Lading Logic
Official@ladinglogichq
Offers specialized technical capabilities for GPU-accelerated data processing, blockchain security, and enterprise-grade digital infrastructure analysis.
Agent Skills by Lading Logic
Showing 32 vetted skills indexed across 2 GitHub repositories.
ladinglogichqdtri-overview
Summarizes the RDTII 2.1 framework, pillars, and economy-level data sources for analysts.
ladinglogichqdtri-infrastructure
Analyze digital infrastructure readiness across APAC economies under the RDTII 2.1 framework.
ladinglogichqdtri-innovation-capacity
Analyze digital skills and innovation capacity across ESCAP economies using Pillars 11 and 12 indicators.
ladinglogichqdtri-business-framework
Analyze e-commerce, competition, and digital payments regulations under the RDTII 2.1 framework.
ladinglogichqdtri-digital-trust
Evaluate digital trust readiness across data governance, digital identity, and consumer protection pillars.
ladinglogichqdtri-trade-policy
Assess digital trade policy readiness across Asia-Pacific economies using RDTII 2.1 Pillars 1, 2, and 4.
ladinglogichqsocial-media
Draft social media posts with hooks and companion images for LinkedIn and Twitter/X.
ladinglogichqarxiv-search
Search the arXiv API for relevant papers and return sorted titles and abstracts.
ladinglogichqblog-post
Create structured SEO-optimized blog posts with cover images.
ladinglogichqdata-visualization
Automate publication-quality charts from analysis results using matplotlib and seaborn.
ladinglogichqcode-review
Automate structured code reviews with pytest and ruff checks.
ladinglogichqcoding-prefs
Synchronize user coding preferences with /memory/coding-prefs.md.
ladinglogichqplanning
Creates structured implementation plans with file targets and risk assessments from vague coding tasks.
ladinglogichqlanggraph-docs
Fetch LangGraph Python documentation to build stateful agents and workflows.
ladinglogichqcudf-analytics
Perform GPU-accelerated groupby aggregations and profiling on CSV datasets with cuDF.
ladinglogichqgpu-document-processing
Process large PDFs with GPU-accelerated text extraction, table parsing, and embedding generation.
ladinglogichqskill-creator
Generate SKILL.md files and example resources for new skills.
ladinglogichqcompetitor-analysis
Identify top competitors and compare offerings in a structured matrix.
ladinglogichqschema-exploration
Identify and describe database schema elements including tables, columns, data types, and foreign keys.
ladinglogichqquery-writing
Write and execute SQL queries to retrieve data and generate reports.
ladinglogichqfrontend-design
Generate production-grade frontend interfaces with HTML, CSS, JS, and React components.
ladinglogichqweb-research
Coordinate subagents to gather, organize, and cite web sources into research reports.
ladinglogichqremember
Capture conversation insights and save them to AGENTS.md memory.
ladinglogichqcuml-machine-learning
Train and preprocess tabular data with GPU-accelerated cuML models.
Frequently Asked Questions About Lading Logic
FAQPage SchemaWhat specific technical tasks can I perform with these capabilities?▼
You can execute GPU-accelerated data profiling, perform security audits on Solana blockchain programs, generate production-grade React frontend components, and conduct comprehensive digital infrastructure readiness assessments based on the RDTII 2.1 framework.
Which professional personas benefit most from these technical resources?▼
Data engineers requiring GPU-accelerated processing, blockchain developers focused on Solana security, and policy analysts evaluating digital trade and infrastructure readiness across Asia-Pacific economies will find these resources highly relevant.
What are the primary dependencies for running these technical functions?▼
Execution requires a CUDA-enabled environment for GPU-accelerated tasks, a configured Solana environment for blockchain development, and access to standard web development stacks including React, HTML, and CSS for interface generation.