LLM Mart Basic

AI agent contacts — add, list, remove MCP contacts. Use when someone gives an agent URL, or when you need to view/remove contacts.

批量查看和切换子 agent 的模型配置，用于统一调整多 agent 的 provider/model 设置。

Multi-Agent group chat collaboration system inspired by DingTalk/Lark. Enables AI agents to chat in groups, @mention each other, assign tasks, make decisions via voting, and collaborate. Use when building multi-agent systems that need structured communication, task delegation, de

Format SPAWN REQUEST messages to launch parallel agents, generate structured agent status reports, and define communication protocols within the sprint system. Use when the user needs to coordinate multiple agents, format spawn requests, produce agent reports, or establish inter-

Find and compare Daniel's reviewed GitHub skill sources. Use for high-star skill discovery, link checks, or safe installation, update, and removal of one selected skill.

Run a two-pass, multidisciplinary code audit led by a tie-breaker lead, combining security, performance, UX, DX, and edge-case analysis into one prioritized report with concrete fixes. Use when the user asks to audit code, perform a deep review, stress-test a codebase, or produce

Use when confirming whether a dispatched agent task was actually received, activated, and progressing after sessions_send or other task handoff actions.

Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating ha

Imported from aaaaqwq/agi-super-team/skills/agent-values-alignment-detector.

Audit codebases, infrastructure, AND agentic AI systems for security issues. Covers traditional security (dependencies, secrets, OWASP web top 10, SSL/TLS, file permissions) PLUS agentic security (prompt injection scanning, identity spoofing detection, memory poisoning checks, mu

Generate images using ModelScope Z-Image-Turbo API. Use when user asks to generate, create, or make images, pictures, or illustrations.

Create AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, bra

雷达Skill（AI Radar）——零API、零Key、零服务器的中文AI资讯查询。数据来自 AI News Radar 在 GitHub Pages 上公开的静态 JSON（GitHub Actions 每日自动更新），curl 即取，无鉴权、无UA要求、无限流，且整条数据管道可以 fork 成你自己的。 当用户想知道"今天 AI 圈有什么"、"过去24小时AI新闻"、"AI日报"、"最近有什么大模型发布"、"AI产品更新"、"Agent工具有什么新东西"、"OpenAI/Anthropic/Google最近发了什么"、"AI圈热点"、"看下AI雷达

Security audit engine for OpenClaw configurations. Detects vulnerabilities, misconfigurations, secret leaks, and over-privileged agents. Use when the user asks about security, hardening, config review, or audit of their OpenClaw setup.

Imported from aaaaqwq/agi-super-team/skills/ai-trader-arena.

End-to-end AI video generation - create videos from text prompts using image generation, video synthesis, voice-over, and editing. Supports OpenAI DALL-E, Replicate models, LumaAI, Runway, and FFmpeg editing.

脚本创作 - 短视频脚本撰写与分镜设计 职责：根据爆款模板生产内容、设计黄金3秒开头方案（3种以上）、撰写分镜脚本（包含镜头语言/场景氛围/角色动作/台词/BGM）、设计槽点埋梗与情绪钩子、规划结尾引导、自动推荐Vidu视频生成配置（模型版本/生成方式/时长/比例）、确保人物形象一致性、向视频生成(Leo)传递完整的分镜信息 适用场景：(1) 短视频脚本撰写 (2) 分镜设计 (3) 内容创作 (4) 视频策划

视频生成 - AI视频生成与后期剪辑制作 职责：调用Vidu生成视频、模型选择、Prompt调优、视频拼接、质量检测

AI 视频生成全流程：通过 6 个阶段（剧本→角色/场景设计→分镜→参考图→视频生成→后期剪辑）将用户想法转化为完整视频。支持临时工作台（单独调用 LLM、VLM、文生图、图生图、视频生成）。触发词：视频生成、AI视频、AIGC、创作视频、制作视频、AI画图。

Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.

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.

Run an ad-hoc ordered chain of pm-skills with shared context (ephemeral; routes to the pm-workflow-orchestrator)

Run the Customer Discovery workflow (research -> JTBD -> opportunities -> problem)

Run the Design Sprint workflow (5-day prototype-and-test arc producing a Decider's build/iterate/pivot/stop call)

Run the Feature Kickoff workflow (problem -> hypothesis -> PRD -> stories)

Run the Foundation Sprint workflow (2-day strategic-alignment arc producing a Founding Hypothesis)

Run the end-to-end Foundation Sprint + Design Sprint workflow with narrative handoff

Run the Post-Launch Learning workflow (instrumentation -> dashboard -> results -> retro -> lessons)

Run the Product Strategy workflow (competitive analysis -> stakeholders -> opportunities -> solution -> ADR)

Run the Sprint Planning workflow (refinement -> stories -> edge cases)

Run the Stakeholder Alignment workflow (stakeholders -> problem -> solution -> launch)

Run the Technical Discovery workflow (spike -> ADR -> design rationale)

Placeholder command file for the WS-T9 dual-shell parity smoke. No count phrases.

