LLM Mart Basic
@llm-mart · Joined Jun 2026
Use this skill for Azure management-group hierarchy, subscription placement, resource-group boundary, and platform-versus-workload ownership decisions that affect governance, operations, and landing-zone scale.
Review Azure workload cost posture against the Well-Architected Framework Cost Optimization pillar: cost modeling, rightsizing, reservations, hybrid benefit, storage lifecycle, and idle resource elimination.
Review Azure workload reliability against the Well-Architected Framework Reliability pillar: availability targets, AZ/region topology, health monitoring, data resilience, deployment safety, and chaos testing.
Review Azure workload security posture against the Well-Architected Framework Security pillar: identity and access, segmentation, data protection, threat detection, secure development lifecycle, incident response, and policy compliance.
Use this skill when reviewing Backstage Scaffolder software templates. Trigger when the user asks whether a template is safe for developer self-service, whether template RBAC gates are in place, whether input parameters are validated, whether a step action has excessive blast rad
Use this skill for Cilium network policy review across the three policy formats (Kubernetes NetworkPolicy, CiliumNetworkPolicy, CiliumClusterwideNetworkPolicy), L7 policy via embedded Envoy, ClusterMesh cross-cluster semantics, Hubble flow observability, and CiliumEgressGatewayPo
用于对小说作者做"自我进化"蒸馏:①手动 / 周期回访(挖创作判断、捕获叙述原声(A 类)与创作判断原声(B 类)、周期蒸馏回填"作者小说风格画像"(十层)并反向净化防 AI 自创);②全流程嵌入(选题构思 / 竞品 / 大纲 / 人物 / 背景 / 章节创作等全部环节自动调用,低频环节必采 1–2 问、高频草稿环节只读消费画像);③散落触点(改稿痕迹 / 审阅回流 / 作者窗口 / 口述转写原声);④像不像审计(原声句占比 / 惯用语命中 / 立场显影溯源 / 风格漂移,脚本取数)。与 通用-蒸馏作者文风 组成"静态种子 + 动态进化"双闭环,让写出来
用于围绕起点中文网或其他目标平台的同题材 TopN 候选池,按“市场数据层→内容创作层→运营策略层→受众反馈层”的四层框架锁定 3–5 本核心强样本并逐本深搜式竞对分析;若用户明确要求,也可对 TopN 全量逐本落盘。适合搜索榜单、筛选强样本、阅读目录/公开正文/设定/书评/读者评论/读后感/拆解材料,并在 `竞对分析/` 中为每部作品分别写出可举证、可横比、可回用于当前项目的详细竞对分析报告。关键词:竞对分析、竞品分析、标杆作品拆解、TopN 榜单、同题材对标、榜单深搜、四层拆解、读者评论分析、单书竞对报告。
用于创建连载小说章节正文、作者有话说与章节后记。适合新写单章、重写章节、扩写草稿、直接写回章节文件与完整跑通正文落稿工作流;其中 `## 作者有话说` 默认按读者向小剧场处理,不写成章节点评或创作总结。关键词:写章节正文、重写这章、扩写正文、作者有话说、章节后记、直接写回文件。
用于对章节正文做去 AI 味重写。适合主编式多轮去味、先诊断再定强度、整章去模板腔、局部拆解释腔、打散均匀句群、保信息重写与人物声音去同腔化。关键词:去AI味、主编式去味、多轮改稿、模板腔、解释腔、均匀句群、太像AI、重写这段。
用于做章节或片段的多平台适配策略。适合平台分发前的策略设计、改写前推演与平台撞车修复。关键词:多平台适配、平台差异矩阵、改写前推演、平台撞车修复、平台风格拉开。
用于对单章或多章执行多平台输出全流程编排。适合多平台输出 SOP、批量平台分发、断点恢复、门禁回炉与最终摘要收口。关键词:多平台输出编排、平台分发、断点恢复、门禁回炉、平台日志、最终摘要、今日头条。
用于对指定提纲执行"审阅→修改→复审"的闭环,直到双轴评分(技法分 ≥ 6.0 / 留存分 ≥ 5.0)加权的综合评分连续两轮独立审阅在保留两位小数后均严格大于 9.20。适合大纲审阅优化 SOP、报告复用、回炉循环、评分门槛控制与最终回执收口。关键词:大纲审阅闭环、回炉到 9.20 以上、双轴评分、复审循环、主报告覆盖、提纲优化 SOP。
