feat(skills): complete multi-agent collaboration framework
## Skills Ecosystem (60+ Skills) - Engineering: 7 skills (ai-engineer, backend-architect, etc.) - Testing: 8 skills (reality-checker, evidence-collector, etc.) - Support: 6 skills (support-responder, analytics-reporter, etc.) - Design: 7 skills (ux-architect, brand-guardian, etc.) - Product: 3 skills (sprint-prioritizer, trend-researcher, etc.) - Marketing: 4+ skills (growth-hacker, content-creator, etc.) - PM: 5 skills (studio-producer, project-shepherd, etc.) - Spatial: 6 skills (visionos-spatial-engineer, etc.) - Specialized: 6 skills (agents-orchestrator, etc.) ## Collaboration Framework - Coordination protocols (handoff-templates, agent-activation) - 7-phase playbooks (Discovery → Operate) - Standardized skill template for consistency ## Quality Improvements - Each skill now includes: Identity, Mission, Workflow, Deliverable Format - Collaboration triggers define when to invoke other agents - Success metrics provide measurable quality standards Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
iven
349
skills/sales-data-extraction-agent/SKILL.md
Normal file
349
skills/sales-data-extraction-agent/SKILL.md
Normal file
@@ -0,0 +1,349 @@
|
||||
---
|
||||
name: sales-data-extraction-agent
|
||||
description: "销售数据提取 Agent - 从 CRM、ERP、电商平台自动提取和标准化销售数据"
|
||||
triggers:
|
||||
- "销售数据"
|
||||
- "CRM提取"
|
||||
- "订单数据"
|
||||
- "客户数据"
|
||||
- "销售分析"
|
||||
- "收入数据"
|
||||
tools:
|
||||
- bash
|
||||
- read
|
||||
- write
|
||||
- grep
|
||||
- glob
|
||||
---
|
||||
|
||||
# Sales Data Extraction Agent - 销售数据提取 Agent
|
||||
|
||||
从多种销售系统 (CRM、ERP、电商平台) 自动提取、清洗和标准化销售数据的智能 Agent。
|
||||
|
||||
## 能力
|
||||
|
||||
- **多源提取**: Salesforce、HubSpot、SAP、Shopify、淘宝等
|
||||
- **数据清洗**: 去重、格式统一、缺失值处理
|
||||
- **实时同步**: 增量提取、变更捕获 (CDC)
|
||||
- **数据验证**: 业务规则校验、异常检测
|
||||
- **标准化输出**: 统一数据模型、API 接口
|
||||
|
||||
## 工具依赖
|
||||
|
||||
- bash: 执行数据提取脚本、API 调用
|
||||
- read: 读取配置、映射规则、缓存数据
|
||||
- write: 输出提取数据、日志报告
|
||||
- grep: 搜索数据模式、日志分析
|
||||
- glob: 查找数据文件、配置
|
||||
|
||||
## 支持的数据源
|
||||
|
||||
| 类型 | 系统 | 协议 | 认证 |
|
||||
|------|------|------|------|
|
||||
| CRM | Salesforce | REST API | OAuth 2.0 |
|
||||
| CRM | HubSpot | REST API | API Key |
|
||||
| ERP | SAP S/4HANA | OData | Basic Auth |
|
||||
| ERP | Oracle NetSuite | REST API | OAuth 1.0 |
|
||||
| 电商 | Shopify | GraphQL | API Key |
|
||||
| 电商 | WooCommerce | REST API | Basic Auth |
|
||||
| 电商 | 淘宝/天猫 | Open API | OAuth 2.0 |
|
||||
|
||||
## 统一销售数据模型
|
||||
|
||||
### Order (订单)
|
||||
```json
|
||||
{
|
||||
"order_id": "ORD-2024-001234",
|
||||
"external_id": "SF-00123456",
|
||||
"source_system": "salesforce",
|
||||
"customer_id": "CUST-001",
|
||||
"order_date": "2024-01-15T10:30:00Z",
|
||||
"status": "completed",
|
||||
"currency": "USD",
|
||||
"subtotal": 1500.00,
|
||||
"tax": 150.00,
|
||||
"discount": 50.00,
|
||||
"total": 1600.00,
|
||||
"line_items": [
|
||||
{
|
||||
"product_id": "PROD-001",
|
||||
"product_name": "Enterprise License",
|
||||
"quantity": 1,
|
||||
"unit_price": 1500.00,
|
||||
"category": "Software"
|
||||
}
|
||||
],
|
||||
"shipping_address": {
|
||||
"country": "US",
|
||||
"state": "CA",
|
||||
"city": "San Francisco"
|
||||
},
|
||||
"metadata": {
|
||||
"sales_rep": "John Doe",
|
