Agent Skills Hub

tikz-flowchart

Create professional technical diagrams and flowcharts using LaTeX TikZ with standardized Google Material and Anthropic-inspired design themes.

cn-daily-tools

An all-in-one Chinese daily utility toolkit: weather, currency exchange, news, and package tracking. Zero configuration, no API keys required.

atxp

Equip autonomous agents with a funded wallet, identity, and paid API tools for search, generative AI media creation, messaging, and remote communication.

context-driven-development

Standardizes project context by managing artifacts (product, tech-stack, workflow, tracks) in a conductor/ directory. Supports project scaffolding, artifact synchronization, and AI alignment for greenfield and brownfield projects.

sales-ai-assistant

An AI-powered sales assistant that transforms business scenarios into optimized prompts, automatically generating high-quality emails, proposals, and analysis reports without requiring prompt engineering skills.

issue-resolver

Automated GitHub issue analysis, triage, and resolution planning tool integrated with Specification Driven Development (SDD) workflows.

consultancy-practices

Apply effective software quality consultancy practices. Use when consulting on QA strategy, advising development teams, or establishing sustainable quality workflows.

doc-reader

Read and navigate external documentation efficiently using llms.txt, MCP search, and smart parsing strategies.

qa

Browser-based QA automation for web applications. Performs automated site audits, visual regression testing, user flow verification, and issue tracking with real-time browser snapshots.

swe-cli-skills

Expert CLI guides for AI agents, featuring senior engineer workflows, safety guardrails, and operational patterns for cloud, IaC, containers, databases, and dev tools.

subagent-driven-development

Execute implementation plans using isolated subagents for each task, featuring a rigorous two-stage review process for spec compliance and code quality.

pymc

Bayesian modeling and probabilistic programming with PyMC. Build hierarchical models, perform MCMC sampling (NUTS), variational inference, and conduct rigorous model comparison using LOO and WAIC.