LLM Mart Basic

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

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。

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.

Use the bundled `skillopt-sleep` skill to run or manage SkillOpt-Sleep for the

Git + worktree orchestrator entry point. /git-ops --landall surveys every branch/worktree and batch-lands the ones that are done; bare /git-ops runs a status survey. Thin router over the git-ops skill.

Save session state - persist tasks (via TaskList), plan content, and git context. Complementary to /sync.

Session bootstrap - read project context, restore saved state, show status. Quick orientation with optional deep dive.

Query AI Gateway models (list, filter by provider/tag, get details)

Search for icons by name, or identify a PUA character

Install a pinned skill extension on demand (/add-skill <id>), or list core packs and extensions

Implement an approved plan or issue in its own worktree, run the gate, open the pull request.

Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.

Write the repository handoff file for the next session, and record any durable learning.

Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.

Turn a topic or issue into a plan the reviewer approves in the native plan pane.

Answer a research question with parallel read-only gatherers and one synthesized digest.

Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.

Run ad-hoc PostgreSQL analytics queries against dev/test database

Find and report technical debt in the codebase

Refreshes local project state from a linked Supabase project or branch in one step, instead of running `config pull`, `db pull`, `migration fetch`, and `functions download` individually. It runs four steps, always in this order: pull config into `supabase/config.toml`, optionally

Send one of the user's own Minutes meetings to their X1 household for review. Use when the user wants a meeting's summary, decisions, action items, and open questions to reach X1 so they can confirm what belongs in their household record. X1 asks the user to approve the send, and nothing reaches the household record until they confirm each item. Never use it for a restricted meeting, a transcript, or someone else's meeting.

Send one of the user's own Minutes meetings to their X1 household for review. Use when the user wants a meeting's summary, decisions, action items, and open questions to reach X1 so they can confirm what belongs in their household record. X1 asks the user to approve the send, and nothing reaches the household record until they confirm each item. Never use it for a restricted meeting, a transcript, or someone else's meeting.

> **Usage:** Create a new skill from the template.

PiG (Pi in Go) is a faithful Go port of upstream Pi, the TypeScript codebase behind the Pi coding agent. It is a parity-bound translation, not a rewrite: upstre…

An AI Agent that lives in your pocket. Local-first and privacy focused.

Unofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.

Adaptive Test-time Learning and Autonomous Specialization

Prediction-market trading engine — Wang Transform pricing on 291K+ contracts; paper-traded across Kalshi · Polymarket · Solana DFlow (Jito bundles) · 633 tests

Knowledge Management for Humans and Agents

Open-source Claude Cowork / Codex / WorkBuddy alternative — a local-first AI office agent that turns one request into real PPTX, DOCX, XLSX and HTML files. Runs…

DeepAgent Code: AI coding agent with persistent memory and control plane

Awesome Jev — evidence-graded index of TypeSafe System One: SDKs, MCP tools, agents, apps and open models. 20 languages, rebuilt every 2 hours.

CLI for Telegram — agent-friendly, daemon-based, with webhook event push.

AI deep-research agent that turns any question into a cited report: plans searches, reads real sources, verifies evidence. Self-hosted, multi-provider, Docker-r…

Event-stream AI Agent framework for building your persona bot 🍊

Give the agent a machine. Just not yours. Each AI coding agent gets its own isolated machine with root, Docker, and systemd - active defense detects and stops t…

Local Emperor-style AI agent with Vue WebUI, multi-provider LLMs, streaming chat, tools, skills, memory, and token telemetry.

Open-source AI reverse-engineering agent platform and MCP server for Ghidra, Frida, x64dbg and Rizin — automated PE/APK/binary analysis, CTF and malware researc…

"Never send a human to do a machine's job" - Open Source AI hacking agent

Prismer Cloud

My Personal Blog (Robotics)

Tau Coding Agent - like Pi, but twice as much

Open-source alternative to OpenAI Dots: self-hosted AI chat, tools, approvals, connectors, and computer tasks.