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Browse reusable Agent Skills, each with a clear purpose and practical guidance.
x-cmd
**IMPORTANT**: Before using any `x <mod>` command, you MUST load x-cmd first: `. ~/.x-cmd.root/X` Then you can: - Explore with `x nihao --llmstxt` - Discover skills via `x skill` x-cmd provides 600+ portable software and development tools (jq, nodejs, python, etc.). Use `x <env|pixi> use <pkg>` to install and use any package instantly. After loading x-cmd, packages in x-cmd/pixi's local bin will be automatically available in PATH. Browse x-cmd website for more usage and skills: https://www.x-cmd.com/llms.txt
agentscope-java
Expert Java developer skill for AgentScope Java framework - a reactive, message-driven multi-agent system built on Project Reactor. Use when working with reactive programming, LLM integration, agent orchestration, multi-agent systems, or when the user mentions AgentScope, ReActAgent, Mono/Flux, Project Reactor, or Java agent development. Specializes in non-blocking code, tool integration, hooks, pipelines, and production-ready agent applications.
apply-patch
Apply multi-file or tricky edits atomically with git apply instead of many fragile edit_file calls. Use when changing several files at once or when edit_file fails to match.
chart-rendering
Visualise the result of an analysis as a chart (line, bar, area, scatter, etc.). Use when the user asks to "plot...", "chart...", "show me the trend of...", "visualise...", or when a numerical result has more than ~10 rows and would be easier to read as a picture. Produces an image file plus the script that generated it.
code-search
Search a codebase efficiently with ripgrep regular expressions, file globs, and git history search. Use to locate symbols, usages, and definitions instead of reading whole files.
git-checkpoint
Use git as a safety net - create a checkpoint commit before risky or large changes and roll back cleanly if a change makes things worse. Use before multi-file refactors.
sql-analysis
Answer a quantitative business question by writing a SQL query against the data warehouse, validating it, and presenting the result. Use when the user asks "how many...", "what's the trend of...", "compare X vs Y over...", "what's our top N...", or anything that resolves to a query against tabular data. Produces a small result table plus the underlying query.