LLM Mart Basic
@llm-mart · Joined Jun 2026
Set up Zuke — a code-first, strongly-typed build automation system for Deno/TypeScript — in a project. Use when the user wants to add Zuke to a repo, scaffold a zuke.ts build file, install the Zuke CLI, or bootstrap the ./zuke launcher. After scaffolding, switch to the zuke-write
Write or edit a Zuke build (zuke.ts) — the code-first, strongly-typed build system for Deno/TypeScript. Use when adding or changing targets, wiring dependencies, calling a tool wrapper (DenoTasks, NpmTasks, DockerTasks, ...), generating CI, or authoring/refactoring a zuke.ts buil
网络小说工具箱主入口。根据用户需求自动路由到对应 skill,并可管理作者习惯、启动本地 Dashboard。触发方式:/story、$story、/story dashboard、/网文、「我想写小说」「记住我的写作习惯」「打开工作台」「检查更新」。
长篇网文拆文。深度拆解爆款长篇小说的黄金三章、人设架构、爽点设计、节奏控制。单一深度拆解管道:跑完黄金三章(Stage 1)后产出快速预览报告并询问是否继续全量拆解,确认后从 Stage 2 续跑逐章摘要、聚合分析、设定关系、汇总报告,全程产物落盘 拆文库/{书名}/。触发方式:/story-long-analyze、/长篇拆文、「帮我拆这本书」「拆这本书」「分析黄金三章」「深度拆解」「完整拆解」「系统拆解」或提供小说文本文件路径——全部进入同一管道。
长篇网文写作。从大纲到正文,辅助长篇网络小说的创作,包括世界观、人物、情节线管理。触发方式:/story-long-write、/写长篇、「帮我开书」「写大纲」「日更」「续写」「继续写」「修改第X章」「回炉」「重写第X章」。
短篇网文拆文。拆解爆款短篇小说(番茄短篇 / 故事会 / 知乎盐选 / 追妻 / 世情 / 重生 / 虐渣等通俗题材)的故事核、结构、情感线、反转设计、写作手法、共鸣层次。单一全量拆解管道:跑完 Stage 2-6 产出完整拆文报告,落盘到 拆文库/{书名}/,下游 story-short-write 同时读拆文报告 + 情节节点 + 写作手法 + 原文 + _meta.json 写下一篇。触发方式:/story-short-analyze、/短篇拆文、「拆短篇」「拆这篇短文」「短篇拆文」「精细拆解短篇」「8000 字短篇拆解」「番茄短篇拆文」「故事会拆
短篇网文写作。辅助短篇小说创作,从构思到成稿,聚焦情绪拉扯与节奏把控。触发方式:/story-short-write、/写短篇、「帮我写一篇短篇」「写个盐言故事」。
网文去AI味。检测并清除文本中的AI写作痕迹,让文字回归自然、非模板化。触发方式:/story-deslop、/去AI味、「去AI味」「这篇太AI了」「网文去AI味」。
Use this skill when you need to control a Chrome browser via CDP (Chrome DevTools Protocol) to reuse existing login sessions. Covers: launching Chrome in debug mode, opening URLs, waiting for page load, evaluating JavaScript, taking snapshots, and extracting auth tokens. Trigger
网文写作工具集基础设施部署。为 Claude Code / OpenCode / Codex / ZCode / OpenClaw / Reasonix 提供内置适配;Web AI / 通用 Agent 可走 skills + AGENTS.md 文件模式。触发方式:/story-setup、$story-setup、「准备写书」「帮我搭一下环境」「配置写作项目」。
多视角对抗式审查。full/lean 模式在已部署 reviewer agents 时并行 spawn;缺失/异常 agents 或 spawn 失败时自动降级 solo,参考文件不可读时使用内置 rubric fallback。触发方式:/story-review、/审查、「审查一下」「帮我审一下」。
小说封面生成。根据书名、作者名自动分析题材风格,调用 GPT-Image-2 生成含标题和署名的专业级网文封面;Codex CLI 优先使用内置 ImageGen,无需单独 API Key。触发方式:/story-cover、/封面、「帮我做个封面」「生成封面图」「做个小说封面」「封面设计」。
章节摘要与情节点提取专家。接收单章文本,输出结构化摘要、情节点列表、角色提及。 被 story-long-analyze(拆解管道 Stage 2)按章节并行调用。 输出格式严格遵循本文件「输出格式」章节;不依赖外部输出模板文件。
角色设计与对话创作专家。负责角色设定、语言风格档案、动机链、人物弧线、 对话质量、角色关系设计。被 story-long-write(Phase 2,4)和 story-short-write(Phase 2,3)调用。 也可审查角色一致性和对话质量。
事实一致性与伏笔状态检查专家(只读)。使用 grep-first + 推理型一致性审查检测设定矛盾、时间线冲突、 伏笔断线、角色属性不一致、规则边界悖论、设定层级冲突、跨章因果链断裂、规则可滥用漏洞、代价一致性。输出 S1-S4 分级冲突报告。 被 story-review、story-long-write(Phase 5)、story-short-write(Phase 4)调用。 不做任何创作判断。
叙事文本创作与去AI味专家。负责正文写作(三维度揉进、感知/反应)、 情绪弧线执行、开篇/收尾、去AI味(禁用词替换、句式去套路、节奏调整)。 被 story-long-write(Phase 4-5)和 story-short-write(Phase 3-4)调用。 也可执行完整去AI味流程和格式合规检查。
故事架构与世界观创作专家。负责题材选择、核心梗设计、世界观构建、大纲排布、 钩子/悬念/反转等叙事工程、情绪弧线设计、范围控制审查。 被 story-long-write(Phase 1-3)、story-short-write(Phase 1-2)调用。 也可审查已有内容的结构问题。
故事项目结构化查询 agent(只读)。响应关于角色状态、伏笔进度、设定出现位置、 时间线节点、写作进度的查询。使用 grep + read 从项目文件系统中检索信息, 返回结构化 JSON 摘要。 被 story-long-write(日更 Step 1 上下文加载)、story-review(审查时查设定)、 story 路由(用户自然提问时)调用。 不做任何创作判断或修改。
小说写作资料研究 agent。接收研究查询,优先使用 CDP (agent-browser) 搜索并提取完整正文, WebSearch/webReader 作为兜底。输出带来源引用的结构化 Markdown 参考文件。 被 story-long-write(Phase 4)、story-review、story skill 路由调用。
章节摘要与情节点提取专家。接收单章文本,输出结构化摘要、情节点列表、角色提及。 被 story-long-analyze(拆解管道 Stage 2)按章节并行调用。 输出格式严格遵循本文件「输出格式」章节;不依赖外部输出模板文件。
