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Agent Skill · 研究检索

add-sample-data(添加样本数据)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

add-sample-data 是研究检索类 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 49,433。

总安装 652周安装 28GitHub Stars 228下载 228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:add-sample-data(添加样本数据)
来源仓库:https://github.com/microsoft/power-platform-skills
仓库路径:skills/add-sample-data
安装命令:
npx skills add https://github.com/microsoft/power-platform-skills --skill add-sample-data
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/microsoft/power-platform-skills --skill add-sample-data

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

通过 OData API 向 Dataverse 表填充示例记录,用于测试和演示 Power Pages 站点。适用于快速搭建 demo 环境,验证页面功能和数据展示效果。按插入顺序优先处理父表,确保外键引用可用,避免数据错误。失败时仅记录日志并继续,不自动回滚,保证部分成功仍可使用。

需提前配置 PAC CLI 和 Azure CLI 认证,确保有权限写入目标表。

来源仓库内路径:skills/add-sample-data

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/microsoft/power-platform-skills --skill add-sa…;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

add-sample-data 怎么安装?

在终端执行 npx skills add https://github.com/microsoft/power-platform-skills --skill add-sample-data。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

add-sample-data 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。

add-sample-data 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。

add-sample-data 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。

add-sample-data 用的人多吗?

公开数据是累计安装 652 次,近一周安装 28 次,下载 228 次,GitHub 228 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。

add-sample-data 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
add-sample-data

添加样本数据 · 本页

652228接触敏感数据未明确有提醒

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

Plugin check: Run node "${CLAUDE_PLUGIN_ROOT}/scripts/check-version.js" — if it outputs a message, show it to the user before proceeding.

Add Sample Data

Populate Dataverse tables with sample records via OData API so users can test and demo their Power Pages sites.

Core Principles

  • Respect insertion order: Always insert parent/referenced tables before child/referencing tables so lookup IDs are available when needed.
  • Use TaskCreate/TaskUpdate: Track all progress throughout all phases -- create the todo list upfront with all phases before starting any work.
  • Fail gracefully: On insertion failure, log the error and continue with remaining records -- never attempt automated rollback.

Initial request: $ARGUMENTS


Phase 1: Verify Prerequisites

Goal: Confirm PAC CLI auth, acquire an Azure CLI token, and verify API access

Actions:

  1. Create todo list with all 6 phases (see Progress Tracking table)
  2. Follow the prerequisite steps in ${CLAUDE_PLUGIN_ROOT}/references/dataverse-prerequisites.md to verify PAC CLI auth, acquire an Azure CLI token, and confirm API access. Note the environment URL as <envUrl> for subsequent script calls.

Output: Authenticated session with valid token and confirmed API access


Phase 2: Discover Tables

Goal: Find the custom tables available in the user's Dataverse environment

Actions:

Path A: Read .datamodel-manifest.json (Preferred)

Check if .datamodel-manifest.json exists in the project root (written by the setup-datamodel skill). If it exists, read it -- it already contains table logical names, display names, and column info.

See ${CLAUDE_PLUGIN_ROOT}/references/datamodel-manifest-schema.md for the full manifest schema.

Path B: Query OData API (Fallback)

If no manifest exists, discover custom tables via OData:

node "${CLAUDE_PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET "EntityDefinitions?\$select=LogicalName,DisplayName,EntitySetName&\$filter=IsCustomEntity eq true"

For each discovered table, fetch its custom columns:

node "${CLAUDE_PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET "EntityDefinitions(LogicalName='<table>')/Attributes?\$select=LogicalName,DisplayName,AttributeType,RequiredLevel&\$filter=IsCustomAttribute eq true"

2.1 Present Available Tables

Show the user the list of discovered tables with their columns so they can choose which to populate.

Output: List of discovered tables with their columns presented to the user


Phase 3: Select Tables & Configure

Goal: Gather user preferences on which tables to populate and how many records to create

Actions:

3.1 Select Tables

Use AskUserQuestion to ask which tables they want to populate (use multiSelect: true). List all discovered tables as options.

3.2 Select Record Count

Use AskUserQuestion to ask how many sample records per table:

OptionDescription
5 recordsQuick test -- just enough to verify the setup
10 recordsLight demo data for basic testing
25 recordsFuller dataset for realistic demos
CustomLet the user specify a number

3.3 Determine Insertion Order

Analyze relationships between selected tables. Parent/referenced tables must be inserted first so their IDs are available for child/referencing table lookups.

Build the insertion order:

  1. Tables with no lookup dependencies (parent tables) -- insert first
  2. Tables that reference already-inserted tables -- insert next
  3. Continue until all tables are ordered

Output: Confirmed table selection, record count, and insertion order


Phase 4: Generate & Review Sample Data

Goal: Generate contextually appropriate sample records and get user approval before inserting

Actions:

4.1 Generate Contextual Sample Data

For each selected table, generate sample records with contextually appropriate values based on column names and types:

  • String columns: Generate realistic values matching the column name (e.g., "Email" -> jane.doe@example.com, "Phone" -> (555) 123-4567, "Name" -> realistic names)
  • Memo columns: Generate short descriptive text relevant to the column name
  • Integer/Decimal/Currency columns: Generate reasonable numeric values
  • DateTime columns: Generate dates within a sensible range (past year to next month)
  • Boolean columns: Mix of true and false values
  • Picklist/Choice columns: Query valid options first (see references/odata-record-patterns.md), then use actual option values
  • Lookup columns: Reference records from parent tables that will be/were already inserted

4.2 Present Sample Data Preview

For each table, show a markdown table previewing the sample records directly in the conversation:

### Project (cr123_project) -- 5 records

| Name | Description | Status | Start Date |
|------|-------------|--------|------------|
| Website Redesign | Modernize the corporate website | 100000000 (Active) | 2025-03-15 |
| Mobile App | Build iOS and Android app | 100000001 (Planning) | 2025-04-01 |
| ... | ... | ... | ... |

Show relationship handling: which lookup fields reference which parent table records.

