Xpersona

Crawler Summary

my_crew answer-first brief

第一个crewai项目 数据分析 Agent (Data Analyst Agent) 基于 CrewAI 的多 Agent 协作数据分析系统。4 个专业 Agent 分工协作，从用户自然语言问题自动生成 SQL、安全执行查询、分析数据、输出报告。 架构 Agent 管线 Agent 角色 | Agent | Role | 职责 | |-------|------|------| | **Planner** | 任务规划师 | 理解业务问题，拆解为 SQL 查询步骤。熟悉电商数据库 Schema（t_order / t_order_item / t_product / t_product_sku） | | **SQL_Executor** | SQL 安全执行专家 | 安全检查（只允许 SELECT），自动 LIMIT，对接后端 API 执行查询 | | **Analyst** | 数据分析师 | 从查询结果中提取商业洞察——趋势、异常、相关性。每个结 Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Freshness

Last checked 10/9/2026

Best For

my_crew is best for crewai, multi-agent workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB REPOS, runtime-metrics, public facts pack

CardFactsSnapshotContractTrust
Agent DossierGITHUB REPOSSafety: 66/100

my_crew

第一个crewai项目 数据分析 Agent (Data Analyst Agent) 基于 CrewAI 的多 Agent 协作数据分析系统。4 个专业 Agent 分工协作，从用户自然语言问题自动生成 SQL、安全执行查询、分析数据、输出报告。 架构 Agent 管线 Agent 角色 | Agent | Role | 职责 | |-------|------|------| | **Planner** | 任务规划师 | 理解业务问题，拆解为 SQL 查询步骤。熟悉电商数据库 Schema（t_order / t_order_item / t_product / t_product_sku） | | **SQL_Executor** | SQL 安全执行专家 | 安全检查（只允许 SELECT），自动 LIMIT，对接后端 API 执行查询 | | **Analyst** | 数据分析师 | 从查询结果中提取商业洞察——趋势、异常、相关性。每个结

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Oct 9, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Oct 9, 2026

Vendor

Bearmonkey

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.

View Source

Setup snapshot

  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Bearmonkey

profilemedium
Observed Oct 9, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Oct 9, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB REPOS

Extracted files

0

Examples

4

Snippets

0

Languages

python

Executable Examples

mermaid

flowchart TB
    User[用户自然语言问题] --> Planner
    Planner[Planner<br/>任务规划师] -->|SQL 查询计划| SQL[SQL_Executor<br/>SQL 安全执行专家]
    SQL -->|查询结果 JSON| Analyst[Analyst<br/>数据分析师]
    Analyst -->|洞察列表| Reporter[Reporter<br/>报告撰写专家]
    Reporter -->|Markdown 报告| Output[report.md]

    SQL -.->|SQL 安全检查| Guard{安全校验}
    Guard -->|SELECT ✅| API[POST /api/agent/execute]
    Guard -->|DROP/DELETE ❌| Error[拦截并返回错误]
    API --> DB[(MySQL<br/>ai-learn-backend)]

text

用户提问 → Planner → SQL_Executor → Analyst → Reporter → Markdown 报告
  ↓           ↓            ↓              ↓           ↓
自然语言    拆解任务      安全执行SQL     从数据中     生成结构化
           生成SQL计划    只读查询        提取洞察     报告

bash

# 安装依赖
crewai install

# 配置环境变量（.env 文件）
DEEPSEEK_API_KEY=your-key
DEEPSEEK_BASE_URL=https://api.deepseek.com
DEEPSEEK_MODEL=deepseek-chat

# 启动 ai-learn-backend（端口 8080）
# 需要后端提供 POST /api/agent/execute 接口

# 运行
crewai run

text

my_crew/
├── .env                          # LLM 配置
├── src/my_crew/
│   ├── main.py                   # 入口 + 测试场景
│   ├── crew.py                   # @CrewBase 组装 4 Agent + 4 Task
│   ├── config/
│   │   ├── agents.yaml           # Agent 的 role/goal/backstory
│   │   └── tasks.yaml            # Task 的 description/expected_output + context 串联
│   └── tools/
│       └── db_query.py           # 安全 SQL 执行 + 后端 API 对接
└── report.md                     # Reporter 输出文件

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB REPOS

Docs source

GITHUB REPOS

Editorial quality

ready

第一个crewai项目 数据分析 Agent (Data Analyst Agent) 基于 CrewAI 的多 Agent 协作数据分析系统。4 个专业 Agent 分工协作，从用户自然语言问题自动生成 SQL、安全执行查询、分析数据、输出报告。 架构 Agent 管线 Agent 角色 | Agent | Role | 职责 | |-------|------|------| | **Planner** | 任务规划师 | 理解业务问题，拆解为 SQL 查询步骤。熟悉电商数据库 Schema（t_order / t_order_item / t_product / t_product_sku） | | **SQL_Executor** | SQL 安全执行专家 | 安全检查（只允许 SELECT），自动 LIMIT，对接后端 API 执行查询 | | **Analyst** | 数据分析师 | 从查询结果中提取商业洞察——趋势、异常、相关性。每个结

