LLM Mart Basic

用于强化章节结尾的章末钩子。适合章末抢救、结尾补针、翻页感增强、下一章驱动增强与最后 150–300 字局部强化。关键词：强化章末钩子、结尾没翻页感、只修结尾、下一章驱动、最后一句、章末补针。

用于强化章节开头前 150–300 字的入场抓力。适合章首抢救、首屏留存优化、异常前置、冲突前置与只修前两三段的局部强化。关键词：强化开头、章首抓人、前 150–300 字、首屏留存、开头太慢、只修前两段。

用于设计或重写场景单元、章节场景与微型剧本。适合场景施工卡落地、动作链推进、证据入场、对话承压与控制卡到场景的职责拆解。关键词：场景单元、场景施工卡、微型剧本、动作链、证据推进、场景职责。

用于设计、重写或强化对话冲突。适合把角色对话写成立场碰撞、潜台词拉扯、信息释放与情绪升级并存的有效场景。关键词：对话冲突、盘问、谈判、争执、潜台词、关系升级。

执行微空间或受限空间场景。用于在楼道、电梯、值班室、走廊、地下车库、出租屋、候诊区、办公室后区等熟悉空间里，把空间常态、微反常、人物动作、后果升级与证据入场咬成一个可落地的场景引擎；执行时必须先加载 通用-执行场景单元，再叠加本 Skill 的微空间专项工法。适合微空间惊悚、受限场景压迫、日常异化场景设计。

提纯多平台输出前的中文母稿。用于在不同平台改写前，把正文母稿修成信息稳、事件链稳、情绪主轴清、证据与规则关键点不丢、追读链完整、平台可分化的高质量源稿，避免后续平台适配建立在松散底稿上。适合多平台前置精修、母稿加固、跨平台源稿提纯。

用于撰写、重写或审计小说书评。适合把全书 / 分部 / 分卷 / 分章的阅读体验、核心卖点、平台传播口径与非剧透钩子写成可直接发布的书评文件。关键词：撰写书评、推荐文案、分章安利、平台推荐评述、非剧透书评、今日头条。

用于撰写、重写或审计作品的内容简介。简介即开篇——读者看简介的决策模式与看开头完全一致：在 3–5 秒内决定要不要点开。适合把题材卖点、主角处境、核心冲突、持续承诺与情绪抓手压缩成平台可用文本，支持全层级（全书/分部/分卷/章节）简介。关键词：内容简介、作品简介、平台简介、卖点压缩、简介重写、简介审计、简介同构。

用于润色已有章节正文。适合整章精修、局部重写、节奏提纯、章首抓力增强、中段回报提亮与章末钩子收紧。关键词：润这章、精修正文、整章精修、局部重写、节奏提纯、直接回写。

润色章节后的 `## 作者有话说`。用于把作者有话说修成读者向小剧场：一丢丢创作花絮 + 一点贴着本章余波的情绪共鸣 + 一个开放式轻追问，而不是创作说明会、设定讲义或章节总结。适合发布前精修、后记前小剧场重写、把作者有话说从复盘腔改回读者腔。

专用于小说写作的结构化深度研究 Skill。支持对题材趋势、平台生态、专业知识、场景环境、人物原型、写作技法、读者市场等研究域，执行大纲生成→并行深搜→报告输出的全流程深度调研。关键词：深度研究、写作研究、题材调研。

用于生成写前章节控制卡、章节施工卡或章节作战卡。适合写前施工、场景拆分、中段回报预埋、章末钩子预埋与上游供血对齐。关键词：章节控制卡、施工卡、作战卡、中段回报、章末钩子、写前施工。

用于对单章或连续多章执行"初始化→控制卡→创作→润色→去AI味→审阅回炉→读者产物→摘要"的完整章节闭环。适合章节写作 SOP、批量写章、日志续跑、9.2+ 回炉与最终摘要收口。关键词：章节创作闭环、跑完整 SOP、批量写章、回炉到 9.2、日志续跑、最终摘要。

用于管理章节与卷层的连续性、冷热线、动态状态与回归压力。适合写前判断该回什么、写后更新动态状态、检查中段失温与追踪章节链路热度。关键词：连续性、冷热线、谁该回来了、哪些线快忘了、动态状态、失温检查。

