LLM Mart Basic

Eliminate a stubborn configuration bug by testing 8-10 fundamentally different fixes in parallel instead of one at a time. Use when the root cause is ambiguous and asked to "fix this stubborn bug", "we've tried everything", "run approaches in parallel", "use parallel subagents",

Use when the user asks for the "system design philosophy", "design principles", "/ar:philosophy", or "/ar:ph", and before major feature work, an architecture decision, or a pull-request review. Lists the 17 universal system design principles, ordered from most fundamental to most

Use when the user asks to "make a plan", "plan this out", "/ar:plannew", or "/ar:pn", or starts multi-step work that needs tracked steps. Creates a structured plan with checkbox steps, the evidence each step must produce, and the wait process between them.

Use when the user asks to "execute the plan", "run the plan", "/ar:planprocess", or "/ar:pp". Executes an approved plan step by step with the wait process, task tracking, and verification before each completion claim.

Use when the user asks to "refine the plan", "critique the plan", "/ar:planrefine", or "/ar:pr". Critiques an existing plan against the actual code, records a change ledger, and iterates until a full pass finds no new material issue.

Use when the user asks to "update the plan", "sync the plan with the code", "/ar:planupdate", or "/ar:pu". Reconciles an existing plan with the current codebase and marks what already shipped.

Edit prose for brevity and scanability without losing facts. Use for requests to "revise", "rewrite", "edit", "polish", "clean up", "clarify", "simplify", "condense", "tighten", "shorten", "streamline", "de-fluff", remove bloat/repetition or unnecessary newlines, fix spelling/typ

Use when the user asks to "list my claude sessions", "which windows are waiting", "/ar:tabs". Discovers Claude sessions across tmux windows and reports which need attention.

Use when the user asks to "continue every session", "send this to all windows", "/ar:tabw". Acts on Claude sessions across tmux windows; destructive to in-flight work, so it states what it will do before doing it.

Drive CLI tests inside isolated tmux/byobu sessions with ai-monitor integration. Use when asked to "test this CLI", "run it in tmux", "automate a terminal session", "capture the output of an interactive command", "send keystrokes to a session", or to exercise a plugin or terminal

autorun control commands, stated as prose after $ar: status; allow/justify/find file-creation policy; ok/no/blocks/clear command guards; global variants; stop/estop; task tracking and pause; cache-miss gate; planexport settings; reload; help lists everything.

This skill should be used when the user asks to "extract text from PDF", "convert PDF to text", "parse PDF", "read PDF contents", "extract data from documents", "batch PDF extraction", "PDF to markdown", "OCR PDF", "get text from PDF files", "I have a PDF", "can you read this PDF

Expertise in maintaining, debugging, and deploying the autorun hook system across Claude Code, Codex CLI, Gemini-family CLIs, Google Antigravity, Qwen Code, ForgeCode, custom harnesses, and desktop app integrations. Use when the user asks to "fix hooks", "deploy autorun", "debug

Hugging Face Inference SDK patterns for TypeScript/Node.js — InferenceClient setup, chat completion, text generation, streaming, embeddings, image generation, audio transcription, translation, summarization, and Inference Endpoints

Replicate SDK patterns for TypeScript/Node.js -- client setup, predictions, streaming, webhooks, file handling, model versioning, deployments, and training

Together AI SDK patterns for TypeScript — client setup, chat completions, streaming, structured output, function calling, embeddings, image generation, fine-tuning, and OpenAI-compatible endpoints

LLM observability with Langfuse — OpenTelemetry-based tracing, evaluations, prompt management, datasets, and production best practices

Testing and evaluation framework for LLM prompts and applications -- promptfooconfig.yaml, assertions, model-graded evals, red teaming, CI/CD integration, custom providers, and comparative evaluation

LangChain.js patterns for building LLM applications — chat models, LCEL chains, prompt templates, structured output, agents, tools, RAG, streaming, and LangSmith tracing

LlamaIndex.TS data framework for RAG, indexing, retrieval, query engines, chat engines, and agentic workflows in TypeScript

