LLM Mart Basic

Use this skill when you need AI-assisted testing workflows such as test data generation, root-cause analysis, and prioritization; triggers include AI-assisted testing and AI for QA.

Use this skill when you need to test an AI-enabled product feature for behavior, safety, and user-impact boundaries; triggers include AI feature testing.

Use this skill when reviewing AI-generated unit, functional, API, or end-to-end tests for false confidence, weak assertions, missing risks, or unsafe test behavior; triggers include AI-generated test review and functional test review.

Use this skill when you need evidence-bounded safety policy, abuse categories, refusal/redirect behavior, privacy, escalation, and Human risk decisions; triggers include AI 安全 and AI safety.

Use this skill when you need to verify API contract compatibility, consumer expectations, and schema change risk; triggers include API contract testing.

Use this skill when an API, OpenAPI, or consumer contract needs a quality review before implementation or versioning; triggers include API design review, contract readiness review, and consumer compatibility audit.

Use this skill when you need to review API error shape, status, code, and disclosure behavior against sourced contracts; triggers include API 错误契约测试 and API error contract testing.

Use this skill when you need to assess API retry and duplicate-request behavior against sourced side-effect evidence; triggers include API 幂等性测试 and API idempotency testing.

Use this skill when you need to design evidence-bounded API failure and rejection scenarios; triggers include API 负向测试 and API negative testing.

Use this skill when you need to design API pagination scenarios from ordered data and cursor or offset evidence; triggers include API 分页测试 and API pagination testing.

Use this skill when you need to design evidence-bounded API quota, burst, and recovery scenarios; triggers include API 限流测试 and API rate limit testing.

Use this skill when you need to compare API schemas with sourced request and response evidence; triggers include API Schema 校验 and API schema validation.

Use this skill when you need evidence-bounded api-security-testing analysis and validation preparation; triggers include API 安全测试 and api-security-testing.

Use this skill when you need to parse multi-format API definitions and generate Bruno collections for executable regression; triggers include Bruno collections and Bruno API testing.

Use this skill when you need to design Postman collections, environments, scripts, and Newman-ready API regression plans; triggers include Postman API testing, API testing, and api-test-postman.

Use this skill when you need to parse multi-format API definitions and generate Pytest API automation; triggers include Pytest API tests and API automation with Pytest.

Use this skill when you need to parse multi-format API definitions and generate Rest Assured Java test classes; triggers include Rest Assured, RestAssured, and Java API automation.

Use this skill when you need to parse multi-format API definitions and generate executable Supertest scripts; triggers include Supertest, Node.js API testing, and Supertest automation.

Use this skill when you need to assess API version compatibility from old-client, new-server, and deprecation evidence; triggers include API 版本兼容性测试 and API version compatibility testing.

Use this skill when you need evidence-bounded authentication-testing analysis and validation preparation; triggers include 身份认证测试 and authentication-testing.

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

A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从…

Convert Files / Folders / GitHub Repos Into AI / LLM-ready Files

Open-source, local-first conversational AI video editor with a professional multi-track timeline, Agent Skills, MCP integration, and Remotion rendering.

Maintainer-governed agent for evidence-backed open-source contribution proposals

A Claude Code skill by Hao (駱君昊) that learns your Facebook voice and auto-posts to FB / IG / Threads / X with a 14-day content calendar. Mega-viral validated: 8…

Local-first AI agent workspace for coding, writing, design, research, and automation — one runtime for desktop GUI and TUI.

Open-source AI Agent platform for teams. Your agents don't just chat — they read files, run code, call APIs, and deliver results.

Give your AI agent eyes for PDFs — structured text, tables, OCR, visual evidence, and page-level citations via MCP. Native Rust, local-first.

Real-world AI penetration testing engineer for authorized assessments — built-in cloud module covering AWS/Azure/GCP + Aliyun/Tencent/Huawei clouds. Built on Cl…

OpenGUI is an Android GUI agent framework for phone-use AI that can see, plan, and operate real mobile apps through the GUI.

Tinybot is a lightweight personal AI Agent that is constantly evolving

Goink 桌面 AI 小说创作助手，对话式写作 + 自动状态追踪 + 本地语义搜索。跨平台开箱即用。AI Agent Novel Generator.

Pluggable DeepSeek-colored TUI for DeepSeek Harness

Entity-level git merge driver. Resolves false conflicts git invents when independent agents edit the same file. ~95% reduction vs. line-based merge.

Percho: Minimalist desktop GUI for the Pi coding agent — the same engine as the Pi CLI, in a clean visual interface. Multi-session chat, visual tool approvals,…

Run Claude Code, Codex & Gemini in parallel on Windows & macOS — git worktree fan-out with atomic hunk adoption, approval gates, reboot-surviving sessions

A hierarchical memory framework for personalized presentation agents. Try it at memslides.com.

Real-time multimodal desktop agent evolving toward a persistent AI OS interface (0.1 α).

clawdcursor compiles whatever's on screen into one UI map — accessibility tree and OCR fused into stable, addressable elements, with a screenshot only when need…

Repeatable agentic engineering. The workflow layer that turns AI coding agents into a disciplined factory: durable specs, fresh-context workers, adversarial cro…