Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Backboard.io
Integrate Backboard.io for assistants, threads, memories, and document RAG via a local backend on http://localhost:5100.
skill openclawclawhub Free
Integrate Backboard.io for assistants, threads, memories, and document RAG via a local backend on http://localhost:5100.
β¬ 0 downloads β
0 stars Unverified but indexed
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
- backend/pyproject.toml, backend/api/__init__.py, backend/api/models/__init__.py, backend/api/models/schemas.py, backend/api/app.py, backend/api/routes/assistants.py
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. 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. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.2
Provenance
- Publisher
- chrisk60331
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Tools
This skill connects to a local Flask backend that wraps the Backboard SDK. The backend must be running on http://localhost:5100.
backboard_create_assistant
Create a new Backboard assistant with a name and system prompt. Parameters: name (string, required): Name of the assistant system_prompt (string, required): System instructions for the assistant Example: { "name": "Support Bot", "system_prompt": "You are a helpful customer support assistant." }
backboard_list_assistants
List all available Backboard assistants. Parameters: None
backboard_get_assistant
Get details of a specific assistant. Parameters: assistant_id (string, required): ID of the assistant
backboard_delete_assistant
Delete an assistant. Parameters: assistant_id (string, required): ID of the assistant to delete
backboard_create_thread
Create a new conversation thread for an assistant. Parameters: assistant_id (string, required): ID of the assistant to create thread for
backboard_list_threads
List all conversation threads, optionally filtered by assistant. Parameters: assistant_id (string, optional): Filter threads by assistant ID
backboard_get_thread
Get a thread with its message history. Parameters: thread_id (string, required): ID of the thread
backboard_send_message
Send a message to a thread and get a response. Parameters: thread_id (string, required): ID of the thread content (string, required): Message content memory (string, optional): Memory mode - "Auto", "Readonly", or "off" (default: "Auto")
backboard_add_memory
Store a memory for an assistant that persists across conversations. Parameters: assistant_id (string, required): ID of the assistant content (string, required): Memory content to store metadata (object, optional): Additional metadata for the memory Example: { "assistant_id": "asst_123", "content": "User prefers Python programming and dark mode interfaces", "metadata": {"category": "preferences"} }
backboard_list_memories
List all memories for an assistant. Parameters: assistant_id (string, required): ID of the assistant
backboard_get_memory
Get a specific memory. Parameters: assistant_id (string, required): ID of the assistant memory_id (string, required): ID of the memory
backboard_update_memory
Update an existing memory. Parameters: assistant_id (string, required): ID of the assistant memory_id (string, required): ID of the memory content (string, required): New content for the memory
backboard_delete_memory
Delete a memory. Parameters: assistant_id (string, required): ID of the assistant memory_id (string, required): ID of the memory to delete
backboard_memory_stats
Get memory statistics for an assistant. Parameters: assistant_id (string, required): ID of the assistant
backboard_upload_document
Upload a document to an assistant or thread for RAG (Retrieval-Augmented Generation). Parameters: assistant_id (string, optional): ID of the assistant (use this OR thread_id) thread_id (string, optional): ID of the thread (use this OR assistant_id) file_path (string, required): Path to the document file Supported file types: PDF, DOCX, XLSX, PPTX, TXT, CSV, MD, PY, JS, HTML, CSS, XML, JSON
backboard_list_documents
List documents for an assistant or thread. Parameters: assistant_id (string, optional): ID of the assistant thread_id (string, optional): ID of the thread
backboard_document_status
Check the processing status of an uploaded document. Parameters: document_id (string, required): ID of the document
backboard_delete_document
Delete a document. Parameters: document_id (string, required): ID of the document to delete
Instructions
When the user asks about:
Memory Operations
"Remember that..." or "Store this..." β Use backboard_add_memory "What do you remember about..." β Use backboard_list_memories or backboard_get_memory "Forget..." or "Delete memory..." β Use backboard_delete_memory "Update my preference..." β Use backboard_update_memory
Document Operations
"Upload this document" or "Index this file" β Use backboard_upload_document "What documents do I have?" β Use backboard_list_documents "Is my document ready?" β Use backboard_document_status
Assistant Management
"Create a new assistant" β Use backboard_create_assistant "List my assistants" β Use backboard_list_assistants "Delete assistant" β Use backboard_delete_assistant
Conversation Threading
"Start a new conversation" β Use backboard_create_thread "Show conversation history" β Use backboard_get_thread "Send message to thread" β Use backboard_send_message
General Guidelines
Always confirm successful operations with the user When creating assistants, suggest meaningful names and system prompts For document uploads, verify the file type is supported before attempting When using memory, explain what information is being stored Thread IDs and assistant IDs should be stored/tracked for the user's context
Example 1: Store a User Preference
User: "Remember that I prefer dark mode and Python code examples" Action: Call backboard_add_memory with content "User prefers dark mode interfaces and Python code examples" and metadata {"category": "preferences"} Response: "I've stored your preferences. You prefer dark mode and Python code examples."
Example 2: Create an Assistant
User: "Create a code review assistant" Action: Call backboard_create_assistant with name "Code Reviewer" and system_prompt "You are an expert code reviewer. Analyze code for bugs, performance issues, and best practices. Provide constructive feedback." Response: "Created your Code Reviewer assistant (ID: asst_xxx). It's ready to review code and provide feedback."
Example 3: Upload and Query a Document
User: "Upload my project documentation and then tell me what it covers" Action 1: Call backboard_upload_document with the file Action 2: Wait for processing, check status with backboard_document_status Action 3: Use backboard_send_message with memory="Auto" to query about the document Response: "I've uploaded and indexed your documentation. Based on the content, it covers..."
Example 4: Start a Threaded Conversation
User: "Start a new conversation with my support assistant" Action: Call backboard_create_thread with the assistant_id Response: "Started a new conversation thread (ID: thread_xxx). You can now send messages to your support assistant."
Backend Setup
The skill requires a running backend server. To start: Set the BACKBOARD_API_KEY environment variable Navigate to the backend directory Run ./start.sh The backend will be available at http://localhost:5100.
API Endpoints Reference
EndpointMethodDescription/healthGETHealth check/assistantsGET, POSTList/create assistants/assistants/{id}GET, PATCH, DELETEGet/update/delete assistant/assistants/{id}/threadsGET, POSTList/create threads for assistant/assistants/{id}/memoryGET, POSTList/add memories/assistants/{id}/memory/{mid}GET, PATCH, DELETEGet/update/delete memory/assistants/{id}/memory/statsGETMemory statistics/assistants/{id}/documentsGET, POSTList/upload documents/threadsGETList all threads/threads/{id}GET, DELETEGet/delete thread/threads/{id}/messagesPOSTSend message/threads/{id}/documentsGET, POSTList/upload thread documents/documents/{id}/statusGETDocument processing status/documents/{id}DELETEDelete document
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
5 Scripts1 Files
- backend/api/__init__.py
- backend/api/app.py
- backend/api/models/__init__.py
- backend/api/models/schemas.py
- backend/api/routes/assistants.py
- backend/pyproject.toml