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Agent Skill · 开发

json-no-code-connector(JSON NO 代码 connector)

json-no-code-connector 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

json-no-code-connector 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在开发类的 21,746 个 Skill 里排第 13,774。

总安装 824周安装 34GitHub Stars 14下载 269核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:json-no-code-connector(JSON NO 代码 connector)
来源仓库:https://github.com/stahura/domo-ai-vibe-rules
仓库路径:skills/json-no-code-connector
安装命令:
npx skills add https://github.com/stahura/domo-ai-vibe-rules --skill json-no-code-connector
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/stahura/domo-ai-vibe-rules --skill json-no-code-connector

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于处理 GitHub 仓库、Issue、Pull Request 等协作信息。适合围绕代码变更和协作事项进行整理分析。可辅助理解项目状态和开发流程。json-no-code-connector 属于开发类 Skill,可作为该场景下的辅助能力补充。建议先确认权限范围和维护状态再投入使用。

注意避免过度依赖自动化处理敏感协作内容。

来源仓库内路径:skills/json-no-code-connector

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/stahura/domo-ai-vibe-rules --skill json-no-cod…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

json-no-code-connector 怎么安装?

在终端执行 npx skills add https://github.com/stahura/domo-ai-vibe-rules --skill json-no-code-connecto…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

json-no-code-connector 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

json-no-code-connector 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

json-no-code-connector 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

json-no-code-connector 用的人多吗?

公开数据是累计安装 824 次,近一周安装 34 次,下载 269 次,GitHub 14 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

json-no-code-connector 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
json-no-code-connector

JSON NO 代码 connector · 本页

82414接触敏感数据未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Domo JSON Connector — Product API Reference

Primary data ingestion path for REST/JSON APIs. Always try the JSON connector first when the source is a REST API. If it fails (auth, parsing, or pagination issues), fall back to the Java CLI (domo-data-upload skill). See that skill's guide for the two-path fallback pattern.

Overview

The Domo JSON (No Code) connector uses dataProviderType: "json5". It is managed via the Product API:

POST /api/data/v1/accounts          Create an account
GET  /api/data/v1/accounts           List all accounts
GET  /api/data/v1/accounts/{id}      Get a specific account
POST /api/data/v1/streams                      Create a connector (stream)
GET  /api/data/v1/streams                      List all streams
GET  /api/data/v1/streams?limit=500            List streams (paginated)
POST /api/data/v1/streams/{id}/executions      Run a stream

Authentication to the API itself uses the X-Domo-Developer-Token header.

Workflow

Creating a JSON connector requires four steps in order:

  1. Inspect the API — fetch the target URL and examine the JSON structure to determine the correct parsing rules.
  2. Create an account (POST /api/data/v1/accounts) — defines the authentication method (none, basic auth, or API key) for the target API.
  3. Create a stream (POST /api/data/v1/streams) — defines the connector configuration (URL, paging, parsing) and links it to the account created in step 2.
  4. Run the stream (POST /api/data/v1/streams/{id}/executions) — triggers the connector to fetch data and populate the dataset.

You must create the account before the stream, because the stream requires an accountId reference.

Step 1: Inspect the API and plan parsing

Before creating the connector, fetch the API URL and examine the JSON response to determine the correct jsonParsing rules. The goal is to flatten nested JSON into a tabular structure (rows and columns).

curl -s "https://api.example.com/v1/data" | python3 -m json.tool | head -50

Identify the response shape and choose the right pattern:

Pattern A: Top-level flat array — no parsing needed

If the response is already a flat array of objects, no parsing rules are required. Each array element becomes a row, each key becomes a column.

[
  { "id": 1, "title": "...", "body": "...", "userId": 1 },
  { "id": 2, "title": "...", "body": "...", "userId": 1 }
]

Parsing: {"parsing": ""}

Result columns: id, title, body, userId

Tested with: JSONPlaceholder (/posts) → 100 rows, 4 columns. Jokes API (/jokes/ten) → 10 rows, 4 columns (type, setup, punchline, id).

Pattern B: Object wrapping an array — use expandRow

If the response is an object with a nested array of records, use expandRow to turn each array element into a row.

