Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Project Orchestrator
AI 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.
skill openclawclawhub Free
AI 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.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- AGENTS.md, CLAUDE.md, CONTRIBUTING.md, Cargo.toml, README.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.2.0
Provenance
- Publisher
- reversTeam
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Project Orchestrator
Coordinate multiple AI coding agents with a shared knowledge base.
Features
Multi-Project Support: Manage multiple codebases with isolated data Neo4j Knowledge Graph: Code structure, relationships, plans, decisions Meilisearch: Fast semantic search across code and decisions Tree-sitter: Precise code parsing for 12 languages Plan Management: Structured tasks with dependencies and constraints MCP Integration: 62 tools for Claude Code, OpenAI Agents, and Cursor
Documentation
Installation Guide Getting Started Tutorial API Reference MCP Tools Reference Integration Guides: Claude Code | OpenAI | Cursor
1. Start the backends
cd {baseDir} docker compose up -d neo4j meilisearch
2. Build and run the orchestrator
cargo build --release ./target/release/orchestrator serve Or with Docker: docker compose up -d
3. Sync your codebase
# Via CLI ./target/release/orch sync --path /path/to/project # Via API curl -X POST http://localhost:8080/api/sync \ -H "Content-Type: application/json" \ -d '{"path": "/path/to/project"}'
Create a project
# Create a new project curl -X POST http://localhost:8080/api/projects \ -H "Content-Type: application/json" \ -d '{ "name": "Embryon", "root_path": "/Users/triviere/projects/embryon", "description": "Neural network composition framework" }' # List all projects curl http://localhost:8080/api/projects # Sync a project curl -X POST http://localhost:8080/api/projects/embryon/sync # Search code within a project curl "http://localhost:8080/api/projects/embryon/code/search?q=tensor&limit=10"
Create a plan
orch plan create \ --title "Implement GPU Backend" \ --desc "Add Metal GPU support for neural network operations" \ --priority 10
Add tasks to the plan
orch task add \ --plan <plan-id> \ --desc "Implement MatMul Metal shader" orch task add \ --plan <plan-id> \ --desc "Add attention layer GPU support" \ --depends <task-1-id>
Get context for an agent
# JSON context orch context --plan <plan-id> --task <task-id> # Ready-to-use prompt orch context --plan <plan-id> --task <task-id> --prompt
Record decisions
orch decision add \ --task <task-id> \ --desc "Use shared memory for tile-based MatMul" \ --rationale "Better cache locality, 2x performance improvement"
Search past decisions
orch decision search "memory management GPU"
Projects (Multi-Project Support)
MethodPathDescriptionGET/api/projectsList all projectsPOST/api/projectsCreate a new projectGET/api/projects/{slug}Get project by slugDELETE/api/projects/{slug}Delete a projectPOST/api/projects/{slug}/syncSync project's codebaseGET/api/projects/{slug}/plansList project's plansGET/api/projects/{slug}/code/searchSearch code in project
Plans & Tasks
MethodPathDescriptionGET/healthHealth checkGET/api/plansList active plansPOST/api/plansCreate planGET/api/plans/{id}Get plan detailsPATCH/api/plans/{id}Update plan statusGET/api/plans/{id}/next-taskGet next available taskPOST/api/plans/{id}/tasksAdd task to planGET/api/tasks/{id}Get task detailsPATCH/api/tasks/{id}Update taskGET/api/plans/{plan}/tasks/{task}/contextGet task contextGET/api/plans/{plan}/tasks/{task}/promptGet generated promptPOST/api/tasks/{id}/decisionsAdd decisionGET/api/decisions/search?q=...Search decisions
Sync & Watch
MethodPathDescriptionPOST/api/syncSync directory to knowledge baseGET/api/watchGet file watcher statusPOST/api/watchStart watching a directoryDELETE/api/watchStop file watcherPOST/api/wakeAgent completion webhook
Code Exploration (Graph + Search)
MethodPathDescriptionGET/api/code/search?q=...Semantic code searchGET/api/code/symbols/{path}Get symbols in a fileGET/api/code/references?symbol=...Find all references to a symbolGET/api/code/dependencies/{path}Get file import/dependent graphGET/api/code/callgraph?function=...Get function call graphGET/api/code/impact?target=...Analyze change impactGET/api/code/architectureGet codebase overviewPOST/api/code/similarFind similar code snippetsGET/api/code/trait-impls?trait_name=...Find types implementing a traitGET/api/code/type-traits?type_name=...Find traits implemented by a typeGET/api/code/impl-blocks?type_name=...Get all impl blocks for a type
Auto-Sync with File Watcher
Keep the knowledge base updated automatically while coding: # Start watching a project directory curl -X POST http://localhost:8080/api/watch \ -H "Content-Type: application/json" \ -d '{"path": "/path/to/project"}' # Check watcher status curl http://localhost:8080/api/watch # Stop watching curl -X DELETE http://localhost:8080/api/watch The watcher automatically syncs .rs, .ts, .tsx, .js, .jsx, .py, .go files when modified. It ignores node_modules/, target/, .git/, __pycache__/, dist/, build/.
