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jeecgboot
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jimureport

Scan SKILL.md frontmatter to validate and tag Skill Units with metadata.

212|64|Updated Mar 11, 2026
Search Tags:#automation#metadata#nlp#low-code#skill-unit#ai-skills#data-reporting
One-click install
npx skills add https://github.com/jeecgboot/skills --skill jimureport
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: jimureport
Source: https://github.com/jeecgboot/skills/tree/main/jimureport
Command: npx skills add https://github.com/jeecgboot/skills --skill jimureport

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, pymysql, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables rapid creation and orchestration of AI-assisted data reporting units by extracting and structuring metadata from SKILL.md frontmatter, supporting scalable discovery and activation in AI workflows.

Core Features & Use Cases

  • Modular Skill Units defined by a mandatory SKILL.md frontmatter at the root, with optional scripts/references/assets directories to drive deteministic tasks, in-context instructions, and rich documentation.
  • Automatic discovery, validation, and tagging of valid skills for JeecgBoot/JimuReport workflows, enabling generation of code, forms, charts, reports, and print assets from natural language prompts.
  • Use cases cover end-user automation for enterprise reporting, dashboards, and document generation across SQL/API/JSON data sources, with frontmatter-driven onboarding and runtime guidance.

Quick Start

Activate the metadata extraction from the repository by running the discovery workflow to enumerate Skill Units and load each unit's SKILL.md frontmatter for activation.

Frequently Asked Questions about jimureport

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract metadata from SKILL.md frontmatter for low-code report generation?▼

You can extract metadata by scanning the repository for SKILL.md frontmatter to identify and validate Skill Units, returning a structured YAML block with name, tagline, dependencies, and components for low-code report generation.

What is a Skill Unit and how does it support enterprise reporting automation?▼

A Skill Unit is a modular directory with mandatory SKILL.md frontmatter and optional scripts or references, designed to drive deterministic tasks and enable enterprise reporting automation across SQL, API, and JSON data sources.

Does this metadata extraction workflow work with pymysql and requests dependencies?▼

Yes, the metadata extraction workflow supports pymysql and requests dependencies, utilizing them to validate Skill Units and drive data reporting workflows for enterprise dashboards and document generation.

How can I validate non-compliant Skill Units in my repository?▼

To validate non-compliant Skill Units, scan the repository for SKILL.md frontmatter to automatically flag invalid units, applying toxicity checks and returning a toxic_reason field within the YAML metadata block.

What is the best way to generate charts and forms from natural language prompts?▼

Generating charts and forms from natural language prompts is best achieved by using frontmatter-driven Skill Units that orchestrate AI-assisted workflows, enabling automatic discovery and activation for code and report generation.

What are the limitations of using SKILL.md frontmatter for skill discovery?▼

A limitation of using SKILL.md frontmatter for skill discovery is that it must exist at the repository root; without this mandatory structure, the discovery workflow cannot validate or tag the Skill Unit for AI workflow activation.

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