LLM Mart Basic

根据真实业务与数据处理事实生成隐私政策和服务条款页面草稿。支持明确输入与结果回读。Use to draft website privacy

把重复操作封装成通用 Skill，并按需提供宿主 slash command 适配入口。支持明确输入与结果回读。Use to turn a

将已有 clone 连接到用户自己的 GitHub 仓库并保留来源与历史。支持明确输入与结果回读。Use to publish a cloned

生成 changeset 草稿并提供编辑入口，审阅后验证版本计划。支持明确输入与结果回读。Use to create a changeset

根据实际包变更生成 changeset，并按请求更新版本与 CHANGELOG。支持明确输入与结果回读。Use to manage package

从已核实的社区地址或仓库列出可访问的 XBTI 人格测试案例。支持明确输入与结果回读。Use to browse a gallery of

用真人尽调思路校验用户提出的事实命题：拆解可验证问题、检索一手资料、 交叉验证证据链，并给出带置信度和不确定边界的结论。 Trigger when the user asks to fact-check, verify a claim, confirm whether something is true, source-check an answer, or mentions "事实校验", "帮我确认", "这是真的吗", "verify this", "fact check", "source check", "due diligence".

Create learner-friendly English subtitles with level-aware glosses and

Use when the user asks to find and download a film, series, or long video. 以 aria2 为默认传输后端，完成多源测速、续传、容量预检、版本核验与字幕验收；也适用于“帮我下载这部电影”。

面向中国大陆网站的一站式备案与上线 Skill Kit：当用户说“办 ICP 备案”“做公安联网备案”“备案后绑定域名”或 "handle China website filing" 时，按权威页面完成材料、审核、域名切换、合规展示与巡检留痕。

给纯文本模型"看图"：调用智谱 GLM-4V-Flash（免费）把图片转成文字描述。当用户要求描述/识别/读取图片，或任务里出现图片文件（截图/图表/照片）而当前模型无法直接看图时，优先调用本 skill。需要图片磁盘路径，可附带具体问题。

把需求、现有界面与真实素材落实为有辨识度、交互一致的前端，覆盖页面、组件、导航、GSAP 展示及图片音视频。触发：设计前端、界面不够专业、制作交互案例集；design or refine a frontend UI.

面向公众号、网站、App、策划案、海报等真实发布场景，为读者可见文本建立受众、品牌角色、组件惯例与信息可见性门禁。Use when generating, editing, rendering, publishing, or reviewing audience-facing copy for brand and context fit.

把单人照片用 gpt-image-2 重绘成身份保真的 Riso 头像，并检查五官、手指、饰品与圆形裁切。Use when the user asks“做成 Riso 人像”“生成孔版印刷头像”or “create a Riso portrait”。

从产品与品牌事实出发，独立推导适合当前产品的定位、叙事与视觉，并完成 Landing Page 实现、响应式和生产回读；适用于创建官网、品牌官网重构、产品价值不清或视觉与产品不匹配。

Initialize or refactor a frontend project to use TanStack Query as the unified server-state layer. Use when the user asks to install TanStack Query, initialize query infrastructure, migrate ad hoc fetch/invoke/useEffect request state, standardize query keys, or make app network r

Use when the user asks for "App生成器", "生成 Web App", "生成 Tauri App", "生成原生 macOS App", "Finder Quick Action", "只创建 web", or to standardize an existing app with branding, CI/CD, native integration, and Lovinsp where applicable.

为 Electron 桌面应用设计、实现和验证增量自动更新，覆盖 macOS Sparkle、签名、appcast、发布产物与失败拦截。用户提到增量更新、Sparkle、检查更新、appcast、DMG 更新或 delta updater 时使用。

Publish or submit a validated Skill. Default to the LovStudio official website, run lov-skill-pricing automatically, and use other channels only when explicitly named.

重置 Obsidian 缓存，解决卡在 "Loading cache..." 的问题。 当用户说 "obsidian 卡住"、"loading cache"、"obsidian 打不开"、"重置 obsidian 缓存" 时触发。 Trigger when the user mentions Obsidian startup hangs, cache reset, or "Loading cache".

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.

Instrument services with structured logging, Prometheus metrics, and OpenTelemetry tracing. Build Grafana dashboards, write Prometheus alerting rules, run k6 load tests, and plan infrastructure capacity.

Generate, test, validate, explain, and debug OPA (Open Policy Agent) Rego policies and Conftest configurations. Covers deny/warn/violation rules, unit tests, regal linting, conftest fmt, namespace design, input shape analysis, and GitHub Actions integration. Use when asked to "write a policy", "test a rego file", "validate policies", "explain this rego", or "why is my policy not firing".

OpenShift SCC diagnosis and hardening, Route TLS patterns, OpenShift GitOps app delivery, and cluster upgrade validation.

Comprehensive PR review across six dimensions — cost impact, environment drift, ownership gaps, SOC 2 compliance, deprecated API / version hygiene, and rollback feasibility. Each mode inspects the diff and current file state, reports findings with severity, and recommends concrete fixes. Use when preparing a PR for merge, conducting a pre-deployment readiness check, or performing a post-merge risk assessment.

