LLM Mart Basic

State-of-the-art secrets management for building and auditing software. Use whenever a task involves creating, storing, injecting, rotating, or scanning for credentials — or reviewing code/infrastructure for secret leaks and misuse. BUILD mode: implementing secrets handling; AUDI

State-of-the-art security & compliance engineering (2026) for the cybersecurity control frameworks and product-security regulations that drive architecture, code, and CI gates — not the organizational policy binder. Use when work must satisfy or be audited against NIST CSF 2.0, S

State-of-the-art shell scripting (bash-focused, defensive) for writing and auditing shell scripts, CI scripts, init/deploy scripts, container entrypoints, and Makefile recipes — and, just as much, for the ad-hoc commands you run yourself: a grep/find/rg sweep whose result you are

State-of-the-art software testing strategy and practice (2026) for designing test strategy, writing unit/integration/e2e tests, or auditing test suites. Covers suite shape (pyramid/trophy/honeycomb), test design quality (behavior-first, AAA, determinism, smells), test doubles (mo

State-of-the-art threat modeling for both designing new systems and auditing existing ones. Use when designing a feature, service, integration, or architecture that touches untrusted input, new trust boundaries, sensitive data, or third-party dependencies (BUILD mode), and when r

State-of-the-art UX writing and product-copy guidance (2026) covering voice and tone systems, plain language (ISO 24495-1), microcopy (buttons, labels, empty states, onboarding, notifications), error and feedback message craft, and the accessibility and localization of interface

State-of-the-art engineering rules (2026) for the JavaScript SSR meta-frameworks: React 19 + Next.js (App Router, React Server Components, Server Actions) and Vue 3 + Nuxt 4 (Nitro server routes, composables) — plus the cross-cutting concerns of server rendering: hydration correc

Give this repo's CLAUDE.md / AGENTS.md a checkup — size vitals vs official guidance, dead references, dead commands, stale claims — then backtest every rule against the repo's own Claude Code session history to see which rules were actually followed, ignored, or never used, and p

Example skill loaded from resources_discover

Creates implementation plans from context and requirements

Code review specialist for quality and security analysis

Fast codebase recon that returns compressed context for handoff to other agents

General-purpose subagent with full capabilities, isolated context

Git-backed control plane for AI-agent skills, tools, context, permissions, and identity. Self-hosted and MCP-native.

在 WorkBuddy 中下载并配置 dsh-plugin-garmin-connect npm 包，通过 MCP 工具分析 Garmin 活动、睡眠、步数、心率、体重、训练库、跑步趋势和有限的恢复信息，也可按用户要求创建 Garmin 训练或下载活动 FIT 文件。适用于 Garmin 配置、回顾、比较和明确授权的写操作；不用于医疗诊断。

GitHub Actions, required checks, TestMu, OS matrix, and merge gates for Skill Doctor. Use when editing workflows, adding CI jobs, deciding what runs on every commit, or wiring crates/npm publish.

Skill Doctor CLI UX, flags, exit codes, text/JSON/SARIF reports. Use when changing clap, printers, GitHub Action inputs, or CI gate flags.

SD-11 scanner-mediated injection — neutralize untrusted skill bytes before any model; additive-only scoring. Use when touching L2, MCP, prompts, envelopes, or scoring merge.

Skill Doctor product and architecture context. Use at the start of a session, when deciding where code lives, when the user asks how the scanner works, or before any non-trivial change.

Pre-publish and publish path for crates.io, npm installer, GitHub Releases, SBOM. Use when cutting versions, editing release.yml, or adding publish steps. Never publish from a feature branch.

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.

Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.

Write the repository handoff file for the next session, and record any durable learning.

Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.

Turn a topic or issue into a plan the reviewer approves in the native plan pane.

Answer a research question with parallel read-only gatherers and one synthesized digest.

Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.

Audit infra security: secrets, deps, CI/CD, webhooks, AI/skill files

Audit Solana program code for exploitable bugs and write a findings report

Compare per-instruction CU with the stored baseline to catch regressions

Build the web client (Next.js, Vite, React) and check env, types and bundle

Build Solana programs (Anchor, Pinocchio, native), incl. verifiable builds

Build the Unity project in batchmode for WebGL, desktop, Android or PSG1

Turn a solana-ai-kit fork into a project: set up CLAUDE.md, remove kit files

Un-ignore and commit the kit config dir, instruction file, .mcp.json and .gitmodules

Replay a user's failing transaction on forked state and map the error to source

Deploy a program to devnet, or to mainnet after the user's explicit go-ahead

Review the branch diff for Solana security issues, CU waste and AI slop

Read-only check of toolchain and kit config, with one fix-it command per failure

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

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

Conduit — native SwiftUI iOS client for Hermes Agent

一个现代化的可视化规则引擎平台，用于编排复杂的 AI 工作流。在无限画布上设计、测试和部署 AI 流程——无需编写代码。结合 flowgram.ai 的能力与 Java 服务端，提供生产级工作流管理。在此之上提供AI Agent / Copilot的助手编排能力。

Job application tracker and AI-powered job search assistant. Helps job seekers manage their search journey with AI resume review, job matching, task logging, an…

📝 Markdown and HTML renderer for Svelte 5 — built for streaming AI agent output from Claude Code, ChatGPT, and agentic workflows. XSS-safe defaults, token cach…

ServiceNow MCP server: 500+ tools and 26 AI capabilities for any AI (Claude, ChatGPT, Gemini, Cursor, Copilot). Multi-transport (stdio, SSE, HTTP), A2A, dynamic…

Free crypto news API - real-time aggregator for Bitcoin, Ethereum, DeFi, Solana & altcoins. No API key required. RSS/Atom feeds, JSON REST API, historical archi…

Build production-ready AI agents in both Python and Typescript.

From agent user to agent builder: build a Claude Code-style coding agent from scratch in Python: 8 articles, 4 videos, one codebase

🪁 A lightweight, modern Kubernetes dashboard that unifies multi-cluster and resource management, enterprise-grade user governance (OAuth, RBAC, and audit logs)…

Stateful runtime management for LLM agents—inject, manipulate, and retrieve Python objects across turns.

AgentCall lets AI Agents join meetings with voice, video & screen-share to build together. Supports Google Meet, Teams, Zoom (Beta)

Kition brings Markdown, DataTable, WhiteBoard, a tool-using AI agent, browser research, and visual workflows into one desktop workspace.

IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.

A powerful Model Context Protocol (MCP) server providing comprehensive Google Maps API integration with LLM processing capabilities.

Turn your Claude Pro/Max subscription into an OpenAI-compatible API for your IDEs and devices — LAN auth, per-key quotas, response cache, disciplined cli.js ali…

Paw Work - selection-first web agent for Chrome: select on the live page, describe the outcome, take away an editable office file. BYOK, sandboxed, no server.

基于 AI Agent + MCP 工具链 + 渗透 Skill 编排， 配合大语言模型， 自然语言输入 → 自动完成「信息收集 → 漏洞发现 → 漏洞利用 → 报告生成」全流程。

Lexora — Personal AI workspace built around Desktop / 以 Desktop 为核心的个人 AI 工作台

First AI Journey for DevOps - with comprehensive learning paths, practical tips, and enterprise guidelines

AI coding agent with one Python core and three front-ends — headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-…