象数组,键是 dimension 的 api_code
  • 批量新建数据循环调 create_entry → 改用 create_entries 一次提交(≤200 条/批,超过自行分批);它部分成功、按下标返回 errors、不幂等(重复调会生成重复数据)
  • update_entry / delete_entry 找批量版本 → 没有,只支持单条,批量逐条循环(仅新建有批量版 create_entries)
  • 测试号段(13800138000)→ 号段正则校验 400 拒;用真实在用号段
  • 删除整张表单 → MCP 不支持 delete_form,引导用户去后台手动操作
  • ESignatureField / FormulaField 写入 entry → 服务端忽略,写入无效
  • 改选项文案用 remove + add → 会换 api_code,历史数据引用失效;改名用 fields.update_choices.update
  • 选择字段设默认选中用 predefined_value → 选择类字段(单选 / 多选 / 下拉 / 级联)不接受 predefined_value;默认选中改用 choices[].selected: true
  • 字段显示规则 comparator 跟触发字段类型不匹配(如选择字段用 like)→ 整批 field_rules 被拒;选择类用 equal / none_in、评分 / NPS 用 between、文本类用 like / not_like
  • 只传新增的那条 field_rules → 是全量替换、不是合并,会静默清空其余已有规则且无法回滚;改动前先 get_form(带 include_field_rules=true)读全量 → 合并 → 回传完整列表
  • 删字段 / 选项不先查数据 → 删有提交数据的字段 / 选项会永久清除数据且不可恢复;fields.remove / update_choices.remove 前先对每个目标用 check_field_data 查,has_data=true 时把影响告诉用户、确认后再删(edit_form 本身不拦截)
  • 用 create_form 建考试/测评 → scene 枚举已移除 exam / evaluation;用 create_exam_form / create_evaluation_form
  • 考试开限时又把题目设必填 → show_timeout=true 与题目字段 required 互斥;默认不开限时,仅用户明确要求时开
  • FormulaField 引用同一请求新增的字段 → 新字段还没有 api_code,公式里用 <gd-field data-cid="..."> 引用其 cid,不要猜 api_code
  • 编辑考试/测评题目时只传改动的 answers 项 → answers 是整体替换语义,会重建整个答案库;必须传完整列表
  • 限流报错(HTTP 429 / code 14003)把原始 JSON 抛给用户 → 不友好;改为告知"接口请求频繁,请等 1–2 分钟后重试",并放慢节奏、合并可批量的请求降低调用频次;不要立刻疯狂重试

Verification

操作完成后确认:

  • 创建/编辑表单:返回中包含有效 form_token,可访问 https://jinshuju.net/f/{form_token}
  • create_entry:返回包含 serial_number(整数)
  • create_entries:返回 created_count 与提交条数一致,errors 为空(有部分失败时按下标核对原因)
  • update_entry:返回的字段值与提交值一致
  • delete_entry:后续 get_entry 返回 404 或条目不再出现在 list_entries
  • 批量操作:向用户汇报"共 N 条,成功 X 条,失败 Y 条"

MCP 配置

金数据 MCP 端点:https://jinshuju.net/mcp

方式 A · HTTP Basic(API Key/Secret)

bash
echo -n "YOUR_API_KEY:YOUR_API_SECRET" | base64
json
{
  "mcpServers": {
    "jinshuju": {
      "url": "https://jinshuju.net/mcp",
      "headers": { "Authorization": "Basic <BASE64>" }
    }
  }
}

方式 B · OAuth 2.0

json
{
  "mcpServers": {
    "jinshuju": { "url": "https://jinshuju.net/mcp" }
  }
}

常见配置错误:漏 /mcp 后缀、用 http://、Authorization 缺 Basic 前缀、用 command/args(stdio 写法,金数据是远程 HTTP MCP 不支持)。

MCP 不可用时

工具未连接 / 授权失败 / 持续报错时,按顺序降级,不要用任何非标方式替代:

  1. 告知用户"金数据 MCP 未就绪",不要假装已完成操作。
  2. 对照上面的「常见配置错误」引导排查(端点、Basic 前缀、OAuth 授权等)。
  3. 仍不行,就给出在金数据后台(jinshuju.net)手动操作的步骤指引。

超大表单(数十个字段)即使 MCP 正常,也建议先 create_form 建核心字段,再用 edit_form 分批补充,降低超长请求被截断 / 超时的风险。

© infometa, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in experts/jinshuju-expert/skills/jinshuju of infometa/workbuddyskills.

  • SKILL.md
  • references/examples.md
  • references/guide.md
  • references/tools.md
  • scripts/setup.py

Open the folder on GitHubat commit 91b77ea

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VisualizerPinvou/pinvou-agent2.4k—~933Automated safety check: PassMIT
Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences2742 repos~2.7kAutomated safety check: PassApache-2.0

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Questions about Jinshuju

What does Jinshuju do?

通过金数据(Jinshuju,jinshuju.net)MCP 操作用户托管在金数据平台上的在线表单:创建 / 复制 / 编辑表单与主题,含自动判分的考试表单、选项计分的测评表单;查询、新增(单条或批量)、更新、删除、批量修改数据;用上传凭证上传本地图片或文件;查询账户套餐额度与团队成员。仅在用户操作其金数据平台数据时使用——触发信号:提到 金数据 / Jinshuju /…. Jinshuju is an agent skill from infometa/workbuddyskills.

When should I use Jinshuju?

Jinshuju fits situations like: tasks that involve Excel spreadsheets; tasks that involve CSV and tabular files.

How do I install Jinshuju in Claude Code?

Run `npx skills add infometa/workbuddyskills --skill jinshuju -a claude-code`. Or copy the skill folder (experts/jinshuju-expert/skills/jinshuju in infometa/workbuddyskills) into .claude/skills/jinshuju in your project. Claude Code loads it when a task matches its description.

How do I install Jinshuju in Codex?

Run `npx skills add infometa/workbuddyskills --skill jinshuju -a codex`. Or copy the skill folder (experts/jinshuju-expert/skills/jinshuju in infometa/workbuddyskills) into .agents/skills/jinshuju in your project. Codex loads it when a task matches its description.

Can I use Jinshuju in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add infometa/workbuddyskills --skill jinshuju -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jinshuju, .gemini/skills/jinshuju, .github/skills/jinshuju and .opencode/skills/jinshuju in your project.

What does Jinshuju need to run?

Going by SKILL.md and its folder, Jinshuju needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Jinshuju access the network?

SKILL.md names 1 domain. In commands or code: jinshuju.net; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Jinshuju safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Jinshuju use?

Jinshuju is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Jinshuju use?

About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 21k tokens, read only when the agent opens those files.

What are the alternatives to Jinshuju?

Skills that share tags, products or a category with Jinshuju: Data Table Manager (n8n-io/n8n, 207k stars), Datalion (HybridAIOne/hybridclaw, 159 stars), Library (crane-in-clear-sky/WorkWit-AI-Agent, 115 stars) and Visualizer (Pinvou/pinvou-agent, 2.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jinshuju?

infometa (a GitHub user) maintains it in infometa/workbuddyskills, which has 348 GitHub stars. The repository holds 218 skills in this directory. The repository was last updated on October 9, 2026.

Source: infometa/workbuddyskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.