LLM Mart Basic

Delegate a coding task to the Kimi Code CLI (`kimi`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Kimi - phrasings like "have Kimi implement X", "delegate this to Kimi", "run it through Kim

Delegate a coding task to Oh My Pi (`omp`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to delegate implementation work to Oh My Pi / omp - phrasings like "have omp implement X", "delegate this to oh my pi", "run it thro

Delegate a coding task to the OpenCode CLI as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to OpenCode — phrasings like "have OpenCode do X", "delegate this to OpenCode", "run it through OpenCode

Delegate a coding task to the Pi coding agent CLI (`pi`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to delegate implementation work to Pi - phrasings like "have Pi implement X", "delegate this to pi", "run it through P

Delegate a coding task to the Qoder CLI (`qodercli`) as a background implementer, then review its diff and land it yourself. Use this whenever the user asks to have Qoder implement, fix, refactor, or run a queue of coding tasks while the orchestrator remains the reviewer. DO NOT

Delegate a coding task to the Mistral Vibe CLI (`vibe`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Vibe — phrasings like "have Vibe implement X", "delegate this to Vibe", "run it through

Delegate a coding task to the Warp Agent CLI (`oz`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Warp - phrasings like "have Warp implement X", "delegate this to the Warp CLI", "run it thro

Delegate a coding task to the Z.AI ZCode CLI as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to ZCode — phrasings like "have ZCode do X", "delegate this to ZCode", "run it through ZCode", or "use

Fetch brand SVG logos and cloud architecture icons (AWS, Azure, GCP) from theSVG. Use when the user asks for a brand logo, company icon, framework mark, service icon, or any "icon/logo for X" where X is a real brand or cloud service. Returns ready-to-use CDN URLs or raw SVG marku

Imported from ypares/rigup.nix/riglets/agent-rig-system.

Imported from ypares/rigup.nix/riglets/code-search.

Imported from ypares/rigup.nix/riglets/nix-module-system.

Imported from ypares/rigup.nix/riglets/riglet-creator.

Review AI agent skills before installation using NVIDIA SkillSpector and source-aware semantic review. Use when asked whether a skill or downloaded skill folder is safe, trustworthy, installable, over-permissioned, or malicious.

写一整本多章节教材或成体系的课程讲义（含习题）时用它：按 UbD 逆向设计调度五个阶段——教学定位 → UbD 预期结果（gate）→ 章节树（gate）→ 逐章写作 → 审核定稿；进度落盘 .progress.json，中断后可从断点续写。触发语如"写教材"、"写一本教材"、"编写课程讲义"、"系统教材"、"textbook"。只写单篇教程、只写一章（用 textbook-chapter）、只出习题（用 textbook-exercises）时不要用它。需与 textbook-outline、textbook-chapter、textbook-exer

按大纲切片与 UbD 锚点写一章教材正文时用它：固定四段式结构——概念讲解 → 示范例题 → 引导练习 → 独立习题。触发语如"写第三章"、"按大纲写这一章"。通常由 textbook 调度，也可单独运行，用来写一篇带完整例题的深度技术文章。不负责设计大纲，也不负责整本书的调度；只是问一个知识点、要一段解释而不是成篇教材内容时，也不要用它。需与 textbook 系列其余 skill 装在同一 skills 目录下。

生成带 Bloom 层级标注的成套习题时用它：示范例题（完整解题过程）、引导练习（带提示）、独立习题（附参考答案）三类，每道计算题的答案都真算核对过再输出。触发语如"出几道矩阵乘法的练习题"、"给这一章生成例题"。通常由 textbook-chapter 调用，也可单独运行。不适用于文科论述题（stem 学科档案未为其定义验证手段），也不负责组卷。需与 textbook 系列其余 skill 装在同一 skills 目录下。

动笔写教材前要先规划并创建工作目录时用它：规划单本教材项目目录或多教材工作区，可选 git 版本管理与 README 工作说明，建好后把产出交接给 textbook。触发语如"初始化教材项目"、"创建教材工作目录"、"规划教材工作区"、"建一个写教材的目录"。只搭目录骨架，不创建流水线文件（.progress.json、00-教材设计.md、术语表.md）。写正文用 textbook（不经 init 它也会自建默认目录），续写已有项目直接用 textbook。需与 textbook 系列其余 skill 装在同一 skills 目录下。

