Pdf Report Generator
Automatically generate PDF reports from construction data. Create formatted project reports with charts and tables.
Why use this skill?
Generate professional construction project reports automatically. Create formatted PDFs with charts, tables, and KPIs from project data using the OpenClaw Pdf Report Generator.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/datadrivenconstruction/pdf-report-generatorWhat This Skill Does
The Pdf Report Generator is an automated documentation engine designed specifically for the construction industry. It enables the OpenClaw AI agent to aggregate complex project data—including budget metrics, safety logs, and progress status—and compile them into professional, formatted PDF reports. By utilizing a modular architecture, the tool allows users to define custom sections like tables, charts, and KPI cards, ensuring that reporting remains consistent across stakeholders while eliminating the manual labor of data entry and document styling.
Installation
To integrate this skill into your OpenClaw environment, execute the following command in your terminal:
clawhub install openclaw/skills/skills/datadrivenconstruction/pdf-report-generator
Ensure that you have the required Python dependencies, specifically pandas and a PDF generation library, installed in your environment before initializing the generator.
Use Cases
This skill is highly effective for project managers, safety officers, and financial analysts in construction. Primary use cases include:
- Weekly Progress Tracking: Automatically pull project site updates and display them against a timeline chart.
- Safety Compliance Audits: Create comprehensive safety logs that include hazard registers and incident status metrics for stakeholder compliance reviews.
- Executive Cost Reporting: Summarize high-level expenditure data into clear, formatted tables that highlight budget deviations and current spend rates.
- Quality Assurance Documentation: Aggregate inspection results into a standardized format for project sign-off protocols.
Example Prompts
- "Generate a weekly progress report for the Alpha Tower site, including a bar chart showing planned versus actual work hours and a table detailing recent safety inspections."
- "Create a monthly executive financial report. Use the current budget data to highlight any areas where we are over-budget and add a KPI card for total spend."
- "Prepare a safety compliance summary PDF. Include the last 30 days of incident logs in a table format and summarize the key safety metrics at the top of the report."
Tips & Limitations
To get the best results, ensure your input data is clean and structured as a pandas DataFrame before passing it to the generator. The skill is optimized for structured project data; ensure your data source contains valid date-time fields to allow for temporal sorting. Be aware that large datasets (e.g., thousands of rows) might require additional pagination handling in the report layout. For highly complex, custom-branded layouts, you may need to extend the ReportSection base class to add custom CSS or document styling overrides.
Metadata
Not sure this is the right skill?
Describe what you want to build — we'll match you to the best skill from 16,000+ options.
Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-datadrivenconstruction-pdf-report-generator": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-write, file-read, code-execution
Related Skills
data-lineage-tracker
Track data origin, transformations, and flow through construction systems. Essential for audit trails, compliance, and debugging data issues.
cwicr-cost-calculator
Calculate construction costs using DDC CWICR resource-based methodology. Break down costs into labor, materials, equipment with transparent pricing.
data-anomaly-detector
Detect anomalies and outliers in construction data: unusual costs, schedule variances, productivity spikes. Statistical and ML-based detection methods.
historical-cost-analyzer
Analyze historical construction costs for benchmarking, trend analysis, and estimating calibration. Compare projects, track escalation, identify patterns.
df-merger
Merge pandas DataFrames from multiple construction sources. Handle different schemas, keys, and data quality issues.