LLM Mart Basic

Use this skill when you need to identify interactions that need at least pairwise coverage after factors, values, and constraints are explicit; triggers include 成对测试 and pairwise test design.

Use this skill when you need to form evidence-based performance bottleneck hypotheses and validation steps; triggers include performance bottleneck analysis.

Use this skill when you need to compare performance evidence across versions and assess regression risk; triggers include performance regression analysis.

Use this skill when you need to interpret performance results, evidence quality, and risk without inventing conclusions; triggers include performance result analysis.

Use this skill when you need Gatling performance scope, simulations, or runnable entry points; triggers include Gatling, Gatling simulations, and Gatling performance testing.

Use this skill when you need to design JMeter test plans with Thread Groups, samplers, data sets, assertions, timers, CLI runs, and HTML reports; triggers include JMeter performance testing, performance testing, and performance-test-jmeter.

Use this skill when you need to model realistic performance workload, traffic, and acceptance assumptions; triggers include performance workload modeling.

Use this skill when you need to determine test impact from a pull request or code diff; triggers include PR test impact analysis.

Use this skill when you need to analyze production-incident evidence, impact, and follow-up actions; triggers include production incident analysis.

Use this skill when you need to plan or assess evidence-based production verification after a release; triggers include production verification.

Use this skill when you need to design safe prompt-injection tests for AI systems and tool boundaries; triggers include prompt injection testing.

Use this skill when you need to test prompt behavior, regression risk, and output boundaries across versions; triggers include prompt testing and prompt-regression.

Use this skill when you need to turn invariants, generation domains, and shrinking strategies into reviewable property-test candidates; triggers include 基于属性的测试 and property-based test design.

Use this skill when you need evidence-bounded quality dashboard audiences, decision questions, panels, drill-downs, freshness, and alert boundaries; triggers include 质量仪表盘 and quality dashboard.

Use this skill when you need evidence-bounded quality-debt items, origins, impact, age, priority, ownership, and paydown tradeoffs; triggers include 质量债务 and quality debt.

Use this skill when you need evidence-bounded entry criteria, evidence requirements, owners, and exception paths for a delivery or release gate; triggers include 质量门禁 and quality gate.

Use this skill when you need evidence-bounded quality-practice maturity dimensions, rubric anchors, evidence sufficiency, and improvement gaps; triggers include 质量成熟度 and quality maturity.

Use this skill when you need evidence-bounded quality metric definitions, calculation rules, data sources, freshness, and anti-gaming boundaries; triggers include 质量指标 and quality metric.

Use this skill when you need evidence-bounded quality and delivery metrics, denominators, attribution limits, gaming risk, and the Human-use boundary; triggers include 质量生产力 and quality productivity.

Use this skill when you need to identify and prioritize quality risks from product, change, and evidence inputs; triggers include quality risk analysis.

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.

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Run a systematic, reproducible literature review on a topic and return an APA 7.0 annotated bibliography with a documented search strategy. Invokes the alterlab-deep-research pipeline in lit-review mode.

Run a full multi-perspective peer review of a manuscript, simulating an Editor-in-Chief plus three peer reviewers and a Devil's Advocate, and produce a structured editorial decision and revision roadmap. Invokes the alterlab-paper-reviewer skill.

Orchestrate the end-to-end academic research-to-publication workflow (research, write, integrity check, review, revise, re-review, finalize) with mandatory integrity gates and two-stage peer review. Invokes the alterlab-research-pipeline orchestrator.

Infrastructure-first security audit — secrets, supply chain, CI/CD, LLM/skill security, OWASP, STRIDE. Complements /audit-solana (program-level)

Security audit for Solana programs (Anchor/native)

Benchmark CU usage and compare against baseline for regression detection

Build web client application (Next.js, React, Vite)

Build Solana program (Anchor or native)

Build Unity project (WebGL, Desktop, or PSG1)

Initialize forked template — setup CLAUDE.md and remove config repo scaffolding

Version the Solana AI Kit config in git (un-ignores .claude/, CLAUDE.md, .mcp.json, .gitmodules and commits them)

Reproduce and debug a user-reported failing transaction against forked cluster state, mapping the failure back to source code

Deploy Solana program (devnet first, then mainnet)

AI-powered diff review for Solana-specific issues and code quality

Health check for the dev environment and solana-ai-kit config — read-only, with one exact fix-it command per failure

Memory consolidation — dedupe, contradiction-check, prune, and re-rank MEMORY.md + CLAUDE.md Project Learnings. Run after major refactors

Explain complex Solana/blockchain code with visual diagrams and step-by-step breakdowns

Generate TypeScript client from Solana program IDL using Codama or Anchor

Migrate from @solana/web3.js to @solana/kit

Plan feature implementation with technical specifications for Solana projects

Claude Code skills for Chinese-narration recaps from supported video files, with optional editable JianYing/CapCut draft export. | 用 Claude Code skills 为支持的视频文件…

Drive the Unity Editor from an AI agent or the terminal. The Editor serves MCP itself over HTTP, so there is no second process to run, and the isuzu-unity-cli c…

面向企业的数字员工构建与运行平台：把专业员工的经验、流程与判断标准，固化为可随时上岗、可配置、可审批、可观测的 AI 数字员工。

A local-first, Pi-powered AI agent workspace for Desktop, WebUI, and CLI

660+ muapi-hosted generative-media models plus community-submitted third-party API tools (SEO, enrichment, social, scraping) — one YAML file per entry, browsabl…

A compounding agent OS for recursive agents. Also an open source alternative to Grok Bot and Meta's Muse.

Independent desktop client for OpenCode 2. Manage projects, sessions, parallel agents, requests, and changes on Linux and macOS.

Production agent skills for Claude Code, Cursor, and any SKILL.md harness — Codex fleets, video pipeline, monorepo review bundles, multi-chain explorer.

See and manage what your coding assistants load — skills, commands, subagents, plugins and MCP servers, with real usage.

An Enterprise-Grade Full-Stack RBAC Permission Management System Built with Go + React

Create AI Agents in a No-Code Visual Builder or TypeScript SDK with full 2-way sync. For shipping AI assistants and multi-agent AI workflows.

基于 DeepSeek Harness（DSH）的稳定桌面端，集成Git、内置浏览器与记忆功能 | DeepSeek Harness desktop GUI with local workspaces, Git, browser and memory.

⚡ Control Apache Airflow with natural language via MCP. Chat with your workflows using Claude, GPT, or any LLM — no REST API calls needed. Supports Airflow 2.x…

Open-source CLI, schemas, resolver, and DSH agent tools for DSH Plugin Hub

Pi Coding Agent 中文学习蓝皮书：从安装与第一个可验收任务开始，逐步掌握 Session、Context、Skill、Extension、Subagent 与长期 Agent 工作流。

Self-hosted framework for orchestrating fleets of specialist AI agents — ensemble reasoning and a full agentic coding pipeline, model-agnostic and local-friendl…

Self-hosted, vendor-neutral control plane for your local coding agents (Claude Code & Codex). Run your agents, on any plane.

A practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and…

Vibe Coding 从入门到精通教程｜AI 结对编程工作流｜Prompt、Skill、Workflow、上下文管理、codex实战指南

Static security scanner for LLM agents — prompt injection, MCP config auditing, taint analysis. 51 rules mapped to OWASP Agentic Top 10 (2026). Works with LangC…