教材项目要做教学设计时用它：产出教学定位、UbD 预期结果五件套（大概念 / 持久理解 / 核心问题 / 迁移目标 / 学习目标）、章节树与例题 Bloom 梯度规划，写入 00-教材设计.md。触发语如"设计教材大纲"、"教材规划"、"课程体系设计"。通常由 textbook 调度，也可单独运行。不负责写章节正文，也不负责生成习题。需与 textbook 系列其余 skill 装在同一 skills 目录下。

Comprehensive PostGIS spatial table design reference covering geometry types, coordinate systems, spatial indexing, and performance patterns for location-based applications

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.

Прогнать контроль качества 1С по изменённым файлам и снять блокирующий гейт

Показать состояние гейта качества 1С — какие файлы ждут проверки

Прогнать контроль качества 1С по изменённым файлам и снять гейт

Triage drain over the keyed audit residue recorded in merged pull-request bodies. Enumerates candidates, resolves each one's cited line, and takes one disposition per entry, promote to a tech-debt issue, dismiss, or keep. Never fixes anything. Pass `list` to see live candidates or `why <path>:<line>` to explain one.

Deprecated - use the aegis:brainstorming skill instead

Deprecated - use the aegis:executing-plans skill instead

Deprecated - use the aegis:writing-plans skill instead

Initialize a new camp

Capture an idea, list intents, or promote an intent to a festival

Commit changes with festival traceability metadata

Create a new festival, phase, sequence, or task

List all festivals with their status and completion percentage

Get the next actionable festival task with full context

Show festival progression (in-progress tasks, roadmap, and dependency view)

Show festival progress and current status

Learn about the Festival Methodology (concepts, structure, rules, and workflows)

Validate festival structure and find issues

Turn one sentence of intent into a structured plan, sized correctly and planned through the loop

Initialize a new camp

Capture an idea, list intents, or promote an intent to a festival

Open-source MCP servers for Latin American commerce — Pix, NF-e, banking, fiscal, logistics, and messaging across Brazil, Mexico, Argentina, Colombia, Chile, an…

pi coding agent in a technicolor web trenchcoat

Open-source AI Search Intelligence Platform — track, analyze, and improve AI visibility, citations, prompts, competitors, and content opportunities across ChatG…

Open-source toolkit for the QVeris capability routing network: CLI, MCP server, Python SDK, skills, and REST API docs for agents to discover, inspect, call, and…

⚡ The Complete X/Twitter Automation Toolkit — Scrapers, MCP server for AI agents (Claude/GPT), CLI, browser scripts. No API fees. Open source. Unfollow people w…

The AI agent that interacts with you in the real world.

Offline Codex Desktop migration for Windows and macOS.

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashbo…

Your smart, reliable, and friendly personal AI assistant.

The LLM Anti-Framework

A general-purpose AIGC video engine: script to finished film in one pipeline — dramas, ads, product videos, otome games, and more. | 通用 AIGC 视频引擎 —— 从剧本到成片一条流水线…

GTM agent for technical founders. Pay-per-result. Signed receipts. Two surfaces: terminal CLI + local web dashboard.

Desktop automation MCP server — computer use for any AI agent: control screen, windows, mouse/keyboard, and Chrome via Model Context Protocol (stdio)

DeepSeek Harness (dsh) Windows desktop client - bundled Node.js + dsh CLI, one-click launch

Open-source, real-time collaborative AI canvas - notes, mini-apps, and agents on one infinite board.

MCPSafari: Native Safari MCP Server for AI Agents

197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Po…

The AI agent with a wallet — spends USDC autonomously to get real work done. Apache-2.0, TypeScript.

The fastest browser for AI agents to run browser automation, built for sharing your logged-in browser state with your AI agents, like Codex or Claude Code, with…

Ouroboros — self-creating AI agent. Born Feb 16, 2026.