LLM Mart Basic

用于设计分部大纲、分卷大纲、卷纲、章清单与章节微型剧本。适合分卷拆解、章清单落地、卷级启动表编排、卷内节奏校准与故事面承接映射。关键词：分卷大纲、卷纲、章清单、卷级启动表、章节微型剧本、卷内节奏。

用于设计、重写或审计小说封面生图提示词。适合把题材核心意象、人物识别、主色调、构图、风格限制、禁行元素与平台展示约束整理成可交付方案。关键词：封面提示词、封面生图、主视觉、构图、主色调、平台展示。

用于设计或重写总大纲、全书总纲与战略层文件组。适合总纲搭建、M0 / X / C 规划、跨卷推进、终局闭环与总纲级验收。关键词：总大纲、全书总纲、M0、X线、C线、跨卷推进、终局闭环。

设计、重写或补强故事设定全品类——包括世界观设定、技术设定、规则/机制设定、社会制度设定、能力/金手指设定、手法/程序链/证据载体设定。用于产出可叙事化、可证据化、边界与代价明确的作者侧设定裁判源，覆盖规则条款、误导与证伪、程序摩擦、镜头包、实际文件写回与跨阶段演进。支持联动竞对分析、网络调研、深度研究与结构化深入思考，确保设定既有真实感锚点又有竞争辨识度。适合所有品类故事设定的创建、重构、补强与规则边界修复。

用于设计、重写或审计故事面。适合故事面搭建、卷级供血检查、硬抓手补强、跨卷交接与可拆卷可拆章的故事面重构。关键词：故事面、一句话谜面、供血、硬抓手、卷级推进、跨卷交接。

用于设计、筛选、重排和审计小说的全层级标题系统——包括全书书名、分部标题、分卷标题与章节标题。标题即开篇——读者看标题的决策模式与看开头完全一致，但标题受字数限制更严格，且各平台显示规则不同。适合为全书、分部、分卷、多平台版本或逐章生成真正像书名的候选标题，并形成可复盘的命名方案。关键词：设计标题、书名候选、平台适配书名、标题系统、章标题、分卷标题、标题字数限制、标题Hook。

用于设计、重写或维护线索台账、伏笔台账与回收计划。适合把线索、嫌疑、误导、伏笔、回收窗口与兑现后果写成作者可审计、可回指、可跨卷追踪的统一账本。关键词：线索台账、伏笔台账、回收计划、回收窗口、兑现后果、推理公平性。

用于设计或校准作品的题材定位框架。适合从零生成故事概念、题材定位、平台校准、读者承诺梳理与创新组合整理。关键词：题材定位、概念工厂、PK筛选、平台口径、主角抓手、现实锚点、代价锚点、创新组合、代偿原型、套路定位。

用于把小说章节改写为更适合 WebNovel 平台的英文版本。适合强调跨文化可读性、移动端阅读节奏、清晰因果链与全球年轻读者易读性的正文输出；供多个题材的 `题材名-输出WebNovel版` 包装层路由使用。关键词：输出WebNovel版、WebNovel、英文平台、跨文化改写。

用于把小说章节改写为更适合今日头条平台的版本。适合强情节、弱冗余、开篇钩子密集、互动驱动为核心的正文输出；供多个题材的 `题材名-输出今日头条版` 包装层路由使用。关键词：输出今日头条版、今日头条平台、强钩子改写、互动驱动、社交媒体小说。

用于把小说章节改写为更接近传统出版社审稿口味的版本。适合强调文笔克制、逻辑自洽、出版可读性、结构完整与审读友好的正文输出；供多个题材的 `题材名-输出出版社版` 包装层路由使用。关键词：输出出版社版、传统出版、纸媒投稿、出版社风格。

Add educational comments to code files to transform them into effective learning resources. Explains the "why" behind syntax, idioms, and design choices, aligned with the learner's knowledge level and educational goals.

Advisory skill for Contabo resource planning across regions (EU, US-central, US-east, US-west, SIN, UK, AUS, JPN, IND), instance tiers (VPS, VDS, Storage VPS), and add-ons (Private Networking, Additional IPs, Extra Storage, Custom Images). Includes Cloud-Init userData strategy an

Advisory skill for analyzing Contabo cost posture across contract periods, VPS/VDS product tiers, Storage VPS options, and add-ons including Private Networking, Additional IPs, Extra Storage, and Custom Images. Use when the user asks to reduce, explain, or optimize Contabo spendi

Live-guard skill for Contabo Object Storage (S3-compatible) bucket operations including inventory audit, access policy review, retention policy enforcement, and deletion workflows. Hard-stops any bucket deletion requested without verified backup evidence and a documented rollback

Router skill for classifying Contabo tasks and delegating to the narrowest specialist for cost analysis, capacity planning, security hardening, VPS/VDS lifecycle operations, or Object Storage management. Use when the user asks a Contabo question that spans multiple domains or nee

Advisory skill for hardening Contabo infrastructure security: SSH key management via secret IDs, default root and admin user policy, firewall posture review, OAuth2 credential hygiene including token short TTL and environment variable storage, and x-request-id UUIDv4 traceability

Use this skill when compliance controls must be mapped to audit evidence, when evidence collection, retention policy, and legal-hold status need to be assessed across Microsoft 365 workloads, or when an attestation package must be assembled for an auditor or regulator. Defines th

Use this skill when a customer service case must be triaged, routed to the right team, driven to resolution, and captured as reusable knowledge in Dynamics 365 Customer Service. Covers intake-to-routing, SLA tracking, escalation gates, knowledge capture, and post-resolution CSAT.

Use this skill when a Dynamics 365 change request must be structured and progressed through impact assessment, fit-gap analysis, UAT sign-off, go/no-go decision, go-live execution, and hypercare using the Success by Design framework. Defines the full change-to-go-live flow — chan

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.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

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.

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.