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.
/generate-idl-client
Generate idl client
Generate a typed client from an Anchor or Shank IDL (Codama or Anchor TS)
/migrate-web3
Migrate web3
Migrate TypeScript from @solana/web3.js 1.x to @solana/kit
/plan-feature
Plan feature
Plan a Solana feature before coding: accounts, PDAs, instructions, risks, tests
/product-review
Product review
First-time-user product review: scorecard and fix roadmap; --harsh for a roast
/profile-cu
Profile cu
Measure compute units per instruction and flag the expensive ones
/quick-commit
Quick commit
Format, lint and commit with a conventional message on a kit-named branch
/resync
Resync
Resync external skill submodules to latest upstream versions
/scaffold
Scaffold
Scaffold a Solana project (Anchor, fullstack, frontend, Pinocchio) with the kit
/setup-ci-cd
Setup ci cd
Set up GitHub Actions CI for Solana programs: lint, build, test, audit
/setup-mcp
Setup mcp
Configure MCP server API keys in .env and add the optional MCP servers
/test-and-fix
Test and fix
Run tests, auto-fix fmt and lint, and fix failures until green or stuck
/test-dotnet
Test dotnet
Run C# tests: Unity Test Framework in batchmode, or dotnet test
/test-rust
Test rust
Run Rust tests for programs (LiteSVM, Mollusk, Surfpool, Trident) and backends
/test-ts
Test ts
Run TypeScript tests for programs (Anchor TS, Kit) and dApp frontends
/update
Update
Update solana-ai-kit to latest version from upstream
/write-docs
Write docs
Write docs for a Solana program, SDK or component from its code and IDL
/a
A
Allow all file creation (short for /ar:allow)
/afa
Afa
Set AutoFile policy to allow-all mode (full file creation permissions)
/afj
Afj
Set AutoFile policy to justify-create mode (require justification for new files)
/afs
Afs
Set AutoFile policy to strict-search mode (only modify existing files)
Make any song you can imagine
39 views 0 likesLeading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars
37 views 0 likesHermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research
36 views 0 likesKilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster
34 views 0 likesGeneral-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…
20 views 0 likesAutonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.
20 views 0 likesTSP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
15 views 0 likesCurated, verified Agent Skills powered by ModelStudio.
18 views 0 likesRun Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…
17 views 0 likespi 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…
14 views 0 likesA persistent workspace for development work that self-improves and continues beyond one session.
33 views 0 likesOpen-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.
20 views 0 likes📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…
28 views 0 likesDeterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.
31 views 0 likesDeterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…
20 views 0 likesNative Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…
32 views 0 likesAgent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.
15 views 0 likesGit for agent memory. Branches, diffs, PRs, and rollback for what your agents know.
34 views 0 likesMulti-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…
16 views 0 likesProduction-grade MCP server for MikroTik RouterOS with secure AI-native network automation.
29 views 0 likes