{"id":"6051322a-c985-45aa-b0bb-c3d263cf0c0e","entityType":"agent","slug":"crewai-samruk-code-design-develop-and-deploy-multi-agent-system","name":"Design-Develop-and-Deploy-Multi-Agent-Systems-with-CrewAI","canonicalUrl":"https://www.xpersona.co/agent/crewai-samruk-code-design-develop-and-deploy-multi-agent-system","canonicalPath":"/agent/crewai-samruk-code-design-develop-and-deploy-multi-agent-system","generatedAt":"2026-10-10T06:42:05.414Z","source":"GITHUB_REPOS","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-09T18:04:02.664Z","emptyReason":null},"description":"Design Develop and Deploy Multi-Agent Systems with CrewAI Multi-Agent Automated Code Review with CrewAI A multi-agent system that reviews pull requests end to end: it analyzes code quality, checks for security vulnerabilities against live OWASP references, and produces a final decision — approve, request changes, or escalate. The project was built across three progressive assignments from $1 (DeepLearning.AI, taught by João Moura, co-founder and CEO of CrewAI). Each assignm","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.","installCommand":null,"sourceUrl":"https://github.com/samruk-code/Design-Develop-and-Deploy-Multi-Agent-Systems-with-CrewAI","homepage":null,"primaryLinks":[{"label":"View Source","url":"https://github.com/samruk-code/Design-Develop-and-Deploy-Multi-Agent-Systems-with-CrewAI","kind":"source"}],"safetyScore":66,"overallRank":18.8,"popularityScore":0,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"Design Develop and Deploy Multi-Agent Systems with CrewAI Multi-Agent Automated Code Review with CrewAI A multi-agent system that reviews pull requests end to e"},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-10-09T18:04:02.664Z","emptyReason":null},"protocols":[{"protocol":"OPENCLEW","label":"OpenClaw","status":"self-declared","notes":"Declared in the public agent profile."}],"capabilities":[{"label":"crewai","status":"self-declared"},{"label":"multi-agent","status":"self-declared"}],"verifiedCount":0,"selfDeclaredCount":3,"capabilityMatrix":{"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"}},"adoption":{"evidence":{"source":"no-adoption-signals","verified":false,"confidence":"low","updatedAt":"2026-10-09T18:04:02.664Z","emptyReason":"No source adoption metrics were available."},"stars":0,"forks":0,"downloads":null,"packageName":null,"latestVersion":null,"tractionLabel":null},"release":{"evidence":{"source":"agent-index","verified":false,"confidence":"medium","updatedAt":"2026-10-09T18:04:02.650Z","emptyReason":null},"lastUpdatedAt":"2026-10-09T18:04:02.664Z","lastCrawledAt":"2026-10-09T18:04:02.650Z","lastIndexedAt":null,"nextCrawlAt":"2026-10-16T18:04:02.650Z","lastVerifiedAt":null,"highlights":[]},"execution":{"evidence":{"source":"GITHUB REPOS","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":null,"setupComplexity":"low","setupSteps":["Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.","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."],"contract":{"contractStatus":"missing","authModes":[],"requires":[],"forbidden":[],"supportsMcp":false,"supportsA2a":false,"supportsStreaming":false,"inputSchemaRef":null,"outputSchemaRef":null,"dataRegion":null,"contractUpdatedAt":null,"sourceUpdatedAt":null,"freshnessSeconds":null},"invocationGuide":{"preferredApi":{"snapshotUrl":"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":["OPENCLEW"]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"GITHUB_REPOS","generatedAt":"2026-10-10T06:42:05.414Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crewai-samruk-code-design-develop-and-deploy-multi-agent-system/trust"}},"reliability":{"evidence":{"source":"runtime-metrics","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No trust, reliability, or runtime telemetry is available."