Report Generator for Openclaw

An automated reporting engine designed to transform structured data files into professional, decision-ready executive summaries and visualizations.

plgonzalezrx8
v1.0.0
Mar 1, 2026
0
2.5k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install report-generator-pedro

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install report-generator-pedro 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 Report Generator?

The Report Generator is a specialized component of the Openclaw Skills library that bridges the gap between raw data collection and strategic decision-making. It enables AI agents to process structured formats such as CSV, Excel, and JSON to produce comprehensive, stakeholder-ready reports including KPI dashboards and trend analysis. By utilizing these Openclaw Skills, users can ensure their data storytelling is consistent, professional, and grounded in mathematical accuracy.

This skill focuses on business readability, prioritizing clear KPIs and concise narrative insights over raw data dumps. Whether you need a monthly sales summary or a deep-dive operational analysis, the generator applies a canonical structure to ensure every report includes an executive summary, detailed analysis, and actionable recommendations.

Report Generator Use Cases

  • Creating recurring monthly or weekly KPI dashboards for executive leadership.
  • Generating automated sales and performance summaries from transaction CSV or Excel data.
  • Producing ad-hoc analytical reports with professional visualizations for team presentations.
  • Converting complex JSON datasets into human-readable executive briefs.
  • Identifying and flagging data inconsistencies while providing data-driven growth recommendations.

How Report Generator Works

  1. Validates the input data source to ensure the provided CSV, XLSX, or JSON schema is compatible.
  2. Identifies the reporting goal and target audience to determine the necessary level of detail.
  3. Computes critical KPIs such as growth rates, revenue totals, and trend directions using predefined logic.
  4. Generates visual assets, specifically bar and line charts, to visualize trends and category breakdowns.
  5. Assembles the report sections including executive summary, KPI dashboard, analysis, and charts.
  6. Performs a final sanity check on numerical consistency and narrative flow before finalizing the deliverable.

Report Generator Setup

To deploy this skill within your environment, ensure you have the necessary dependencies for data processing and visualization installed. These Openclaw Skills require the local script resources to be accessible by your agent.

# Install required Python dependencies
pip install pandas matplotlib jinja2

# Ensure the report generation script is in your project path
mv scripts/generate_report.py ./agent/tools/

Report Generator Data Schema & Taxonomy

The skill organizes its output using a structured blueprint to maintain consistency across different report types.

Component Description Data Type
title The descriptive name of the report String
period The specific timeframe the data covers String
sections Ordered list including summary, KPIs, analysis, and charts List
metrics Computed values for revenue, volume, and growth Object
findings Top 3-5 key insights derived from the data Array

Report Generator Advanced Features

  • Multi-format output capabilities optimized for HTML and PDF-ready layouts.
  • Intelligent trend detection highlighting period-over-period growth or decline automatically.
  • Domain-specific KPI mapping to adapt standard metrics to unique business requirements.
  • Automated chart selection based on data distribution and visualization best practices.
  • Built-in data integrity checks that explicitly flag missing or dirty data points within the report.

SKILL.md


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