Fast non-interactive briefing before any meeting — auto-detects your next calendar event, pulls relationship history, surfaces open commitments, and produces a one-page brief in under 30 seconds. Use this whenever the user says "brief me", "give me a quick brief", "what's coming up", "background on my next call", "who am I meeting next", "brief me on Sarah", "I have a call in 10 min", "quick rundown", or right before walking into a meeting. Different from /minutes-prep — brief is the fast hook-fireable version that doesn't ask questions and doesn't set goals. Use brief when speed matters; use prep when the user wants to think hard about goals first.

Manage old recordings — find large files, archive old meetings, delete processed originals. Use when the user says "clean up recordings", "how much space are meetings using", "delete old recordings", "archive meetings", "manage meeting storage", or asks about disk space from minutes.

Start and control Minutes Coach, the separate real-time copilot HUD, with an explicit meeting goal. Use only for explicit Coach or HUD lifecycle requests such as "start Minutes Coach", "open the Coach HUD", "pause Minutes Coach", "resume Minutes Coach", "Minutes Coach status", or "stop Minutes Coach". Do not use for requests that explicitly ask the current terminal agent to watch or strategize; those belong to minutes-live-sidekick. An ambiguous request such as "coach me live" requires one short surface clarification and must not automatically start Coach.

Post-meeting debrief — analyzes what happened, compares outcomes to your prep intentions, tracks decision evolution. Use when the user says "debrief", "what just happened in that meeting", "what did we decide", "debrief that call", "post-meeting", "what changed", or right after stopping a recording.

Policy-safe relationship rankings, commitments, aliases, person profiles, and topic research. Always use Minutes' bounded native CLI surfaces; never build or read a durable graph cache.

Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.

Extract facts from meetings and update your knowledge base — person profiles, chronological log, and index. Use when the user asks "ingest my meetings", "update my knowledge base", "extract facts from meetings", "sync meetings to wiki", "backfill knowledge", or wants their PARA/Obsidian/wiki profiles updated from conversation data.

Health-check your meeting knowledge for contradictions, stale commitments, and decision conflicts. Use when the user asks "any conflicts in my meetings", "check for stale action items", "lint my meetings", "consistency check", "are there contradictions", or wants to audit their decision history.

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.

Agent OS: the agent gets smarter on its own. We just hold the line: the grading command and expected result never make it into the success contract we hand it.…

Curated systems, benchmarks, and papers etc. on memory for LLMs/MLLMs --- long-term context, retrieval, and reasoning.

:memo: Vimlike Modal Text Editor in Rust

CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.

Hermes Agent memory plugin/provider for scope-aware recall, SQLite truth, LanceDB semantic search, and hybrid retrieval.

For You Agent——AI 时代的个人随身数字人格。把你的模型、AI 账号、技能、提示词和工作方式，带到每一个 AI 工具里。

A coding agent: give it a prompt and it reads, writes, runs commands, and searches code in a loop until the work is done, using native tool-calling across OpenA…

A secure persistent personal agent server in Rust. One binary, sandboxed execution, multi-provider LLMs, voice, memory, Telegram, WhatsApp, Discord, Teams, and…

Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption

DeepSeek Harness Desktop (dsh-desktop). EAC: Embracing All Creation (揽尽万象). Bundled Node.js runtime with full dsh-CLI kernel, one-click startup, 10 built-in UI…

See your agent think. Zero-config observability & governance for 26 AI agent runtimes: Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Cline, Ope…

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Codex, Copilot, Cursor, Gemini CLI. Local MCP…

Yet another coding agent harness, lightweight and written in go.

a coding Agent from pi. ∞ providers, sub-agents, hashline edits, and a permission gate

Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting…

🧠 Leon is your open-source personal assistant.

The Station, an open-world multi-agent environment that models a miniature scientific ecosystem.

The Frontend Stack for Agents & Generative UI. React, Angular, Mobile, Slack, and more. Makers of the AG-UI Protocol

VelaTerm = iTerm2 + Codex, The Best Terminal for AI Coding