LLM Mart Basic
@llm-mart · Joined Jun 2026
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.
WorldQuant 101 Formulaic Alphas — 因子计算、IC测试、回测一体化工具包。 基于Kakushadze (2015) 论文,提供101个价量/波动率/相关性因子的Python/Pandas实现。 Use when: "alpha101", "101因子", "formulaic alphas", "因子回测", "因子IC", "因子筛选", "WorldQuant因子", "价量因子", "alpha因子库".
Automate Amplitude tasks via Rube MCP (Composio): events, user activity, cohorts, user identification. 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.
/dashboard-cockpit
Dashboard cockpit
Repeatable pass upgrading an Angular admin dashboard into a compact black-and-cyan developer-cockpit PWA
/drift-check
Drift check
Run the drift-detection checklist (incl. agent-drift signals); report + fix in-turn
/final-review
Final review
Orchestrate the final review fan-out (integration + diversity + risk + release readiness)
/improve-lint
improve-lint
Run the AI-augmented lint self-improvement loop on the current project. Scans `.lint-history/` for recurring violation patterns (≥3 hits in 30d window), drafts a Claude-ready prompt to author a new semgrep rule for the top candidate, and surfaces the proposal under `.lint-history/proposals/<ts>.md`. Non-blocking analysis. See rules/lint-doctrine.md § Self-improving.
/install-lint-stack
install-lint-stack
Bootstrap industry-leading lint+autofix+commit-hygiene stack on the current project. Drops in lefthook, oxlint, ESLint, Prettier, Stylelint, markdownlint, ruff, shellcheck, shfmt, yamllint, hadolint, actionlint, jscpd, knip, semgrep, gitleaks, commitizen + git-cz-emoji (emoji-mandatory commits), and semantic-release. Idempotent — re-runs upgrade safely. See rules/lint-doctrine.md.
/list-arcs
list-arcs
Surface all retrospective documents with key shape metrics; compare arcs deliberately.
/multimedia-enrich
Multimedia enrich
Progressive multimedia enrichment pass — add high-value audio/video/image/interactive to a site, run again and again
/plan-execute-verify-repair
Plan execute verify repair
Run the autonomous-engineering operating loop on a task (plan→implement→verify→repair→report)
/post-arc-retrospective
Post arc retrospective
Capture the cumulative output of a /loop arc into a single auditable retrospective document; scans the heymegabyte-claude-skills plugin for modified files, categorizes by directory, counts LOC delta, extracts tool counts from MCP servers, and writes a timestamped report to retrospectives/
/prepare-multi-file-brief
prepare-multi-file-brief
Turn a comma-separated list of file paths into a fully structured Pattern A agent brief — ordered writes, per-file schemas, and a verification step baked in.
/prepare-skeleton-brief
prepare-skeleton-brief
Turn Pattern B from agent-resilience-discipline into a one-keystroke agent brief for a single-file deliverable < 300 lines.
/process
Process
Chain the full Superpowers process flow — brainstorm → plan → worktree → build → review → finish — on one slash command
/retro
Retro
Generate a timestamped arc retrospective from the past 7 days of git history in `~/.agentskills`.
/review-global-prompts
Review global prompts
Review ~/.claude/CLAUDE.md + rules for contradictions, stale guidance, duplication; consolidate
/run-evals
Run evals
Batch-run all LLM eval cases in tools/evals/cases/*.json; aggregate pass/fail, cost, regression vs last run; exit nonzero in CI mode
/saas
Saas
One-line SaaS — from a description, scaffold a complete CF-native multi-tenant SaaS (Hono + D1 + Drizzle + Better Auth + Stripe + shadcn) deployed to a real URL
/security-supply-chain
security-supply-chain
Unified supply-chain audit. Checks GitHub Actions SHA-pinning (`sha-pin:check`), package.json git+https deps (per `no-gitlab-megabytelabs-deps` semgrep), gitleaks scan, and trufflehog verified-only sweep. Surfaces any tag-mutable, git-URL, or secret-exposed surface. Per rules/ai-agent-security.md § Supply chain.
/self-improve
Self improve
Run a learning pass after a major run; fold reusable lessons into global config
/session-recap
session-recap
Summarize recent CHANGELOG.md entries for context restoration. Parses the canonical heading shape `## YYYY-MM-DD — pass-N — summary`. Filters: last N (default 10), YYYY-MM date prefix, or "today". Supports --json for machine-readable output.
/skill-health
Skill health
Run quality-scores + token-budget + dep-graph, interpret results, flag missing budgets, orphans, and oversize skills
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