用于蒸馏一部成功小说的叙事架构 DNA、故事线台账、套路指纹与读者吸引留存策略，产出可被下游写/审/改 Skill 消费的"作品蓝本模板"。蒸馏优先级：书名策略 > 内容简介 > 黄金三章 > 章标题/章首/章末模式 > 套路配置 > 故事线台账。适合把一部作品的"读者为何点开/为何追读"的核心回路提炼为可参照的结构约束。关键词：蒸馏作品蓝本、叙事架构DNA、故事线台账、读者吸引指纹、黄金三章拆解、书名策略、套路指纹、章标题策略、钩子指纹、交叉蒸馏。

用于蒸馏一位小说作者的文笔 DNA，产出可被下游写/审/改 Skill 消费的"作者风格模板"。适合把作者的多部作品的文笔特征提炼为可测量的风格约束（句长基线、段落节奏、感官偏好、对话标签偏好、比喻指纹、禁忌清单），并在目标项目根目录自动注册到 Agents.md。关键词：蒸馏作者文风、作者风格模板、文笔DNA、风格注入、文风复刻。

用于从写作研究报告（题材×平台级）中提取可执行写作约束，产出"写作研究模板"，作为下游写/审/改 Skill 的题材×平台默认约束基线。蒸馏源默认扫描小说项目根"写作研究/"目录 + "调研报告/"目录 + "CommonSkills/写作研究/"目录；支持指定目录、文件、URL 或 网络搜索内容。关键词：蒸馏写作研究、研究报告提取、题材平台约束、写作约束基线、规则提取。

用于在已有素材库目录（默认：项目根/素材库/）中定向补充、扩写或新建素材条目。适合素材库缺件诊断、定向搜索补充、按格式落盘、同步更新总索引与搜索日志的全流程闭环操作。关键词：补充素材、素材库缺件、素材收集、桥段池补全、人物设定填充、名场面扩写、搜索补素材、素材格式标准化。

用于设计单元案、案件母板或事件引擎。适合把局部事件做成可供章节拆分、主线供血、规则显影、人物代价与案件余波同时成立的结构骨架。这里的“主线供血”默认指：推进主线关键问题、补入可回收拼图或抬升核心冲突压力。关键词：事件案件引擎、单元案、证据链、嫌疑池、案件余波、主线供血。

用于设计、重写、补强人物传记。适合产出可回指、可核查、可直接调用的人物裁判源，并统一承接传记模板、动机代价、能力边界、关系网、成长时间线、价值观与心理弧线。内置 Nuwa 深度人物心智模型注入（心智模型提炼、表达DNA、决策启发式、矛盾张力、诚实边界）。关键词：设计人物传记、人物裁判源、成长时间线、价值观、关系网、心理弧线、心智模型、表达DNA、决策启发式。

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.

Inventory devices for an Auvik tenant with type, manage status, and lifecycle breakdown

Audit a tenant's networks, interfaces, and saved configurations; flag drift and missing backups

Single-tenant Auvik snapshot - devices, alerts, networks, billing usage

Phishing-simulation results and click-rate trend for a given window

Human risk score report for one client or the whole portfolio, built from training completion and phishing-simulation performance

Training completion snapshot for one client or the whole portfolio — completion rates, overdue users, and cadence status

Check backup health for one Axcient-protected device

Backup health overview across every device for one Axcient client

Azure cost and pricing analysis for a subscription — Advisor cost recommendations, retail pricing lookups, and quota-driven right-sizing signals, scoped to one subscription

Resource health and diagnostics triage for an Azure resource or subscription — Resource Health status, AppLens deep diagnostics, and Azure Monitor alert state

Portfolio-wide backup job health snapshot - failure count, at-risk clients, and storage trends

Restore-readiness check - has this actually been restore-tested, for one client or the whole portfolio

Retention and RPO compliance audit against contracted requirements, for one client or the whole portfolio

Create a new Better Stack uptime monitor

Triage current Better Stack incidents

Check all Better Stack monitor statuses and identify downtime

Search logs via Better Stack Logtail

Update a Better Stack status page with current status or maintenance

Investigate a single Blackpoint Cyber / CompassOne detection end-to-end

Portfolio-level Blackpoint Cyber / CompassOne rollup of detections and exposure across all tenants

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.