用于审阅人物传记。适合检查身份归属、动机代价、能力边界、关系网、写作抓手、心理弧线与索引映射是否成立,并输出可落库、可回写的传记审阅报告。内置 Nuwa 深度审阅(心智模型、表达DNA、矛盾张力、诚实边界、决策启发式)。关键词:审人物传记、人物审阅、能力边界、关系网、心理弧线、传记报告、心智模型、表达DNA。
用于审阅分部大纲、分卷大纲、章清单与单元案执行版。适合检查上级分配内容是否全量落地、5/15 节奏与钩子是否成立、章中回报是否存在、单元案是否能阶段闭环并供血主线,并输出可回写的分层审阅报告。关键词:审分卷、分卷审阅、章清单审阅、章中回报、卷内节奏、分层报告。
用于审阅总大纲、全书总纲与战略层文件组。适合检查总纲包对象是否完整、M0 / X / C 体系是否稳固、四阶段机制递进是否成立、单元案矩阵是否持续供血主线,并输出可回写的总纲审阅报告。关键词:审总纲、全书总纲审阅、M0、X线、C线、总纲报告。
用于审阅故事设定、手法、程序链、证据载体或规则文档。适合检查规则是否可执行、边界与代价是否明确、是否可证据化、是否具备程序摩擦与镜头化表达,并输出可落库、可回写的设定审阅报告。关键词:审故事设定、设定审阅、规则边界、证据化、程序摩擦、设定报告。
用于审阅章节正文的执行质量。适合检查章首抓力、中段回报、章末钩子、现实落地、规则边界、链路失配与可回写的审阅结论。内置人物执行审计(声口一致性、心智模型落地、压力反应匹配、误判/盲区触发、关系拉扯兑现)。关键词:审这章、章节审阅、章首抓力、中段回报、章末钩子、审阅报告、人物执行审计、声口检测。
用于在选定平台与题材之后、设计大纲之前,完成项目级战略初始化。唯一目标:在平台和题材约束下确定最能吸引读者和最能赚钱的小说要素清单。 核心方法:从写作研究和竞对分析数据出发自主决策。核心产出:项目根目录下的 Agents.md(强制产出)+ 项目初始化蓝皮书。 关键词:项目初始化、项目策划、Agents.md、从数据出发、套路自主决策、蓝皮书
用于以默认极严、保守、负面证据优先的口径评估作品在目标平台的签约或过稿潜力。适合统一承接评估流程骨架、分阶段准入评估、材料完整度判断、评分维度、概率区间、封顶与一票否决规则,并兼容竞争位 / 竞品威胁评估语境。评估{目标平台}项目时,强制要求使用多种可用网络搜索工具检索{目标平台}同题材 TopN 候选池(起点默认按起点中文网榜单检索,其他平台按可用性调整),并按 "TopN 候选池 + 3–5 主压制样本 + 四层竞对拆解"做从严对照。目标平台路由优先级:用户显式指定 > Agents.md 主输出平台 > 默认回退起点中文网。关键词:平台签约评估、极
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.
/story-cover
Story cover
网文封面生成。分析书名题材,生成专业封面图。
/story-deslop
Story deslop
网文去AI味。检测并清除文本中的AI写作痕迹,让文字回归自然。
/story-import
Story import
逆向导入已有小说。将已写好的小说反向解析为标准项目目录结构。
/story-long-analyze
Story long analyze
长篇网文拆文。深度拆解爆款长篇小说的黄金三章、人设、爽点、节奏。
/story-long-scan
Story long scan
长篇网文扫榜。分析起点、番茄、晋江等平台排行数据,提炼市场趋势。
/story-long-write
Story long write
长篇网文写作。从大纲到正文,辅助长篇网络小说的创作。
/story-review
Story review
多视角对抗式审查。使用多个 Agent 对作品进行多维度审稿。
/story-setup
Story setup
网文写作环境部署与检查。部署 hooks、rules、agents、项目指令等基础设施;传入 check 只检查不改动。
/story-short-analyze
Story short analyze
短篇网文拆文。拆解爆款短篇的故事核、结构、情感线和反转设计。
/story-short-scan
Story short scan
短篇网文扫榜。分析知乎盐言、番茄短篇等平台热门数据。
/story-short-write
Story short write
短篇网文写作。辅助短篇小说创作,从构思到成稿。
/story
Story
网文工具箱路由入口。根据模糊意图自动分发到对应的写作、拆文或扫榜工具。
/browser-cdp
Browser cdp
浏览器操控。通过 CDP 复用 Chrome 登录态执行浏览器自动化。
/story-cover
Story cover
小说封面生成。根据书名、作者名和题材生成专业网文封面。
/story-deslop
Story deslop
网文去 AI 味。检测并清理模板化、解释腔和过度工整表达。
/story-import
Story import
逆向导入已有小说,将成稿或半成品解析为可续写项目。
/story-long-analyze
Story long analyze
长篇网文拆文,分析黄金三章、人设、爽点和长线节奏。
/story-long-scan
Story long scan
长篇网文扫榜,分析起点、番茄、晋江等平台趋势。
/story-long-write
Story long write
长篇网文写作,从选题、大纲到逐章正文和持续追踪。
/story-review
Story review
多视角小说审查;ZCode 项目 agents 不可用时自动降级 solo。
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