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

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.

Daily standup: all 9 departments report on the current project in parallel

Identify skills injected where not needed, propose regex and description tightening

Draft X/Twitter announcement post (or thread) for the latest plugin release

Deep quality audit of all skills, agents, and commands for inconsistencies, gaps, duplication, and token waste

Analyze negative-signal sessions for a skill, identify failure patterns, propose and apply fixes

Eval all skills with sufficient data, rank by procedure-following score, identify candidates for optimization

Propose a skill revision and compare fresh executions under a frozen rubric

Prune stale entries from the whetstone sync decision log

Bump version, commit, push, mirror to ai-skills, and update local plugin

Run the SkillOpt process-skill optimizer (offline, local). Default prints the exact bare-terminal command (safe); --run executes it in-session (hardened + checkpointed).

Analyze reference repos and recommend skill/agent/command improvements based on cross-repo patterns

Triage all open PRs with parallel agents, label, group, and review one-by-one

Author a new skill from scratch with paired trigger fixtures and full validation. Use when adding a skill that has no upstream skills.sh source (discipline, meta, or internal-pattern skills).

Create Architecture Decision Records with format selection and lifecycle management

Score each of the 5 agent-native principles (parity, granularity, composability, emergent capability, improvement-over-time) against a codebase and report gaps

Explore requirements and approaches through collaborative dialogue before planning implementation

Create engaging changelogs for recent merges to main branch

Expand each section of a plan via parallel research agents that add framework specifics, library conventions, and concrete implementation steps

Post-ship documentation sync. Reads all project docs, cross-references the diff, updates README/ARCHITECTURE/CONTRIBUTING/CLAUDE.md to match what shipped, polishes CHANGELOG voice, and optionally bumps the version.

Record a video walkthrough of a feature and add it to the PR description

Open-source, self-hosted AI media server. One server replaces your entire media stack, with a web app, native iPhone app, and an AI agent that gets things done.…

A curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.

🦦 Crayotter: A Multimodal AI-Agent for Video-Editing, Video-Composing, and Video Production. Powered by Multimodal LLMs for autonomous Text-to-Video agentic fr…

Webextension tool for Odoo

基于多模态视觉感知与 LLM Agent 的 macOS 微信自动化框架 | Visual RPA for WeChat

The operational superset of Pi Coding Agent — everything Pi, plus observability, governance, recovery, evaluation and multi-agent orchestration. Pi Coding Agent…

Metrik 可以集中查看本机多个 Agent 的配额余量和 Token 消耗，目前支持 ChatGPT、Claude、GLM、Kimi 等主流 AI 服务。

An AI agent with a real self — soul she wrote, desires that drive her, a heartbeat for autonomous action, dreams she processes when you're away. Capability supe…

Production-ready open source terminal coding agent with readable, layered code: permission rules, OS sandboxing, MCP, skills, sub-agents, and Anthropic, OpenAI-…

Answer me with HTML — an agent skill that answers hard questions with a one-page HTML you can actually read. 让 AI Agent 用一页 HTML 回答复杂问题。

Prompt packs that make any AI agent a LaTeX expert — fix errors, polish writing, format for venues, read papers, recover source

Claude Code plugin: universal radial-tree exploration engine. One tree skill + swappable presets (brainstorm / attack / design / code-audit) for divergent ideat…

Claude Code + OpenClaw + Codex + WorkBuddy 中文教程 | 50篇完整教程 + 1张速查卡 | 80万+内容量 | 1500+实操示例 | AI Coding / Agent 四线学习路径（编程+助手+Agent+办公）

SmartLabelBench 2026: LLM-Powered Auto Annotation and Dataset Builder for Everything

从零开始玩转OpenClaw：最全面的中文教程，涵盖安装、配置、实战案例和避坑指南（github版）

Native Android GUI for running AI coding agents locally on-device. No terminal or PC required.

基于 LangChain/LangGraph 的 ReAct Agent ，结合 RAG、工具调用与 Streamlit 界面，面向智能客服与报告生成场景。

An open-source, local-first AI learning workbench

Open-source coding agent for your terminal, built in Rust and on a journey of continuous community improvement. Issues and PRs welcome.

Matt Pocock 技能集的中文翻译版 — 地道中文，原汁原味的技术术语。基于 mattpocock/skills 复刻。每日中午12点钟同步