Full README

数据分析 Agent (Data Analyst Agent)

基于 CrewAI 的多 Agent 协作数据分析系统。4 个专业 Agent 分工协作，从用户自然语言问题自动生成 SQL、安全执行查询、分析数据、输出报告。

架构

flowchart TB
    User[用户自然语言问题] --> Planner
    Planner[Planner<br/>任务规划师] -->|SQL 查询计划| SQL[SQL_Executor<br/>SQL 安全执行专家]
    SQL -->|查询结果 JSON| Analyst[Analyst<br/>数据分析师]
    Analyst -->|洞察列表| Reporter[Reporter<br/>报告撰写专家]
    Reporter -->|Markdown 报告| Output[report.md]

    SQL -.->|SQL 安全检查| Guard{安全校验}
    Guard -->|SELECT ✅| API[POST /api/agent/execute]
    Guard -->|DROP/DELETE ❌| Error[拦截并返回错误]
    API --> DB[(MySQL<br/>ai-learn-backend)]

Agent 管线

用户提问 → Planner → SQL_Executor → Analyst → Reporter → Markdown 报告
  ↓           ↓            ↓              ↓           ↓
自然语言    拆解任务      安全执行SQL     从数据中     生成结构化
           生成SQL计划    只读查询        提取洞察     报告

Agent 角色

| Agent | Role | 职责 | |-------|------|------| | Planner | 任务规划师 | 理解业务问题，拆解为 SQL 查询步骤。熟悉电商数据库 Schema（t_order / t_order_item / t_product / t_product_sku） | | SQL_Executor | SQL 安全执行专家 | 安全检查（只允许 SELECT），自动 LIMIT，对接后端 API 执行查询 | | Analyst | 数据分析师 | 从查询结果中提取商业洞察——趋势、异常、相关性。每个结论附带数据支撑 | | Reporter | 报告撰写专家 | 将分析结果转化为结构化 Markdown 报告。摘要先行 → 关键发现 → 数据支撑 → 行动建议 |

工具

| 工具 | 说明 | |------|------| | DBQueryTool | 安全 SQL 只读查询。拒绝 INSERT/UPDATE/DELETE/DROP/TRUNCATE/ALTER，自动添加 LIMIT 1000 |

安全措施

  • 仅允许 SELECT 语句
  • 拦截 7 种危险操作（DROP、DELETE、UPDATE、INSERT、TRUNCATE、ALTER、CREATE）
  • 自动添加 LIMIT 1000（Planner 未指定时）
  • 通过后端 API 执行，Agent 不直连数据库

快速开始

# 安装依赖
crewai install

# 配置环境变量（.env 文件）
DEEPSEEK_API_KEY=your-key
DEEPSEEK_BASE_URL=https://api.deepseek.com
DEEPSEEK_MODEL=deepseek-chat

# 启动 ai-learn-backend（端口 8080）
# 需要后端提供 POST /api/agent/execute 接口

# 运行
crewai run

项目结构

my_crew/
├── .env                          # LLM 配置
├── src/my_crew/
│   ├── main.py                   # 入口 + 测试场景
│   ├── crew.py                   # @CrewBase 组装 4 Agent + 4 Task
│   ├── config/
│   │   ├── agents.yaml           # Agent 的 role/goal/backstory
│   │   └── tasks.yaml            # Task 的 description/expected_output + context 串联
│   └── tools/
│       └── db_query.py           # 安全 SQL 执行 + 后端 API 对接
└── report.md                     # Reporter 输出文件

测试场景

| # | 场景 | 测试点 | |---|------|--------| | 1 | "本周哪个商品卖得最好？" | 时间筛选 + 聚合 + Top 1 | | 2 | "本月销售额统计" | 时间范围筛选 + SUM 聚合 | | 3 | "哪些商品库存低但销量高？" | 跨表 JOIN + 阈值判断 | | 4 | "买家下单但卖家未发货的订单" | 状态筛选 + 关联查询 | | 5 | "各品类销售额对比" | GROUP BY 品类 + 排序 |

技术栈

  • Agent 框架: CrewAI（@CrewBase + YAML 配置）
  • LLM: DeepSeek（OpenAI 兼容 API）
  • 工具开发: CrewAI BaseTool + Pydantic
  • 数据库: MySQL 8.0（通过 ai-learn-backend API 中间层访问）
  • 后端: Spring Boot 3.4.1（8080 端口）

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB REPOS

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

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Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_REPOS",
      "generatedAt": "2026-10-10T06:42:36.331Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "crewai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "multi-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Bearmonkey",
    "href": "https://github.com/BearMonkey/my_crew",
    "sourceUrl": "https://github.com/BearMonkey/my_crew",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-10-09T17:06:11.304Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-10-09T17:06:11.304Z",
    "isPublic": true
  },
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-bearmonkey-my-crew/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Sponsored

Ads related to my_crew and adjacent AI workflows.