Fourteen posts of being wrong in production, compressed to checkboxes

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

网文封面生成。分析书名题材，生成专业封面图。

网文去AI味。检测并清除文本中的AI写作痕迹，让文字回归自然。

逆向导入已有小说。将已写好的小说反向解析为标准项目目录结构。

长篇网文拆文。深度拆解爆款长篇小说的黄金三章、人设、爽点、节奏。

长篇网文扫榜。分析起点、番茄、晋江等平台排行数据，提炼市场趋势。

长篇网文写作。从大纲到正文，辅助长篇网络小说的创作。

多视角对抗式审查。使用多个 Agent 对作品进行多维度审稿。

网文写作环境部署与检查。部署 hooks、rules、agents、项目指令等基础设施；传入 check 只检查不改动。

短篇网文拆文。拆解爆款短篇的故事核、结构、情感线和反转设计。

短篇网文扫榜。分析知乎盐言、番茄短篇等平台热门数据。

短篇网文写作。辅助短篇小说创作，从构思到成稿。

网文工具箱路由入口。根据模糊意图自动分发到对应的写作、拆文或扫榜工具。

浏览器操控。通过 CDP 复用 Chrome 登录态执行浏览器自动化。

小说封面生成。根据书名、作者名和题材生成专业网文封面。

网文去 AI 味。检测并清理模板化、解释腔和过度工整表达。

逆向导入已有小说，将成稿或半成品解析为可续写项目。

长篇网文拆文，分析黄金三章、人设、爽点和长线节奏。

长篇网文扫榜，分析起点、番茄、晋江等平台趋势。

长篇网文写作，从选题、大纲到逐章正文和持续追踪。

多视角小说审查；ZCode 项目 agents 不可用时自动降级 solo。

AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.

嘉立创EDA专业版(EasyEDA Pro)自动化：给 AI harness 装上画板的「手」—— 一套 typed 原理图/PCB 动作，CLI / Agent Skill / stdio MCP 三形态融合接入。承接嘉立创「不以卖板赚钱，以培养中国工程师为己任」 | EasyEDA Pro automation:…

Claude Code session log viewer for JSONL files in ~/.claude/projects. Browse conversations, tool calls, tokens, and live tail sessions on desktop, web, and TUI.

Shared memory MCP server — persistent, searchable, cross-client Claude, Opencode

OpenAI Codex CLI session log viewer for JSONL files in ~/.codex/sessions. Browse conversations, tool calls, tokens, collaboration chains, and live sessions on d…

High-performance Google Drive CLI and Model Context Protocol (MCP) Server for LLM/AI agents. Natively execute Google Apps Script (GAS) under a secure whiteliste…

"Vibe-Trading: Your Personal Trading Agent"

Local-first chat history analyzer with AI. | 本地优先的 AI 聊天记录分析工具

Official Oxylabs MCP integration

Persistent memory for Claude Code & Codex CLI. Auto-extracted knowledge graph, multi-representation embeddings, 3D WebGL visualization. LongMemEval R@5=97.45%.…

One person, a team of agents. Multi-session CLI that collaborates across terminals; /goal keeps long tasks running; WeChat/WeCom/Feishu gateway lets you call th…

AI 基础知识 - GPU 架构、CUDA 编程、大模型基础及AI Agent 相关知识。

Self-hosted, open-source agent skill registry for enterprises. Publish & version skill packages, govern with RBAC and audit logs, deploy on-premise with Docke…

深度调研报告生成 Skill — 一条命令，十分钟出券商级深度调研报告 / Professional deep research report generation Skill · Supports 19 languages

The OKF toolkit for Claude Code — author, maintain, validate & visualize Open Knowledge Format bundles. Plugin, agent skills, and a GitHub Action.

Autonomous AI pentesting agents — real-time reconnaissance, vulnerability detection, and exploitation orchestration. Go + TypeScript.

Native macOS and iOS App for the Hermes AI agent — multi-window, multi-server (local + remote over SSH). Chat, dashboard, sessions, memory, cron, MCP, and more.

Multiplayer Claude Code and Codex. Self-hosted team workspace for Claude Code and Codex. Multi-user, browser-based, AI mates with memory.

Every past session, subagent, and workflow -- queryable by your agent, browsable by you

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