LLM Mart Basic
@llm-mart · Joined Jun 2026
Imported from aaaaqwq/agi-super-team/skills/agent-capacity-modeler.
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。
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.
/shard
Shard
`crabbox shard` forks a [checkpoint](checkpoint.md) into `--count` leases
/share
Share
`crabbox share` grants other people access to an existing lease through the
/ssh
Ssh
`crabbox ssh` resolves a lease and prints a ready-to-run `ssh` command for it.
/status
Status
`crabbox status` prints the current state of a lease: its slug, provider,
/stop
Stop
`crabbox stop` ends a single lease. For coordinator-backed and direct cloud
/sync-plan
Sync plan
`crabbox sync-plan` prints the local sync manifest and its size hotspots
/tunnel
Tunnel
`crabbox tunnel` opens one foreground SSH local port-forward to a resolved
/unshare
Unshare
`crabbox unshare` removes sharing rules from a coordinator-backed lease. It is
/usage
Usage
`crabbox usage` reports lease cost and usage estimates from the broker, broken down by user, organization, or the whole fleet.
/verify
Verify
`crabbox verify` checks a signed run receipt produced by `crabbox run --attest`.
/vnc
Vnc
`crabbox vnc` prints (or opens) the connection details for a desktop-capable
/warmup
Warmup
`crabbox warmup` leases a box and waits until it is ready: it provisions (or
/watch
Watch
`crabbox watch` runs a command on a warm lease, then watches the local
/webvnc
Webvnc
Linux portal viewers default to **Match window**: only the connected controller
/whoami
Whoami
`crabbox whoami` calls the broker's `/v1/whoami` endpoint and prints the
/add-dep
Add dep
Vet a new or changed third-party dependency for license, provenance, and supply-chain risk before any install runs.
/adr-status
Adr status
Inspect ADR health read-only; optionally select one ADR with --adr N.
/adr
Adr
{{SKILL_ENTRY:decision-lifecycle}}
/audit
Audit
Assemble the governance record for a range — commits, overrides, ADRs, sprint auto-decisions, open questions, checkpoint findings — into one dated audit packet. Read-only.
/btw
Btw
Lightweight Q&A about the project — answer from context and return, no routing, no state change.
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间,让人与智能体在此协作
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