Output: Sample data plan ready for insertion. Proceed directly to Phase 5.


Phase 5: Insert Sample Data

Goal: Execute OData POST calls to create all approved sample records with correct relationship handling

Actions:

Refer to references/odata-record-patterns.md for full patterns.

5.1 Get Entity Set Names

For each table, get the entity set name (needed for the API URL):

node "${CLAUDE_PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET "EntityDefinitions(LogicalName='<table>')?\$select=EntitySetName"

5.2 Get Picklist Options

For any picklist/choice columns, query valid option values before insertion:

node "${CLAUDE_PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET "EntityDefinitions(LogicalName='<table>')/Attributes(LogicalName='<column>')/Microsoft.Dynamics.CRM.PicklistAttributeMetadata?\$expand=OptionSet"

Use the actual Value integers from the option set in your sample data.

5.3 Insert Parent Tables First

Insert records into parent/referenced tables first to capture their IDs:

node "${CLAUDE_PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST "<EntitySetName>" --body '{"cr123_name":"Sample Record","cr123_description":"A sample record for testing"}' --include-headers

The --include-headers flag includes the OData-EntityId response header, which contains the created record ID. Parse the GUID from the response to use in child table lookups.

Store parent record IDs for use in child table lookups.

5.4 Insert Child Tables with Lookups

For child/referencing tables, use @odata.bind syntax to set lookup fields:

node "${CLAUDE_PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST "<ChildEntitySetName>" --body '{"cr123_name":"Child Record","cr123_ParentId@odata.bind":"/<ParentEntitySetName>(<parent_guid>)"}' --include-headers

5.5 Track Progress

Track each insertion attempt:

  • Record table name, record number, success/failure
  • On failure, log the error message but continue with remaining records
  • Do NOT attempt automated rollback on failure

5.6 Refresh Token Periodically

The dataverse-request.js script handles 401 token refresh internally. For long-running operations (many records), periodically re-run verify-dataverse-access.js to confirm the session is still valid:

node "${CLAUDE_PLUGIN_ROOT}/scripts/verify-dataverse-access.js" <envUrl>

Output: All approved records inserted with parent-child relationships established


Phase 6: Verify & Summarize

Goal: Confirm record counts and present a final summary to the user

Actions:

6.1 Verify Record Counts

For each table that was populated, query the record count:

node "${CLAUDE_PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET "<EntitySetName>?\$count=true&\$top=0"

The @odata.count field in the response gives the total record count.

6.2 Record Skill Usage

Reference: ${CLAUDE_PLUGIN_ROOT}/references/skill-tracking-reference.md

Follow the skill tracking instructions in the reference to record this skill's usage. Use --skillName "AddSampleData".

6.3 Present Summary

Present a summary table:

TableRecords RequestedRecords CreatedFailures
cr123_project (Project)10100
cr123_task (Task)1091

Include:

  • Total records created across all tables
  • Any failures with error details
  • Lookup relationships that were established

6.4 Suggest Next Steps

After the summary, suggest:

  • Review the data in the Power Pages maker portal or model-driven app
  • If the site is not yet built: /create-site
  • If the site is ready to deploy: /deploy-site

Output: Verified record counts and summary presented to the user


Important Notes

Throughout All Phases

  • Use TaskCreate/TaskUpdate to track progress at every phase
  • Ask for user confirmation at key decision points (see list below)
  • Respect insertion order -- always insert parent tables before child tables
  • Fail gracefully -- log errors and continue, never rollback automatically
  • Refresh tokens every 20 records to avoid expiration

Key Decision Points (Wait for User)

  1. After Phase 2: Confirm which tables to populate
  2. After Phase 3: Confirm record count and insertion order
  3. After Phase 6: Review summary and decide next steps

Progress Tracking

Before starting Phase 1, create a task list with all phases using TaskCreate:

Task subjectactiveFormDescription
Verify prerequisitesVerifying prerequisitesConfirm PAC CLI auth, acquire Azure CLI token, verify API access
Discover tablesDiscovering tablesRead.datamodel-manifest.json or query OData API for custom tables
Select tables and configureConfiguring tablesUser picks tables, record count, and determine insertion order
Generate and review sample dataGenerating sample dataGenerate contextual sample records, present preview, get user approval
Insert sample dataInserting recordsExecute OData POST calls with relationship handling and token refresh
Verify and summarizeVerifying resultsConfirm record counts, present summary, suggest next steps

Mark each task in_progress when starting it and completed when done via TaskUpdate. This gives the user visibility into progress and keeps the workflow deterministic.


Begin with Phase 1: Verify Prerequisites

平台分布

Codex

36.58%
按下载量换算83

Claude

30.16%
按下载量换算69

Cursor

16.87%
按下载量换算38

Gemini CLI

9.74%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

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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