LLM Mart Basic

前端工程师 Skill，执行前端开发任务，自动适配项目技术栈（React/Vue/Svelte/Next.js 等），支持 Figma/Stitch 设计稿还原

用户说“我有个点子”“帮我梳理产品”或需要先聊清目标时使用。通过逐题访谈整理为可交给 cm-prd 的 PRD；已有明确需求文档时改用 cm-prd，不写代码、不拆开发任务。

用户说“第一次接管这个项目”“分析仓库并生成项目规则”时使用。分析已有代码并生成 Codex AGENTS.md 与 CM/Claude 兼容规则；仅适用于非空存量项目，不创建脚手架、不承接普通代码修改。

微信小程序开发工程师 Skill，执行小程序开发任务，自动适配项目技术栈（原生小程序/Taro/uni-app 等），支持 Figma/Stitch 设计稿还原与云开发

用户说“把需求拆成可开发规格”“变更现有功能需求”或要求整理方案、任务和验收时使用。支持新项目、存量二开与需求变更；完成后停在人审规格，不直接编码。

产品经理 Skill，负责需求分析、用户故事与验收标准编写、歧义清单生成、变更影响分析、业务验收走查；把关型角色，不做技术设计与技术测试

QA 工程师 Skill，执行功能测试、E2E 测试、可视化回归、验收标准核验，自动适配项目测试框架

用户明确要求“只整理结构，不改变行为”时使用。执行边界分流、行为判官、分批重构和独立审查；缺陷修复转交 cm-fix，新增或变化的业务行为转交 cm-prd。

用户要查看或切换 CM 自动派发偏好、单/双 AI 声明、谁写谁审，或修改用户级运行时默认时使用。只管理运行时声明，不安装工具、不测试配额、不接管正在运行的任务。

用户运行 cm-security，或要求代码安全扫描、漏洞检查、密钥泄露排查、依赖漏洞检查时使用。默认检查当前分支相对主分支及已跟踪未提交修改，结合业务地图复核；--all 检查全部已跟踪文件。只报告问题，不自动修复、安装、升级或发布。安装自检用 cm-check，功能测试与覆盖率用 cm-test。

用户直接运行 cm-test、要求分析当前分支相对主分支的业务影响，或说“测试已有功能”“根据代码生成用例”“用浏览器走查”时使用。无参数分析已提交差异、单测覆盖率与回归重点；明确说“补齐单测”时连续补测并重跑、审查。显式目标保留原模式，不擅自修产品代码。

UI 还原工程师 Skill，把已确认的设计基准像素级还原为生产代码（token 先行、原子顺序、按交付形态量化验收：Web 用 BackstopJS、App 用 Maestro+模拟器截图）；有基准才出场，不做业务逻辑

项目代码库上下文管理。通读项目生成参考文档(scan)，或加载文档辅助开发(dev)。

Darwin Skill 2.0 (达尔文.skill 2.0): autonomous skill optimizer, v2.0 integrates Microsoft Research SkillLens (arXiv 2605.23899) 9-dim rubric + SkillOpt (arXiv 2605.23904) validation-gated design + human-in-the-loop checkpoints. Evaluates SKILL.md files using a 9-dimension rubric (s

将产品讨论、问题研究、学术研究、根因假设、测试设计或对抗审查交给外部高能力模型，并由本地主执行者核验、裁决和留存证据；不修改代码或代替正式测试。

Extract a production-ready brand-lock.md from a brand's existing assets. Point it at a website URL, a brand book PDF, screenshots, or a written description and it produces the nine-section brand-lock the rest of shotkit consumes, with a confidence and source noted for every value

Turn a creative brief into a production-grade storyboard with shot specs, timing, on-screen text, and per-shot rationale. Use when the user describes a video brief, plans a video, references shots or beats, scripts a social video, or hands over a creative concept to break into sc

Render a structured storyboard (storyboard.md, shots.json, text-overlays.json, brand-lock.snapshot.md) into a single-file HTML preview that is shareable, printable, and offline. Use when the user wants to share a storyboard, export for review, hand off to an editor, or print a ha

Critique a generated image against its source storyboard shot and prompt, producing revision notes. Use when the user has generated an image and wants feedback before committing. Triggers on "does this match the brief", "review this render", "is this on-brand", "what should I cha

Generate model-specific prompts from shots.json. Outputs copy-paste-ready prompts for stills (Midjourney, Flux, Ideogram, GPT Image, Nano Banana, Seedream) and motion video (Kling, Veo, Seedance, Hailuo). Also runs a revision mode that reads a critique.json and re-emits prompts f

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.

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.

Create or update the project constitution from interactive or provided principle inputs, ensuring all dependent templates stay in sync.

Execute the implementation plan by processing and executing all tasks defined in tasks.md

Execute the implementation planning workflow using the plan template to generate design artifacts.

Create or update the feature specification from a natural language feature description.

Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.

Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design artifacts.

Cancel active execution loop and cleanup state

Start task execution loop

Smart entry point for new features with auto ID and branch management

Show current feature status and progress

Switch active feature

Cancel active execution safely and optionally remove the spec

Generate technical design from requirements

Submit feedback or report an issue for Ralph Specum plugin.

Show help for Ralph Specum plugin commands and workflow.

Start task execution loop

Index codebase components and external resources into searchable specs

Create new spec and start research phase

Run or resume an optional prototype

Update spec files methodically after execution (requirements -> design -> tasks)

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.