{
  "current_page": 1,
  "total": 332,
  "data": [
    { "fact": "Cats sleep 70% of their lives.", "length": 30 },
    { "fact": "A group of cats is called a clowder.", "length": 38 }
  ]
}

Parsing: {"parsing": "0.1:expandRow(data)\n"}

Result columns: data_fact, data_length, plus all top-level fields (current_page, total, per_page, etc.) repeated on every row.

Important: After expandRow, the nested fields are prefixed with the array name. So data[].fact becomes data_fact.

Tested with: Cat Facts (catfact.ninja/facts) → 100 rows. The data array was expanded, and each fact became a row with the parent metadata repeated.

Pattern C: Top-level array with nested objects — use flattenObject

If the response is a top-level array but each element contains nested objects, use flattenObject to promote the nested keys to top-level columns.

[
  {
    "name": { "common": "France", "official": "French Republic" },
    "capital": ["Paris"],
    "region": "Europe",
    "population": 67390000
  }
]

Parsing: {"parsing": "0.0:flattenObject(name)\n"}

Result columns: name_common, name_official, capital, region, population. The nativeName sub-object (deeper nesting) remains as a JSON string unless further flattened.

Depth notation: For top-level arrays, use 0.0 (first object in array). For nested arrays after expandRow, the depth increases (e.g. 0.1.0).

Tested with: REST Countries → 250 rows. flattenObject(name) produced name_common and name_official as separate columns. The deeper nativeName stayed as a JSON string.

Pattern D: Single object with nested objects — use multiple flattenObject

If the response is a single object (1 row) with nested objects, flatten each nested object separately.

{
  "latitude": 40.76,
  "longitude": -111.89,
  "current_weather": {
    "temperature": 11.6,
    "windspeed": 2.2,
    "winddirection": 270
  },
  "current_weather_units": {
    "temperature": "°C",
    "windspeed": "km/h"
  }
}

Parsing: {"parsing": "0.0:flattenObject(current_weather)\n0.0:flattenObject(current_weather_units)\n"}

Result columns: latitude, longitude, current_weather_temperature, current_weather_windspeed, current_weather_winddirection, current_weather_units_temperature, current_weather_units_windspeed, etc.

Multiple flattenObject rules can share the same depth (0.0) when they operate on sibling objects at the same level.

Tested with: Open-Meteo Weather API → 1 row, 21 columns. Both current_weather and current_weather_units were flattened with prefixed column names.

Pattern E: Object with array + nested objects — combine expandRow + flattenObject

For complex responses like GeoJSON, chain operations. The expandRow runs first, then flattenObject operates on the expanded results.

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": { "event": "Flood Warning", "severity": "Moderate" },
      "geometry": { ... }
    }
  ]
}

Parsing:

0.1:expandRow(features)
0.1.0:flattenObject(features_properties)

Key detail: After expandRow(features), the nested field properties is referenced as features_properties (prefixed with the array name).

Tested with: NWS Weather Alerts API → expanded features array into rows, then flattened properties into individual columns.

Parsing rules reference
OperationSyntaxWhen to use
expandRow(field)depth:expandRow(arrayField)Object contains an array that should become rows
flattenObject(field)depth:flattenObject(objectField)Record contains a nested object whose keys should become columns

Depth notation:

  • 0.0 — top-level (first element of array, or root object)
  • 0.1 — one level in (e.g. a field within the root object)
  • 0.1.0 — two levels in (e.g. after an expandRow, within each expanded element)

Rules for field names after operations:

  • After expandRow(data), child fields are prefixed: data.fact → data_fact
  • After flattenObject(name), child fields are prefixed: name.common → name_common
  • Deeper nesting that isn't explicitly flattened remains as a JSON string in the column

Authentication Types

The JSON connector supports multiple credentialsType values that control how the connector authenticates to the target API.

