LLM Mart Basic

Review a PR against the Pascal architectural rules — package boundaries (core/viewer/editor/nodes), the registry-driven composition model (def.geometry / def.renderer / def.system), legacy-dispatch regressions, the slots + world-scale-UV convention for new nodes/geometry, hook hy

Operate, troubleshoot, secure, upgrade, and automate Kubernetes clusters and workloads safely across upstream Kubernetes, k3s, RKE2, MicroK8s, k0s, Talos, OpenShift/OKD, kind, Minikube, Rancher-managed clusters, EKS, AKS, and GKE. Use when a task involves kubectl, Kubernetes APIs

Build LLM applications with LangChain. Use when working with LangChain or comparing LLM application frameworks. Do not use this skill for unrelated requests; route to the nearest named specialist.

Discover product requirements from human stakeholders — map who to talk to, ask questions that surface hidden assumptions, detect gaps in real time, resolve conflicts, and translate conversations into structured SDD specs. Phase 0 upstream of Spec-Driven Development. Do not use t

Route a product through its full lifecycle — discovery, strategy, portfolio choice, roadmap, UX and requirements, experimentation, delivery handoff, adoption, success, and lifecycle review — by composing existing specialist product skills with phase-entry evidence, handoff artifa

Compare intended product outcomes against observed results to close the launch-to-learning loop: collect post-launch evidence, distinguish expected from observed from uncertain from inferred claims, update assumptions, assess feature health, and choose among continue/improve/harv

Define and run product governance — recurring decision rights, intake, portfolio cadences, evidence standards, and cross-functional operating contracts. Covers six review cadences (intake, portfolio, roadmap, experiment, launch, lifecycle) with named accountable owners, minimum e

Build and maintain outcome-based product roadmaps and portfolio views that sequence strategic bets by evidence, not dates. Covers Now/Next/Later views, strategic-bet management, capacity allocation, dependency and confidence mapping, scenario planning, continue/pause/kill/revisit

Use this skill to shape product or engineering work before committing time to it: set appetites instead of estimates, narrow raw ideas into bounded problems, sketch solutions at the right level of abstraction, de-risk rabbit holes, write pitches, bet with capped downside (circuit

Set product vision, positioning, market strategy, and portfolio direction with a CPO methodology. Route tactical prioritization, specifications, and backlog decisions to `product-methodology`; do not use this skill for delivery-level product decisions or unrelated requests.

Build cross-domain production evidence from readiness, migration, recovery, capacity/cost, and incident learning into launch or operational decisions. Do not use this skill for a single specialist's risk packet and launch gate; use `production-readiness` for that readiness review

Apply distilled coding principles from 14 classic software books to code review, refactoring, design, and implementation decisions. Do not use for language- or framework-specific tutorials, tool manuals, or tasks already governed by a project's established conventions.

Teach promise vocabulary, fundamentals, and coordination diagnosis for promise-based systems. Do not use this skill for Semantic Spacetime models or SST CLI tooling; use `semantic-spacetime` for those model and tool workflows.

Query, search, and download public datasets and civic information for the City of Raleigh. Use for live ArcGIS Hub catalog discovery, ArcGIS FeatureServer and MapServer queries, ImageServer imagery exports, official Raleigh geocoding, GoRaleigh transit feeds, guest-public develop

Operate React applications as a named tool: inspect and diagnose React/Vite projects, design component boundaries and state flow, implement accessible responsive UI, and verify behavior with the project's tests. Use when a task explicitly involves React, JSX/TSX, React hooks, Rea

Design, automate, and operate end-to-end software releases: release process models and pipelines (trunk-based development, CD stages, release trains), progressive delivery and feature flags, versioning and artifact management (SemVer, conventional commits, changelogs, SBOM/proven

Administer and troubleshoot remote Linux, FreeBSD, NetBSD, OpenBSD, and macOS systems safely, one host or a fleet at a time. Use when a task requires SSH, Ansible, Paramiko, POSIX diagnostics, service management, software updates, system configuration, firewall changes, or eviden

Chain web research, atomic extraction, and durable note capture when the same research-to-notes sequence must repeat. Do not use this skill to design or evaluate an investigation; use `research-methodology` for research questions, methods, and evidence assessment.

Plan, conduct, evaluate, and synthesize rigorous research investigations with credible evidence and a traceable method, including source-to-claim closure for media evidence. Do not use this skill for repeated source extraction and durable note orchestration; use `research-and-vau

Design, exercise, and evidence graceful degradation, disaster recovery, and restoration behavior across systems and dependencies. Covers failure-mode analysis, RTO/RPO decision records, restore testing, game days, failover drills, data integrity verification, and recovery communi

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.

