project-orchestratorAI agent orchestrator with Neo4j knowledge graph, Meilisearch search, and Tree-sitter parsing. Use for coordinating multiple coding agents on complex projects with shared context and plans.
Install via ClawdBot CLI:
clawdbot install reversteam/project-orchestratorGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
POST → http://localhost:8080/api/syncAccesses system directories or attempts privilege escalation
sudo chownCalls external URL not in known-safe list
http://localhost:8080/api/syncAI Analysis
The skill orchestrates local development workflows using documented local services (Neo4j, Meilisearch) and a local API endpoint (localhost:8080). All data operations appear confined to the user's local environment with no evidence of external data transmission. The 'sudo chown' command is concerning but appears to be part of legitimate Docker/container setup rather than privilege escalation.
Generated Mar 1, 2026
Large teams can coordinate multiple AI coding agents on complex enterprise applications, using the knowledge graph to track code relationships and decisions across microservices. The multi-project support allows managing separate codebases for frontend, backend, and infrastructure with shared context, improving consistency and reducing duplication.
Research teams can use the orchestrator to manage AI model codebases, with Tree-sitter parsing for languages like Python and C++ to analyze neural network implementations. The plan management feature helps structure experiments, track tasks like hyperparameter tuning, and record decisions on architecture choices for reproducibility.
Maintainers of open-source projects can sync codebases to the knowledge graph for semantic search across contributions and decisions, facilitating onboarding of new contributors. The MCP integration with tools like Claude Code enables automated code reviews and issue triaging, while the file watcher keeps the knowledge base updated in real-time.
Educational institutions can build coding platforms where instructors use the orchestrator to create structured lesson plans with tasks and dependencies, while students interact via API to get context and submit code. The Neo4j graph helps visualize learning progress and code relationships, enhancing collaborative learning experiences.
DevOps teams can orchestrate AI agents to automate infrastructure-as-code projects, using the knowledge graph to map dependencies between services and configurations. The search functionality allows quick retrieval of past decisions on scaling or security implementations, and the sync feature integrates with CI/CD pipelines for continuous updates.
Offer the orchestrator as a cloud-hosted service with tiered pricing based on projects, agents, and API usage, targeting enterprises needing scalable AI coordination. Revenue comes from monthly subscriptions, with premium features like advanced analytics and priority support.
Sell on-premise licenses to large organizations with strict data privacy requirements, including custom integrations and dedicated support. Revenue is generated through one-time license fees and annual maintenance contracts, with upsells for training and consulting services.
Provide a free open-source version with basic features to build a community, then monetize through paid add-ons like enhanced MCP tools, premium integrations, and advanced analytics. Revenue streams include in-app purchases and marketplace commissions for third-party extensions.
💬 Integration Tip
Leverage the MCP tools for seamless integration with existing AI agents like Claude Code, and use the file watcher to automate knowledge base updates during active development cycles.
Scored Apr 19, 2026
Audited Apr 16, 2026 · audit v1.0
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