No Auth

Use credentialsType: "fields" with authentication set to "none". For public APIs that require no credentials.

curl -X POST "https://{instance}.domo.com/api/data/v1/accounts" \
  -H "X-Domo-Developer-Token: {devToken}" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "My Public API Account",
    "displayName": "My Public API Account",
    "type": "data",
    "allowExternalUse": true,
    "dataProviderType": "json5",
    "credentialsType": "fields",
    "configurations": {
      "authentication": "none"
    }
  }'

Basic Auth (username/password)

Use credentialsType: "fields" with username and password in configurations.

curl -X POST "https://{instance}.domo.com/api/data/v1/accounts" \
  -H "X-Domo-Developer-Token: {devToken}" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "My Basic Auth Account",
    "displayName": "My Basic Auth Account",
    "type": "data",
    "allowExternalUse": true,
    "dataProviderType": "json5",
    "credentialsType": "fields",
    "configurations": {
      "username": "user@example.com",
      "password": "yourPassword"
    }
  }'

API Key in Header

Use credentialsType: "apikey_header" with apiKey in configurations.

curl -X POST "https://{instance}.domo.com/api/data/v1/accounts" \
  -H "X-Domo-Developer-Token: {devToken}" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "My API Key Account",
    "displayName": "My API Key Account",
    "type": "data",
    "allowExternalUse": true,
    "dataProviderType": "json5",
    "credentialsType": "apikey_header",
    "configurations": {
      "apiKey": "your-api-key-here"
    }
  }'

Response

The API returns the created account object. Note:

  • configurations will be returned as {} (empty) — credentials are not echoed back for security.
  • valid may show false in the response but the account is functional on the front-end.
  • createdAt / modifiedAt may be null in the initial response.

Example response

{
  "id": 117,
  "userId": 149955692,
  "name": "My API Key Account",
  "displayName": "My API Key Account",
  "type": "data",
  "valid": false,
  "allowExternalUse": true,
  "dataProviderType": "json5",
  "credentialsType": "apikey_header",
  "createdAt": null,
  "createdBy": 149955692,
  "modifiedAt": null,
  "modifiedBy": 149955692,
  "secretManagerAccountId": null,
  "secretId": null,
  "configurations": {},
  "accountId": 117,
  "accountTemplateId": null,
  "accountTemplateAuthorizationId": null
}

Creating a Connector (Stream)

Use POST /api/data/v1/streams to create a fully configured JSON connector with a linked account.

Required fields

FieldDescription
transportMust include type: "CONNECTOR", description: "com.domo.connector.json.customparsing", version: "4"
updateMethod"REPLACE" or "APPEND"
dataProvider{"key": "json5"}
account{"id": <accountId>, "accountId": <accountId>} — reference a previously created account
dataSource{"name": "...", "description": "..."} — creates the dataset
configurationArray of {category, name, type, value} metadata objects (see below)

Configuration array

Each entry is a METADATA object with a stringified JSON value. The key entries:

namePurpose
jsonSelectionURL, HTTP method, headers, query params, date filters, connection method
jsonPagingPagination config: type (offset/token/etc.), limit, base URL
jsonParsingParsing rules (e.g. flattenObject(owner))
schema{"automatedSchema": true} for auto-detect
cloudCloud identifier (e.g. "domo")
_description_Dataset description (can be empty string)