},"trust":{"status":"unavailable","handshakeStatus":"UNKNOWN","verificationFreshnessHours":null,"reputationScore":null,"p95LatencyMs":null,"successRate30d":null,"fallbackRate":null,"attempts30d":null,"trustUpdatedAt":null,"trustConfidence":"unknown","sourceUpdatedAt":null,"freshnessSeconds":null},"decisionGuardrails":{"doNotUseIf":["Contract metadata is missing or unavailable for deterministic execution."],"safeUseWhen":[],"riskFlags":["missing_or_unavailable_contract","trust_data_unavailable","schema_references_missing"],"operationalConfidence":"low"},"executionMetrics":{"observedLatencyMsP50":null,"observedLatencyMsP95":null,"estimatedCostUsd":null,"uptime30d":null,"rateLimitRpm":null,"rateLimitBurst":null,"lastVerifiedAt":null,"verificationSource":null},"runtimeMetrics":{"successRate":null,"avgLatencyMs":null,"avgCostUsd":null,"hallucinationRate":null,"retryRate":null,"disputeRate":null,"p50Latency":null,"p95Latency":null,"lastUpdated":null}},"benchmarks":{"evidence":{"source":"no-benchmark-data","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No benchmark suites or observed failure patterns are available."},"suites":[],"failurePatterns":[]},"artifacts":{"evidence":{"source":"GITHUB REPOS","verified":false,"confidence":"high","updatedAt":"2026-10-09T18:04:02.664Z","emptyReason":null},"readme":"# Multi-Agent Automated Code Review with CrewAI\n\nA multi-agent system that reviews pull requests end to end: it analyzes code quality, checks for security vulnerabilities against live OWASP references, and produces a final decision — approve, request changes, or escalate.\n\nThe project was built across three progressive assignments from [Design, Develop, and Deploy Multi-Agent Systems with CrewAI](https://www.deeplearning.ai/courses/design-develop-and-deploy-multi-agent-systems-with-crewai/) (DeepLearning.AI, taught by João Moura, co-founder and CEO of CrewAI). Each assignment adds a layer of production concerns: agent design first, then guardrails and memory, then routing, parallelism, and observability.\n\n## Architecture\n\nThe final system (assignment A3) is a CrewAI Flow that routes each pull request by complexity. Trivial diffs are handled with a single inexpensive LLM call; substantive changes are dispatched to a full multi-agent crew.\n\n```mermaid\nflowchart TD\n    A[\"read_pr_file<br/>(@start — load PR diff into typed state)\"] --> B{\"analyze_changes<br/>(@router — LLM classifies the diff)\"}\n    B -- \"SIMPLE (typos, formatting, docs)\" --> C[\"simple_review<br/>single LLM call\"]\n    B -- \"COMPLEX (features, logic, security)\" --> D[\"full_crew_review<br/>three-agent CodeReviewCrew\"]\n    B -- \"ERROR (file missing or unreadable)\" --> G\n    C --> F[\"make_final_decision<br/>(@listen or_() — consolidates either path)\"]\n    D --> F\n    F --> G[\"return_final_answer<br/>APPROVE / REQUEST CHANGES / ESCALATE\"]\n```\n\nOn the complex path, the crew consists of three specialist agents. The first two run concurrently:\n\n```mermaid\nflowchart LR\n    PR[\"PR diff\"] --> SD & SE\n\n    subgraph parallel [\"async_execution — run in parallel\"]\n        SD[\"Senior Developer<br/>analyze_code_quality<br/>critical and minor issues\"]\n        SE[\"Security Engineer<br/>review_security<br/>vulnerabilities and risk levels<br/>SerperDevTool + ScrapeWebsiteTool (OWASP)\"]\n    end\n\n    SD -- \"structured JSON\" --> TL\n    SE -- \"structured JSON, guardrail-validated\" --> TL\n    TL[\"Tech Lead<br/>summarize_findings<br/>confidence score, fixes, recommendation\"]\n```\n\nThree design decisions drive the system: complexity-based routing avoids spending multi-agent token budgets on trivial diffs, parallel task execution roughly halves crew latency, and schema-enforced outputs mean downstream steps never parse free-form text.\n\n## Assignments\n\n### A1 — Multi-Agent Automatic Code Review\n\nFoundations: agents, tasks, tools, and orchestration.