Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Productivity
Siphonclaw Skill
Hybrid document intelligence pipeline ingesting PDFs, images, and spreadsheets with OCR, visual and text search, and field fix capture for fast retrieval.
skill openclawclawhub Free
Hybrid document intelligence pipeline ingesting PDFs, images, and spreadsheets with OCR, visual and text search, and field fix capture for fast retrieval.
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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
- 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
- 1.2.0
Provenance
- Publisher
- curtisgc1
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
SiphonClaw
Domain-agnostic document intelligence pipeline. Ingest PDFs, images, and spreadsheets into a searchable knowledge base with dual-track retrieval (text + visual), OCR, confidence scoring, and field capture. Built for field service engineers, researchers, mechanics, and anyone who needs fast answers from large document collections.
What SiphonClaw Does
Ingest documents (PDF, Excel, images, screenshots) into a local vector database with text and visual embeddings Search using triple hybrid retrieval: BM25 keyword matching + semantic text vectors + visual page embeddings, fused with RRF and reranked with a cross-encoder Identify equipment, parts, or components from photos using vision models, then search the local knowledge base Capture field fixes and repair notes as first-class knowledge base entries for future retrieval Score every response with composite confidence (retrieval + faithfulness + relevance + coverage) and footnote-style source citations
MCP Tools
SiphonClaw exposes five tools via MCP for integration with agents and other MCP-compatible clients.
siphonclaw_search
Search the knowledge base using triple hybrid retrieval (text + visual + keyword). Parameters: NameTypeRequiredDescriptionquerystringyesNatural language search query or exact part number / error codetop_kintegernoNumber of results to return (default: 5, max: 20)filtersobjectnoMetadata filters (e.g., {"source_type": "service_manual", "model": "ModelA"})modestringnoSearch mode: "hybrid" (default), "text", "visual", "keyword" Returns: { "results": [ { "content": "Extracted text from the matching chunk or page", "source": "ServiceManual_ModelA.pdf", "page": 42, "section": "4.3 Transformer Replacement", "score": 0.92, "match_type": "hybrid" } ], "confidence": 0.87, "confidence_tier": "Confident - verify part number", "keywords_used": ["low voltage supply", "assembly mount", "ModelA"], "citations": ["[1] ServiceManual_ModelA, page 42", "[2] Parts Catalog PC-1102, page 15"] }
siphonclaw_ingest
Add a document or photo to the knowledge base. Supports PDF, Excel, images (JPG/PNG), and screenshots. Parameters: NameTypeRequiredDescriptionfile_pathstringyesAbsolute path to the file to ingestsource_typestringnoDocument type hint: "manual", "parts_catalog", "field_note", "photo", "other" (default: auto-detect)metadataobjectnoAdditional metadata to attach (e.g., {"model": "ModelA", "domain": "industrial"}) Returns: { "status": "ingested", "file": "ServiceManual_ModelA.pdf", "pages_processed": 127, "chunks_created": 843, "visual_pages_indexed": 127, "ocr_pages": 12, "duration_seconds": 45.2 }
siphonclaw_field_note
Save a field fix or repair note as a first-class knowledge base entry. These are indexed and retrievable in future searches, forming a learning loop. Parameters: NameTypeRequiredDescriptionnotestringyesFree-text description of the fix, procedure, or observationmodelstringnoEquipment model or identifier (e.g., "ModelA")partsarray[string]noPart numbers used in the repair (e.g., ["12345", "67890"])procedure_refstringnoReference to a manual procedure (e.g., "ServiceManual_ModelA section 4.3")tagsarray[string]noFree-form tags for categorization (e.g., ["hv_transformer", "calibration"]) Returns: { "status": "saved", "field_note_id": "fn-2026-02-09-001", "indexed": true, "model": "ModelA", "parts_cross_referenced": ["12345"], "retrievable": true }
siphonclaw_identify
Send a photo of equipment, a part, a label, or an error screen. SiphonClaw uses vision models to identify what it sees, then searches the local knowledge base for relevant documentation. Falls back to web search if local confidence is low. Parameters: NameTypeRequiredDescriptionimage_pathstringyesAbsolute path to the image file (JPG, PNG, HEIC)contextstringnoAdditional context about the image (e.g., "circuit board inside equipment housing")search_afterbooleannoAutomatically search the KB after identification (default: true) Returns: { "identification": "Industrial power supply board, Model PSU-200", "visual_features": ["green PCB", "3 large capacitors", "manufacturer logo visible", "part label partially obscured"], "ocr_text": "PSU-200 REV C SN: 4829103", "search_results": [ { "content": "PSU-200 replacement procedure...", "source": "ServiceManual_ModelA.pdf", "page": 67, "score": 0.94 } ], "confidence": 0.91, "web_search_used": false }