||||
"campaign": "Q1_Promo",
|
||||
"extracted_at": "2024-01-15T12:00:00Z"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Customer (客户)
|
||||
```json
|
||||
{
|
||||
"customer_id": "CUST-001",
|
||||
"external_id": "ACC-001234",
|
||||
"source_system": "salesforce",
|
||||
"company_name": "Acme Corp",
|
||||
"industry": "Technology",
|
||||
"size": "Enterprise",
|
||||
"contact": {
|
||||
"name": "Jane Smith",
|
||||
"email": "jane@acme.com",
|
||||
"phone": "+1-555-0100"
|
||||
},
|
||||
"address": {
|
||||
"country": "US",
|
||||
"state": "CA",
|
||||
"city": "San Francisco"
|
||||
},
|
||||
"metrics": {
|
||||
"lifetime_value": 50000.00,
|
||||
"total_orders": 12,
|
||||
"first_order_date": "2022-06-01",
|
||||
"last_order_date": "2024-01-15"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## 提取流程
|
||||
|
||||
### Step 1: 连接配置
|
||||
```bash
|
||||
# 验证数据源连接
|
||||
validate_connection --source salesforce --config salesforce.yaml
|
||||
|
||||
# 测试 API 访问
|
||||
test_api --source salesforce --endpoint /services/data/v58.0/query
|
||||
```
|
||||
|
||||
### Step 2: 增量提取
|
||||
```bash
|
||||
# 获取上次同步点
|
||||
LAST_SYNC=$(get_last_sync --source salesforce)
|
||||
|
||||
# 构建增量查询
|
||||
QUERY="SELECT Id, Name, Amount, CloseDate FROM Opportunity
|
||||
WHERE LastModifiedDate > $LAST_SYNC"
|
||||
|
||||
# 执行提取
|
||||
extract_data --source salesforce --query "$QUERY" --output opportunities.json
|
||||
```
|
||||
|
||||
### Step 3: 数据清洗
|
||||
```bash
|
||||
# 去重处理
|
||||
deduplicate --input opportunities.json --key external_id --output deduped.json
|
||||
|
||||
# 格式标准化
|
||||
standardize --input deduped.json --mapping salesforce-mapping.yaml --output standardized.json
|
||||
|
||||
# 验证规则
|
||||
validate --input standardized.json --rules sales-validation.yaml
|
||||
```
|
||||
|
||||
### Step 4: 数据加载
|
||||
```bash
|
||||
# 加载到目标存储
|
||||
load_data --input standardized.json --target data-lake/orders/
|
||||
|
||||
# 更新同步点
|
||||
update_sync_point --source salesforce --timestamp $(date -u +"%Y-%m-%dT%H:%M:%SZ")
|
||||
```
|
||||
|
||||
## Salesforce 提取配置
|
||||
|
||||
```yaml
|
||||
# salesforce.yaml
|
||||
source:
|
||||
name: salesforce
|
||||
type: crm
|
||||
api_version: "58.0"
|
||||
|
||||
connection:
|
||||
client_id: ${SALESFORCE_CLIENT_ID}
|
||||
client_secret: ${SALESFORCE_CLIENT_SECRET}
|
||||
username: ${SALESFORCE_USERNAME}
|
||||
password: ${SALESFORCE_PASSWORD}
|
||||
security_token: ${SALESFORCE_SECURITY_TOKEN}
|
||||
sandbox: false
|
||||
|
||||
extraction:
|
||||
objects:
|
||||
- name: Opportunity
|
||||
query: |
|
||||
SELECT Id, Name, AccountId, Amount, CloseDate, StageName,
|
||||
Probability, Type, LeadSource, CampaignId,
|
||||
CreatedDate, LastModifiedDate
|
||||
FROM Opportunity
|
||||
WHERE LastModifiedDate > {last_sync}
|
||||
mapping: opportunity-mapping.yaml
|
||||
schedule: "*/15 * * * *" # 每 15 分钟
|
||||
|
||||
- name: Account
|
||||
query: |
|
||||
SELECT Id, Name, Industry, NumberOfEmployees,
|
||||
BillingCountry, BillingState, BillingCity,
|
||||
CreatedDate, LastModifiedDate
|
||||
FROM Account
|
||||
WHERE LastModifiedDate > {last_sync}
|
||||
mapping: account-mapping.yaml
|
||||
schedule: "*/30 * * * *" # 每 30 分钟
|
||||
|
||||
rate_limits:
|
||||
requests_per_second: 5
|
||||
concurrent_requests: 10
|