Full example

curl -X POST "https://{instance}.domo.com/api/data/v1/streams" \
  -H "X-Domo-Developer-Token: {devToken}" \
  -H "Content-Type: application/json" \
  -d '{
  "transport": {
    "type": "CONNECTOR",
    "description": "com.domo.connector.json.customparsing",
    "version": "4"
  },
  "updateMethod": "REPLACE",
  "dataProvider": {
    "key": "json5"
  },
  "account": {
    "id": 116,
    "accountId": 116
  },
  "dataSource": {
    "name": "My JSON Connector",
    "description": "Created via API"
  },
  "configuration": [
    {
      "category": "METADATA",
      "name": "jsonSelection",
      "type": "string",
      "value": "{\"connectionMethod\":\"Advanced\",\"jsonUrl\":\"https://api.example.com/v1/data\",\"httpMethod\":\"GET\",\"jsonLineReader\":\"false\",\"escapeBackslash\":\"false\",\"httpsHeaders\":[],\"body\":\"\",\"queryParameters\":[],\"dynamicSetup\":[{}],\"useDateFilter\":false,\"dateSelection\":{\"dateType\":\"date_range\",\"startDate\":{\"type\":\"relative\",\"offset\":0},\"endDate\":{\"type\":\"relative\",\"offset\":0}},\"dateQueryParamsFormat\":\"yyyy-MM-dd\",\"certificateInputType\":\"NoCertificate\",\"encodeParameterKey\":true,\"encodeParameterValue\":true,\"datasetType\":\"static\",\"dateParameter\":{\"dateType\":\"single_date\",\"dateFrom\":\"relative\",\"dateFromOffset\":1,\"dateTo\":\"relative\",\"dateToOffset\":0,\"date\":\"relative\",\"dateOffset\":1},\"useBody\":false,\"dynamicValuesType\":\"enter\",\"rateLimitSelection\":\"false\",\"timeUnit\":\"second\",\"dateParameterType\":\"separate\",\"useDateAtMidnight\":false}"
    },
    {
      "category": "METADATA",
      "name": "jsonPaging",
      "type": "string",
      "value": "{\"baseUrl\":\"https://api.example.com/v1/data\",\"tokenType\":\"path\",\"pagingType\":\"offset\",\"parsing\":\"\",\"total\":\"false\",\"pageLimitValue\":\"50\",\"startPage\":\"1\",\"encodeParameterValue\":true,\"encodeParameterKey\":true,\"offsetParameter\":\"offset\",\"pageLimitParameter\":\"limit\"}"
    },
    {
      "category": "METADATA",
      "name": "jsonParsing",
      "type": "string",
      "value": "{\"parsing\":\"\"}"
    },
    {
      "category": "METADATA",
      "name": "schema",
      "type": "string",
      "value": "{\"automatedSchema\":true}"
    },
    {
      "category": "METADATA",
      "name": "cloud",
      "type": "string",
      "value": "domo"
    },
    {
      "category": "METADATA",
      "name": "_description_",
      "type": "string",
      "value": ""
    }
  ]
}'

Stream response notes

  • The response includes the full dataProvider with authenticationSchemeConfiguration showing all available credential fields.
  • dataSource.id in the response is the new dataset UUID.
  • account.valid will show true if the account was created with credentials.
  • Default schedule is MANUAL. Set advancedScheduleJson for automated runs (e.g. {"type":"DAY","at":"06:00 AM","timezone":"America/Denver"}).

Running a Stream (Execution)

After creating a stream, trigger it to run with POST /api/data/v1/streams/{streamId}/executions.

curl -X POST "https://{instance}.domo.com/api/data/v1/streams/{streamId}/executions" \
  -H "X-Domo-Developer-Token: {devToken}" \
  -H "Content-Type: application/json"

Example response

{
  "streamId": 561,
  "executionId": 2,
  "startedAt": 1774666802.49,
  "endedAt": null,
  "updateMethod": "REPLACE",
  "currentState": "ACTIVE",
  "rowsInserted": 0,
  "bytesInserted": 0,
  "startedBy": "149955692",
  "errors": []
}

Execution notes

  • currentState will be "ACTIVE" while running, then "SUCCESS" or "ERROR" when complete.
  • No request body is needed — just POST to the endpoint.
  • After creating a stream, always trigger an execution so data is populated immediately.

HubSpot CRM Pattern

HubSpot's CRM API (/crm/v3/objects/{type}) wraps records in a results array, and each record has a nested properties object. Use Pattern E (expandRow + flattenObject):

Response shape:

{
  "results": [
    { "id": "123", "properties": { "email": "...", "firstname": "..." } }
  ],
  "paging": { "next": { "after": "124" } }
}

Parsing rules:

0.1:expandRow(results)
0.1.0:flattenObject(results_properties)

Auth: Use credentialsType: "fields" / authentication: "none" for the account, and inject the Bearer token in jsonSelection.httpsHeaders:

"httpsHeaders": [{"name": "Authorization", "value": "Bearer pat-na2-..."}]

Result columns: results_id, results_properties_email, results_properties_firstname, etc.

Important Notes

  • The PUT and PATCH methods are not supported on /api/data/v1/accounts/{id} — returns 405. To change credentials, create a new account.
  • The authType field is not a valid configuration for json5 — using it returns a 400 error: "Data provider 'json5' does not have 'authType' authentication scheme configuration".
  • Always set type: "data" for data connector accounts.
  • The configuration array values must be stringified JSON — not nested objects.

平台分布

Codex

39.33%
按下载量换算106

Claude

28%
按下载量换算75

Cursor

17.74%
按下载量换算48

Gemini CLI

8.9%
按下载量换算24

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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