siphonclaw_status
Get pipeline health, ingestion statistics, model availability, and cost tracking. Parameters: NameTypeRequiredDescriptiondetailstringnoLevel of detail: "summary" (default), "full", "costs", "models" Returns: { "status": "healthy", "knowledge_base": { "total_documents": 3164, "total_chunks": 656000, "visual_pages_indexed": 31200, "last_ingestion": "2026-02-09T14:30:00Z" }, "models": { "ocr": {"model": "qwen3-vl:latest", "provider": "ollama", "available": true}, "text_embedding": {"model": "bge-m3:latest", "provider": "ollama", "available": true}, "visual_embedding": {"model": "qwen3-vl-embed:2b", "provider": "ollama", "available": true}, "generation": {"model": "MiniMax-M2.5", "provider": "openrouter", "available": true}, "reasoning": {"model": "kimi-k2.5", "provider": "openrouter", "available": true}, "fallback": {"model": "glm-4.7-flash:latest", "provider": "ollama", "available": true} }, "costs": { "today": "$0.12", "this_month": "$2.45", "daily_budget": "$5.00", "budget_remaining": "$4.88" }, "dead_letter_queue": { "pending_retry": 2, "permanently_failed": 1 } }
MCP Server
SiphonClaw runs as an MCP server that any MCP-compatible client (OpenClaw agents, Claude Desktop, etc.) can connect to. # Start the MCP server (stdio transport - default for OpenClaw) python mcp_server.py # Start with SSE transport (for HTTP-based clients) python mcp_server.py --sse --port 8000 OpenClaw agent config (~/.openclaw/openclaw.json): { "mcpServers": { "siphonclaw": { "command": "python", "args": ["mcp_server.py"], "cwd": "/path/to/siphonclaw" } } } Claude Desktop config (claude_desktop_config.json): { "mcpServers": { "siphonclaw": { "command": "python", "args": ["/path/to/siphonclaw/mcp_server.py"] } } }
Mode A: Hybrid Local + Cloud (Recommended)
Local models handle ingestion (OCR + embeddings) for free. Cloud APIs handle intelligence (generation + reasoning) for pennies per query. Monthly cost: ~$0.50-5/mo for typical use. # 1. Install SiphonClaw git clone https://github.com/curtisgc1/siphonclaw.git && cd siphonclaw pip install -r requirements.txt # 2. Install Ollama and pull local models (~10 GB total) curl -fsSL https://ollama.com/install.sh | sh ollama pull qwen3-vl:latest # 6.1 GB - OCR ollama pull bge-m3:latest # ~1.5 GB - text embeddings ollama pull qwen3-vl-embed:2b # ~2 GB - visual embeddings # 3. Get OpenRouter API key (ONE key for all intelligence models) # Visit: https://openrouter.ai -> Sign up -> Copy API key siphonclaw config set openrouter_key sk-or-v1-xxxxx # 4. (Optional) Get Brave Search API key for web search fallback # Visit: https://brave.com/search/api -> Sign up -> Free tier: 2,000 queries/mo siphonclaw config set brave_key BSA-xxxxx # 5. Point to your documents and ingest siphonclaw config set docs_path /path/to/my/docs siphonclaw ingest # 6. Search siphonclaw search "part number for compressor valve"
Mode B: Full Cloud
Everything runs via OpenRouter. Simpler setup (no Ollama needed), but ingestion of large document sets costs $50-100+ in API tokens. First month: ~$50-105. After that: ~$0.50/mo. # 1. Install SiphonClaw pip install siphonclaw # 2. Get OpenRouter API key siphonclaw config set openrouter_key sk-or-v1-xxxxx # 3. Set ingestion mode to cloud siphonclaw config set ingestion_mode cloud # 4. (Optional) Get Brave Search API key siphonclaw config set brave_key BSA-xxxxx # 5. Point to your documents and ingest siphonclaw config set docs_path /path/to/my/docs siphonclaw ingest # 6. Search siphonclaw search "part number for compressor valve"
Cost Comparison
OperationMode A (Hybrid)Mode B (Full Cloud)Ingest 3,000 PDFs$0 (local)~$50-100 (OCR + embeddings)100 searches/month~$0.50 (API generation)~$0.50 (same)Monthly total~$0.50-5/mo~$50-105 first month, $0.50/mo after
Configuration Reference
SiphonClaw reads configuration from config/models.yaml and environment variables. Environment variables (via .env or shell): VariableRequiredDescriptionOPENROUTER_API_KEYMode A/BOpenRouter API key for intelligence modelsBRAVE_SEARCH_API_KEYnoBrave Search API key for web search fallbackOLLAMA_BASE_URLnoOllama server URL (default: http://127.0.0.1:11434)SIPHONCLAW_BUDGET_DAILYnoDaily API spend cap in USD (default: 5.00)SIPHONCLAW_DOCS_PATHnoPath to document directory for ingestion Agent config example (config.json): { "skills": { "entries": { "siphonclaw": { "openrouter_key": "sk-or-v1-xxxxx", "brave_key": "BSA-xxxxx", "docs_path": "/path/to/docs", "ingestion_mode": "local", "ollama_url": "http://127.0.0.1:11434" } } } } Model configuration: See config/models.yaml for full model tier configuration with ingestion and intelligence settings.
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- README.md