Consolidate MEMORY.md and Project Learnings: dedupe, resolve conflicts, prune

Explain Solana code with a diagram and a step-by-step walkthrough

Generate a typed client from an Anchor or Shank IDL (Codama or Anchor TS)

Migrate TypeScript from @solana/web3.js 1.x to @solana/kit

Plan a Solana feature before coding: accounts, PDAs, instructions, risks, tests

First-time-user product review: scorecard and fix roadmap; --harsh for a roast

Measure compute units per instruction and flag the expensive ones

Format, lint and commit with a conventional message on a kit-named branch

Resync external skill submodules to latest upstream versions

Scaffold a Solana project (Anchor, fullstack, frontend, Pinocchio) with the kit

Set up GitHub Actions CI for Solana programs: lint, build, test, audit

Configure MCP server API keys in .env and add the optional MCP servers

Run tests, auto-fix fmt and lint, and fix failures until green or stuck

Run C# tests: Unity Test Framework in batchmode, or dotnet test

Run Rust tests for programs (LiteSVM, Mollusk, Surfpool, Trident) and backends

Run TypeScript tests for programs (Anchor TS, Kit) and dApp frontends

Update solana-ai-kit to latest version from upstream

Write docs for a Solana program, SDK or component from its code and IDL

Seventy-two slash commands for Claude Code, grouped by what you are doing.

Find missing aliases

AI assistant in Telegram that remembers everything and helps you run your life. Self-hosted in one command.

知更 — 本地 AI 的上下文与记忆层。Mac 上用语音输入、情境代回并调度 Codex / Claude Code；iOS 正在成为随身记忆终端和本地 Agent 遥控器。Local-first · BYOK.

Agent skill that turns Claude Code / Codex into a motion-design studio for voiceover-driven explainer videos — word-level voiceover sync, 78 motion recipe cards…

CoCo Super Intelligence is the orchestration layer that turns Claude Code, Cursor, or Codex into an engineering department: a routed advisory board, 185 skills,…

Deploy AI agent teams at scale without compromise

大师.skill — 输入行业，自动调研 6 轨[行业大佬 / 工具地图 / 工作流 / 知识正典 / 信息源 / 术语标准] → 提炼为可运行的行业 Master OS skill；装到任意 Claude Code / OpenClaw / Codex / Hermes agent 即让其进入「这一行的资深人」模式。…

Notion MCP server for Claude, Cursor, ChatGPT & Claude Desktop. Connect AI agents to Notion via Model Context Protocol — pages, databases, blocks, comments, fil…

Hook-based token compressor for 5 AI CLI hosts (Claude Code, Copilot CLI, OpenCode, Gemini CLI, Codex CLI). Up to 95% bash compression, signature-mode for code…

Model-neutral agent desktop/runtime for private, enterprise, and OpenAI-compatible / Anthropic-compatible model API. Tested on DeepSeek, Qwen, Kimi, GLM models.…

AI agent skill for end-to-end hotel search and booking—compare live rates across leading OTAs and hotel suppliers, verify availability, book stays, and manage r…

More than just Karpathy’s LLM Wiki, 100% local with Ollama. Drop Markdown notes → AI extracts concepts → your Obsidian wiki auto-links and grows. Zero sharing.…

Claude Code Guide - Setup, Commands, workflows, agents, skills & tips-n-tricks from beginner to power user!

A magical tool that changes how you use Agents. Install once — every Agent automatically discovers and uses all your MCP tools, and saves your tokens along the…

Open-source 24/7 Cowork app for OpenClaw, Hermes, Claude Code, Codex, OpenCode and 20+ more CLI Agent | Customize your assistants | Team them up｜Star if you lik…

AgenticX is a unified, production-ready multi-agent platform — Python SDK + CLI (agx) + Studio server + Machi desktop app. Features Meta-Agent orchestration, 15…

Query, provision and operate Cloud, SaaS, API and Model Context Protocol (MCP) resources through a unified SQL-based framework for humans and AI agents.

Open-source AI job search: scan job portals, evaluate listings into a structured A-H report with a global 1-5 score, tailor your CV, track applications — runs l…

A self-healing scraper for hostile sites: broken selectors repair themselves, browser rendering kicks in when needed, and a coherent identity layer (Chrome TLS…

Lightweight AI-native workflow builder for individuals and small teams — describe your idea in natural language, get a runnable workflow on a visual canvas, pub…

Minimal AI coding agent (~1,000 lines of Python) inspired by Claude Code. Works with any LLM. Think NanoGPT for coding agents. Formerly NanoCoder.