An expert AI masonry and tiling assistant providing specialized knowledge routing, precise cost estimation via dedicated scripts, and comprehensive reference material lookup.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tile-mason
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install tile-mason using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Tile Mason Knowledge Q&A?
The tile-mason skill is a professional-grade assistant designed to address domain-specific inquiries around interior tiling, waterproofing, substrate leveling, material selection, and construction quality standards. Operating within Openclaw Skills, it acts as an intelligent router that adapts its communication style based on the user persona, ensuring that home renovation owners receive clean, actionable advice while professional tradesmen get exact technical parameters.
By unifying knowledge documents with a robust automation layer, this tool eliminates guesswork during the masonry phase of residential or commercial decoration projects. It empowers developers and automation workflows to deliver contextual responses covering troubleshooting, workflow sequencing, and cost projections with localized precision.
Tile Mason Knowledge Q&A Use Cases
- Persona-Based Guidance Routing: Automatically branching response parameters depending on whether the prompt originates from a property owner seeking acceptance criteria or a contractor requiring detailed installation rules.
- Automated Cost Estimation: Executing automated tile budget computations when dimension variables match specified criteria.
- Masonry Diagnostics and Remediations: Directing quality control audits for common issues such as hollow tiles, efflorescence, waterproofing failures, and poor drainage gradients.
- Technical Material Matching: Providing programmatic technical comparisons between thin-set tile adhesives, traditional cement mortar mixes, and joint grouting compounds like epoxy sand.
How Tile Mason Knowledge Q&A Works
- Intent Analysis and Persona Triage: The system parses input parameters to match key domain triggers (e.g., waterproofing, tile layout, hollow checking) and segments the user profile into either owner or worker pathways.
- Knowledge Retrieval: Based on the diagnosed sub-domain, reference markdown records containing rigorous construction specs are fetched to validate technical limits.
- Computation Hook Triggering: When financial variables or spatial layouts are mentioned, the system intercepts the pipeline to invoke Python execution layers.
- Structured Compilation: Responses are transformed into structured outputs or formatted plain-text guidelines dependent on execution flags.
Tile Mason Knowledge Q&A Setup
Ensure the core environment is configured with the underlying Openclaw Skills runtime infrastructure. Clone the package resources repository to your standard worker workspace:
# Verify your dependencies and script execution paths
chmod +x scripts/calc_tile.py
# Run a test calculation to confirm setup stability
python3 scripts/calc_tile.py --space bathroom --length 3 --width 2.5 --tile-len 300 --tile-wid 600 --tile-price 12 --city-tier 1
Tile Mason Knowledge Q&A Data Schema & Taxonomy
The skill manages its underlying structural workflows through static documentation matrices and execution arguments. Data maps follow this schema:
Static Knowledge Components
| Data File Path | Purpose | Key Metadata Attributes |
|---|---|---|
references/验收标准.md |
Quality Standards | Hollow tile thresholds, flat tolerance (2mm/2m), wet zone slope configurations |
references/材料对比.md |
Material Analytics | Cement mortar vs adhesive grades, joint seal polymers |
references/施工工序.md |
Execution Lifecycle | Chronological task chains, waterproofing layers, curing schedules |
references/常见问题与避坑.md |
Exception Resolution | Owner checklists, root-cause diagnostics for tiling faults |
references/成本估算参考.md |
Parametric Financials | City index baselines, scrap rate equations, manual labor quotes |
Execution Input Parameter Schema
--space(Required): String matchingbathroom,kitchen,livingroom, orbalcony.--length(Required): Float value designating workspace boundary length in meters.--width(Required): Float value designating workspace boundary width in meters.--tile-len(Required): Integer representing tile length metric in millimeters.--tile-wid(Required): Integer representing tile width metric in millimeters.--tile-price(Optional): Unit price float per tile item.--wall-height(Optional): Floor-to-ceiling vertical tiling reach parameter defaults to 2.4m.--city-tier(Optional): Tier evaluation parameter values1,2, or3to weigh labor offsets.--identity(Optional): Adjusts output terminology pathing optionsownerorworker.--json(Optional): Flag formatting downstream payload into a machine-readable string block.
Tile Mason Knowledge Q&A Advanced Features
- Automated Script Integration: Integrates directly with native system utilities (
calc_tile.py) to execute programmatic material and overhead accounting loops. - Dual-Mode Response Strategy: Exposes structural JSON outputs under the
--jsonworker profile for smooth agent-to-agent interface passing, while sustaining a markdown formatting layout for front-facing consumer applications. - Dynamic Diagnostics Routine: Utilizes a strict sequential inquiry checklist that progressively establishes symptoms, positional attributes, and age variables to pinpoint construction failures.
SKILL.md
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