\n\n- A three-agent crew — Senior Developer, Security Engineer, and Tech Lead — each with a focused role, goal, and backstory\n- The Security Engineer uses SerperDevTool (search scoped to `owasp.org`) and ScrapeWebsiteTool, grounding security findings in current best-practice references rather than model memory alone\n- Structured JSON outputs per task (`critical_issues`, `security_vulnerabilities`, `highest_risk`, etc.)\n- Task context chaining, so the Tech Lead synthesizes both specialists' findings into a final verdict\n\n### A2 — Adding Production-Grade Functionality\n\nReliability: guardrails, hooks, memory, and configuration hygiene.\n\n- Pydantic output schemas (`output_json`) guarantee parseable, consistent agent responses\n- Two custom guardrails:\n  - `security_review_output_guardrail` validates risk levels against allowed categories and verifies that `highest_risk` matches the most severe finding\n  - `review_decision_guardrail` ensures the final decision contains an actionable keyword (approve, request changes, or escalate)\n- A before-kickoff hook (`read_file_hook`) injects the PR diff into crew inputs before any agent runs\n- Crew memory retains context across successive reviews\n- YAML-based configuration (`agents.yaml`, `tasks.yaml`) separates prompts from orchestration code\n\n### A3 — Building an Automatic Code Review Flow\n\nScale: routing, parallelism, state, persistence, and observability.\n\n- `PRCodeReviewFlow` built on CrewAI's Flow API with a typed Pydantic `ReviewState` (PR content, errors, results, token usage, final answer)\n- An LLM-powered `@router` classifies each PR as SIMPLE, COMPLEX, or ERROR and dispatches accordingly\n- Quality and security tasks run in parallel (`async_execution=True`) on the complex path\n- `or_()` conditional listeners consolidate whichever path ran; errors short-circuit safely to the final answer\n- State persistence via `@persist` and tracing for observability, with flow state exported to `flow_state.json` for token and cost analysis\n- Packaged as a standard CrewAI CLI project (`crewai run`; `crewai flow plot` generates an interactive HTML flow diagram)\n\n## Project Structure\n\n```\ncode_review_flow/                          # CrewAI CLI project\n├── pyproject.toml                         # Project metadata and dependencies\n├── uv.lock\n└── src/code_review_flow/\n    ├── main.py                            # PRCodeReviewFlow (router + listeners)\n    ├── utils.py\n    ├── tools/\n    │   └── custom_tool.py\n    └── crews/code_review_crew/\n        ├── crew.py                        # Agents, tasks, parallel execution\n        ├── config/\n        │   ├── agents.yaml                # Agent roles, goals, backstories\n        │   └── tasks.yaml                 # Task descriptions and outputs\n        └── guardrails/\n            └── guardrails.py              # Custom output validators\n```\n\n## Tech Stack\n\n| Component | Role |\n|---|---|\n| [CrewAI](https://www.crewai.com/) (Crews and Flows) | Multi-agent orchestration, routing, persistence |\n| OpenAI GPT-4o-mini | LLM powering agents, the router, and direct calls |\n| [Pydantic](https://docs.pydantic.dev/) | Typed flow state and enforced output schemas |\n| [SerperDevTool](https://docs.crewai.com/en/tools/search-research/serperdevtool), [ScrapeWebsiteTool](https://docs.crewai.com/en/tools/web-scraping/scrapewebsitetool) | Live OWASP research for the security agent |\n| Python 3.11, Jupyter, uv | Development and packaging |\n\n## Course\n\n- **Course:** [Design, Develop, and Deploy Multi-Agent Systems with CrewAI](https://www.deeplearning.ai/courses/design-develop-and-deploy-multi-agent-systems-with-crewai/)\n- **Platform:** DeepLearning.AI\n- **Instructor:** João Moura, co-founder and CEO of CrewAI\n","readmeExcerpt":"Multi-Agent Automated Code Review with CrewAI A multi-agent system that reviews pull requests end to end: it analyzes code quality, checks for security vulnerabilities against live OWASP references, and produces a final decision — approve, request changes, or escalate. The project was built across three progressive assignments from $1 (DeepLearning.AI, taught by João Moura, co-founder and CEO of CrewAI). Each assignm","codeSnippets":[],"executableExamples":[{"language":"mermaid","snippet":"flowchart TD\n    A[\"read_pr_file<br/>(@start — load PR diff into typed state)\"] --> B{\"analyze_changes<br/>(@router — LLM classifies the diff)\"}\n    B -- \"SIMPLE (typos, formatting, docs)\" --> C[\"simple_review<br/>single LLM call\"]\n    B -- \"COMPLEX (features, logic, security)\" --> D[\"full_crew_review<br/>three-agent CodeReviewCrew\"]\n    B -- \"ERROR (file missing or unreadable)\" --> G\n    C --> F[\"make_final_decision<br/>(@listen or_() — consolidates either path)\"]\n    D --> F\n    F --> G[\"return_final_answer<br/>APPROVE / REQUEST CHANGES / ESCALATE\"]"},{"language":"mermaid","snippet":"flowchart LR\n    PR[\"PR diff\"] --> SD & SE\n\n    subgraph parallel [\"async_execution — run in parallel\"]\n        SD[\"Senior Developer<br/>analyze_code_quality<br/>critical and minor issues\"]\n        SE[\"Security Engineer<br/>review_security<br/>vulnerabilities and risk levels<br/>SerperDevTool + ScrapeWebsiteTool (OWASP)\"]\n    end\n\n    SD -- \"structured JSON\" --> TL\n    SE -- \"structured JSON, guardrail-validated\" --> TL\n    TL[\"Tech Lead<br/>summarize_findings<br/>confidence score, fixes, recommendation\"]"},{"language":"text","snippet":"code_review_flow/                          # CrewAI CLI project\n├── pyproject.toml                         # Project metadata and dependencies\n├── uv.lock\n└── src/code_review_flow/\n    ├── main.py                            # PRCodeReviewFlow (router + listeners)\n    ├── utils.py\n    ├── tools/\n    │   └── custom_tool.py\n    └── crews/code_review_crew/\n        ├── crew.py                        # Agents, tasks, parallel execution\n        ├── config/\n        │   ├── agents.yaml                # Agent roles, goals, backstories\n        │   └── tasks.yaml                 # Task descriptions and outputs\n        └── guardrails/\n            └── guardrails.py              # Custom output validators"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[],"languages":["python"],"docsSourceLabel":"GITHUB REPOS","editorialOverview":"Design Develop and Deploy Multi-Agent Systems with CrewAI Multi-Agent Automated Code Review with CrewAI A multi-agent system that reviews pull requests end to end: it analyzes code quality, checks for security vulnerabilities against live OWASP references, and produces a final decision — approve, request changes, or escalate. The project was built across three progressive assignments from $1 (DeepLearning.AI, taught by João Moura, co-founder and CEO of CrewAI). Each assignm","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":450,"uniquenessScore":56,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-09T18:04:02.664Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-09T18:04:02.664Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-10T06:42:05.414Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs","url":"https://github.com/CherryHQ/cherry-studio","homepage":"https://cherry-ai.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-11T14:38:40.986Z","createdAt":"2026-02-25T03:38:19.379Z","downloads":null},{"id":"6f6582d0-5d76-4f0f-b81d-86520247950b","entityType":"agent","canonicalPath":"/agent/copilotkit-copilotkit","slug":"copilotkit-copilotkit","name":"CopilotKit","description":"The Frontend for Agents & Generative UI. React + Angular","url":"https://github.com/CopilotKit/CopilotKit","homepage":"https://docs.copilotkit.ai","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-03-25T09:50:57.846Z","createdAt":"2026-02-25T03:39:14.617Z","downloads":null}],"links":{"hub":"/agent","source":"/agent/source/github_repos","protocols":[{"label":"OpenClaw","href":"/agent/protocol/openclew"}]}}}