||||
```
|
||||
|
||||
## 数据映射规则
|
||||
|
||||
```yaml
|
||||
# opportunity-mapping.yaml
|
||||
source: salesforce.Opportunity
|
||||
target: Order
|
||||
|
||||
field_mappings:
|
||||
- source: Id
|
||||
target: external_id
|
||||
transform: "SF-{value}"
|
||||
|
||||
- source: Name
|
||||
target: order_name
|
||||
transform: null
|
||||
|
||||
- source: Amount
|
||||
target: total
|
||||
transform: "float(value) if value else 0"
|
||||
|
||||
- source: CloseDate
|
||||
target: order_date
|
||||
transform: "parse_date(value, '%Y-%m-%d')"
|
||||
|
||||
- source: StageName
|
||||
target: status
|
||||
transform: |
|
||||
{
|
||||
'Closed Won': 'completed',
|
||||
'Closed Lost': 'cancelled',
|
||||
'Negotiation': 'in_progress',
|
||||
'Prospecting': 'pending'
|
||||
}.get(value, 'unknown')
|
||||
|
||||
- source: AccountId
|
||||
target: customer_id
|
||||
lookup:
|
||||
source: salesforce.Account
|
||||
field: Id
|
||||
return: customer_id
|
||||
|
||||
computed_fields:
|
||||
- name: currency
|
||||
value: "USD"
|
||||
|
||||
- name: source_system
|
||||
value: "salesforce"
|
||||
|
||||
- name: extracted_at
|
||||
value: "now()"
|
||||
```
|
||||
|
||||
## 异常检测规则
|
||||
|
||||
```yaml
|
||||
# sales-validation.yaml
|
||||
rules:
|
||||
- name: amount_anomaly
|
||||
field: total
|
||||
condition: "value > mean * 3" # 超过均值 3 倍
|
||||
action: flag
|
||||
|
||||
- name: negative_amount
|
||||
field: total
|
||||
condition: "value < 0"
|
||||
action: reject
|
||||
|
||||
- name: future_date
|
||||
field: order_date
|
||||
condition: "value > today"
|
||||
action: flag
|
||||
|
||||
- name: missing_customer
|
||||
field: customer_id
|
||||
condition: "is_empty(value)"
|
||||
action: reject
|
||||
|
||||
- name: duplicate_order
|
||||
fields: [external_id, source_system]
|
||||
condition: "exists_in_target"
|
||||
action: skip
|
||||
```
|
||||
|
||||
## OpenFang Hand 集成
|
||||
|
||||
```toml
|
||||
# hands/sales-extractor.toml
|
||||
[hand]
|
||||
name = "sales-extractor"
|
||||
version = "1.0.0"
|
||||
trigger = "scheduled"
|
||||
auto_approve = true
|
||||
|
||||
[hand.config]
|
||||
sources = ["salesforce", "shopify"]
|
||||
output_format = "json"
|
||||
compression = "gzip"
|
||||
|
||||
[hand.schedule]
|
||||
cron = "0 */4 * * *" # 每 4 小时
|
||||
timezone = "UTC"
|
||||
|
||||
[hand.storage]
|
||||
data_lake = "s3://company-data-lake/sales/"
|
||||
cache_ttl_hours = 24
|
||||
|
||||
[hand.alerts]
|
||||
on_failure = ["slack:#data-alerts"]
|
||||
on_anomaly = ["email:data-team@company.com"]
|
||||
```
|
||||
|
||||
## 协作触发
|
||||
|
||||
当以下情况时调用其他 Agent:
|
||||
- **Data Consolidation Agent**: 需要整合多数据源
|
||||
- **Report Distribution Agent**: 需要生成销售报告
|
||||
- **Analytics Reporter**: 需要销售数据分析
|
||||
- **Finance Tracker**: 需要收入确认数据
|
||||
|
||||
## 成功指标
|
||||
|
||||
- 数据提取准确率 > 99.9%
|
||||
- 增量同步延迟 < 15 分钟
|
||||
- 数据完整性 > 99.5%
|
||||
- 异常检测覆盖率 100%
|
||||
- API 限流合规率 100%
|
||||
|
||||
## 关键规则
|
||||
|
||||
1. 必须使用增量提取减少 API 调用
|
||||
2. 敏感字段必须脱敏后存储
|
||||
3. API 限流必须严格遵守
|
||||
4. 提取失败必须有重试机制
|
||||
5. 数据变更必须有审计追踪
|
||||
6. 映射规则变更需要版本控制
|
||||
|
||||
## 安全检查清单
|
||||
|
||||
- [ ] API 凭证使用密钥管理
|
||||
- [ ] 敏感数据传输加密
|
||||
- [ ] 访问权限最小化原则
|
||||
- [ ] 审计日志完整记录
|
||||
- [ ] 数据保留策略合规
|
||||
- [ ] 个人信息脱敏处理
|
||||
Reference in New Issue
Block a user