Production-readiness preflight check for a directory, repo, or single file. Auto-detects file types (Kubernetes manifests, Terraform, GitHub Actions workflows, Helm values/charts, Flux Kustomizations/HelmReleases, Dockerfiles, shell scripts) and applies type-specific checks across the whole scope. Returns a per-file summary table and aggregated verdict. Use before deploying, merging, or applying a folder of config. For PR diffs spanning multiple files use /platform-skills:pr-review instead. For deep Helm chart work use /platform-skills:helmchart instead.

Apply product thinking to platform work — DevEx audits, friction analysis, RFC/ADR drafting, incident communication, post-mortems, capacity planning, cost optimisation, and platform health review.

Generate renovate.json covering all dependency file types used in a repo, emit a GitHub Actions workflow that validates renovate.json on every PR, or generate a pre-commit hook for local validation.

Detect and respond to in-container threats at the syscall level using Falco (eBPF-based, CNCF, open-source, no license cost). Covers Falco installation on EKS/GKE with eBPF driver, custom rule authoring, alert routing via Falcosidekick, rule debugging, and bridging Falco runtime signals to Kyverno admission enforcement. Use when asked to "detect privilege escalation in containers", "set up runtime threat detection", "write a Falco rule", "route Falco alerts to Slack", or "debug why my Falco rule is not firing".

Secrets strategy, External Secrets Operator scaffolding, Sealed Secrets seal/rotate/backup, rotation runbooks, and Kubernetes-side secrets audit.

Bootstrap and operate a self-improving agent workspace. Scaffolds .learnings/ and memory/ directories, captures errors and learnings during a session, detects recurring patterns, recalls verified lessons, and promotes stable entries to scoped rule files (.claude/rules/ or ~/.claude/rules/). Also implements the Proactive Agent pillars — WAL protocol, working buffer, SESSION-STATE, daily notes, VBR, VFM scoring, ADL decision logic, heartbeat, and reverse prompting. Use when asked to "remember this lesson", "set up agent memory", "log that error", "what did we learn about X", "promote learnings", "revoke that rule", "capture session state", or "enable proactive mode".

Scaffold a multi-agent AI setup for any repo. Scans the codebase, interviews the developer, generates agent configs for whichever AI tools the repo uses (Copilot, Claude Code, Cursor, Codex, Windsurf). Use when asked to "set up agents", "scaffold Copilot agents", or "create an AGENTS.md".

Secure the software supply chain from source to running container. Covers Cosign keyless image signing (Sigstore/Rekor), SBOM generation and attestation (Syft), vulnerability scanning with severity gates (Trivy/Grype), SLSA Level 2 provenance, and Kyverno/OPA admission enforcement. All open-source, no license cost. Use when asked to "sign my image", "generate an SBOM", "scan for CVEs", "attest build provenance", "enforce image signatures in Kubernetes", or "implement SLSA".

Runs through the full Terraform validation pipeline — fmt, validate, tflint, security scan — and reviews a module or plan for blast radius, IAM risk, and state impact.

Triages a PR comment — from a bot (Copilot, CI) or a human reviewer. Routes to the `triage_helper.py` helper for identity checks, thread snapshotting, isolated-worktree fixes, and publish/reply/resolve mechanics; you classify the finding and apply a justified fix. `--dry-run` is fully read-only (investigation and a printed plan, zero mutations). `--no-resolve` runs the full fix/reply workflow but never resolves a thread. Run from inside the repo.

Scan container images, filesystems, git repos, and existing SBOMs for CVEs, secrets, and license violations using Trivy. Covers local CLI, CI severity gates with SARIF upload, and continuous monitoring via Trivy Operator (Flux HelmRelease). Use when asked to "scan my image", "check for CVEs", "scan this repo for secrets", "scan an SBOM", or "set up continuous cluster vulnerability monitoring". IaC misconfig → /platform-skills:checkov. Admission posture → /platform-skills:kyverno. Image signing/SBOM generation → /platform-skills:supply-chain.

Audit GitHub Actions workflows, composite actions, Dependabot configs, and pre-commit configs for security findings using zizmor — template injection, credential persistence, unpinned uses, over-broad permissions, impostor commits. Covers local CLI, auto-fix, zizmor.yml policy, severity-based CI gates, SARIF upload, and pre-commit. Use when asked to "audit my workflows", "run zizmor", "is this workflow safe", "check for template injection", "pin my actions", or "set up a zizmor CI gate". Workflow syntax and shell errors → /platform-skills:github-actions (actionlint). IaC misconfig → /platform-skills:checkov. Image and dependency CVEs → /platform-skills:trivy. Keeping SHA pins fresh → /platform-skills:renovate.

반복 작업을 `/이름` 으로 호출. 파일명 = 커맨드 이름(`fix-issue.md` → `/fix-issue`).

이슈 #$ARGUMENTS 를 처리한다(이슈 우선 워크플로):

AGENTS.md 생태계(rules·memory·agents·skills·commands·workflows)의 연결 구조를

이슈/기획서 기준 SDLC 한 사이클(이슈→개발→테스트→검증→PR/MR)을 사람 개입 없이 자동 실행.

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…