Code Exploration
Query the code graph instead of reading files directly: # Semantic search across code curl "http://localhost:8080/api/code/search?q=error+handling&language=rust&limit=10" # Get symbols in a file (functions, structs, etc.) curl "http://localhost:8080/api/code/symbols/src%2Flib.rs" # Find all references to a symbol curl "http://localhost:8080/api/code/references?symbol=AppState&limit=20" # Get file dependencies (imports and dependents) curl "http://localhost:8080/api/code/dependencies/src%2Fneo4j%2Fclient.rs" # Get call graph for a function curl "http://localhost:8080/api/code/callgraph?function=handle_request&depth=2&direction=both" # Analyze impact before changing a file curl "http://localhost:8080/api/code/impact?target=src/lib.rs&target_type=file" # Get architecture overview curl "http://localhost:8080/api/code/architecture" # Find similar code patterns curl -X POST http://localhost:8080/api/code/similar \ -H "Content-Type: application/json" \ -d '{"snippet": "async fn handle_error", "limit": 5}' # Find all types implementing a trait curl "http://localhost:8080/api/code/trait-impls?trait_name=Module" # Find all traits implemented by a type curl "http://localhost:8080/api/code/type-traits?type_name=Orchestrator" # Get all impl blocks for a type curl "http://localhost:8080/api/code/impl-blocks?type_name=Neo4jClient"
Getting context before starting work
# Fetch your task context curl http://localhost:8080/api/plans/$PLAN_ID/tasks/$TASK_ID/prompt
Recording decisions while working
curl -X POST http://localhost:8080/api/tasks/$TASK_ID/decisions \ -H "Content-Type: application/json" \ -d '{ "description": "Chose X over Y", "rationale": "Because..." }'
Notifying completion
curl -X POST http://localhost:8080/api/wake \ -H "Content-Type: application/json" \ -d '{ "task_id": "'$TASK_ID'", "success": true, "summary": "Implemented feature X", "files_modified": ["src/foo.rs", "src/bar.rs"] }'
Configuration
Environment variables: VariableDefaultDescriptionNEO4J_URIbolt://localhost:7687Neo4j connection URINEO4J_USERneo4jNeo4j usernameNEO4J_PASSWORDorchestrator123Neo4j passwordMEILISEARCH_URLhttp://localhost:7700Meilisearch URLMEILISEARCH_KEYorchestrator-meili-key-change-meMeilisearch API keyWORKSPACE_PATH.Default workspace pathSERVER_PORT8080Server portRUST_LOGinfoLog level
Architecture
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ ORCHESTRATOR API โ โ (localhost:8080) โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ โโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโ โผ โผ โผ โโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโ โ NEO4J โ โ MEILISEARCH โ โ TREE-SITTER โ โ (7687) โ โ (7700) โ โ (in-proc) โ โ โ โ โ โ โ โ โข Code graph โ โ โข Code search โ โ โข AST parsing โ โ โข Plans โ โ โข Decisions โ โ โข Symbols โ โ โข Decisions โ โ โข Logs โ โ โข Complexity โ โ โข Relations โ โ โ โ โ โโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโ
Development
# Run tests cargo test # Run with debug logging RUST_LOG=debug cargo run -- serve # Format code cargo fmt # Lint cargo clippy
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
5 Docs1 Files
- SKILL.md
- AGENTS.md
- CLAUDE.md
- CONTRIBUTING.md
- README.md
- Cargo.toml