LLM Mart Basic

Use in pre-implementation (idea-to-design) stages to understand spec/requirements and create a correct implementation plan before writing actual code. Turns ideas into a fully-formed PRD/design/specification and implementation-plan. Creates design docs and task lists in docs/feat

Compare two versions of a skill's instructions to detect degradations and complexity increases. TRIGGER when: user asks to diff, compare, or review changes to a skill's markdown instructions. Asymmetric check — only regressions count. Additions, clarifications, and strengthenings

After implementing a new feature or fixing a bug, make sure to document the changes. Use when writing documentation, after finishing the implementation phase for a feature or a bug-fix.

TRIGGER when: user asks to implement, fix, build, or work on something — whether from a docs/feat/wip plan OR a standalone task (bug fix, GitHub issue, one-off change). Examples: "work on task 1", "fix this bug", "implement feature X from the issue". Provides structured execution

Compare and merge two design docs for the same feature into a single source of truth. Use when you have competing or complementary design/implementation docs (e.g. from separate design runs) that need reconciling into one unified document.

Produce or update a domain-reference kit — the durable glossary + divergences/traps pages for a bounded context. Use for domain modelling, information architecture, building a domain glossary or domain model, mapping domain concepts to code (bindings), or surfacing the decidable

Apply Chain-of-Verification (CoVe) prompting to improve response accuracy through self-verification. Use when complex questions require fact-checking, technical accuracy, or multi-step reasoning.

TRIGGER when: adding or upgrading any dependency — library, SDK, framework, API, IaC API version (K8s/Terraform/Helm), CRD, or container image. Use BEFORE writing the call. Forces context7/capy lookup instead of guessing.

Use in pre-implementation (idea-to-design) stages to understand spec/requirements and create a correct implementation plan before writing actual code. Turns ideas into a fully-formed PRD/design/specification and implementation-plan. Creates design docs and task lists in docs/feat

Compare two versions of a skill's instructions to detect degradations and complexity increases. TRIGGER when: user asks to diff, compare, or review changes to a skill's markdown instructions. Asymmetric check — only regressions count. Additions, clarifications, and strengthenings

After implementing a new feature or fixing a bug, make sure to document the changes. Use when writing documentation, after finishing the implementation phase for a feature or a bug-fix.

Compare and merge two design docs for the same feature into a single source of truth. Use when you have competing or complementary design/implementation docs (e.g. from separate design runs) that need reconciling into one unified document.

Produce or update a domain-reference kit — the durable glossary + divergences/traps pages for a bounded context. Use for domain modelling, information architecture, building a domain glossary or domain model, mapping domain concepts to code (bindings), or surfacing the decidable

Designs, reviews, revises, and templates deployable system prompts for agent projects. Use whenever the user asks to write, improve, review, or debug an agent's system prompt, system message, or role/boundary instructions — including Chinese requests such as 系统提示词、角色设定、角色和边界规范、提示

Делает одностраничный сводный снимок бизнеса для собственника — позиция по деньгам (бухгалтерия), тренд продаж (платежи), движение по воронке (CRM), обязательства недели (календарь), срочный список наблюдения (почта, мессенджер) и единственное самое важное на сегодня. Сам пробует

Ранжирует топ-5 лидов, которым стоит позвонить сегодня, готовит тезисы разговора из истории переписки, бронирует время в календаре и набрасывает follow-up сообщения. Принимает необязательные аргументы количества и даты. Командная форма: вызывается по имени.

Берёт согласованный контент-бриф и выполняет кампанию от начала до конца: строит календарь публикаций, генерирует макеты для постов в соцсетях через ~~дизайн (VistaCreate, Supa, Поликрафт), пишет тексты подписей и писем, ставит публикации в очередь через ~~crm. Макеты делаются то

Берёт дебиторку и кредиторку, историю сроков поступления денег и известные постоянные расходы из бухгалтерии (1С, МойСклад) и платёжных сервисов (ЮKassa, Тинькофф, банк-выписка) — или из выгрузки CSV — и строит прогноз денежного потока на 30/60/90 дней с доверительными коридорами

Закрывает месяц — сверяет данные бухгалтерии с эквайрингом и выписками, помечает расхождения, пишет ОПиУ-сводку, выгружает пакет закрытия. Принимает необязательные аргументы месяца и места сохранения. Командная форма: вызывается по имени.

Анализирует данные о продажах из ~~платежи и ~~бухгалтерии (ЮKassa, 1С, МойСклад), находит хиты и зависшие позиции, накладывает сезонность и выдаёт приоритизированный контент-бриф на 30 дней: что продвигать, какие акции запускать, что придержать. На выходе только стратегия — без

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 MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

`crabbox attach` follows the recorded events of an active coordinator run and

`crabbox azure` groups Azure provider setup commands. It currently has a single

`crabbox bench` records and reports local benchmark timing observations. It is a

`crabbox cache` inspects, purges, or warms package and build caches on a

`crabbox capsule` captures, replays, and tracks lightweight failure capsules.

Save the state of a lease, then restore it onto another box or fork it into a

`crabbox claims list` prints the lease claims stored on the current machine. It

`crabbox cleanup` sweeps direct-provider machines and local provider state that

`crabbox code` bridges a Linux lease's `code-server` workspace into the

`crabbox config` inspects and updates user configuration. It has three

`crabbox connect` resolves a lease and opens an interactive SSH session to it.

`crabbox cp` copies files or directories between the host and a Crabbox-owned

`crabbox desktop` drives a visible desktop session on a lease that was warmed

`crabbox doctor` runs a preflight before you commit to a long workflow. It is

`crabbox egress` gives a lease mediated outbound network: a lease-local browser

`crabbox events` prints the broker's event log for a recorded run.

`crabbox heartbeat` refreshes the idle deadline for one owned lease and prints

`crabbox history` lists recorded remote command runs from the broker. Each run is

`crabbox image` holds the trusted-operator controls for provider base images:

`crabbox init` onboards the current repository: it writes the minimal config

Paper trading simulator for Polymarket — built for AI agents. MCP server, live order books, strategy backtesting. Install: npx clawhub install polymarket-paper-…

An SSH tool dedicated to addressing all pain points · (macOS/Windows/Linux/Android/iOS)

The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxe…

SmartLabel AI 2026: Auto-Annotate Any Object via LLM-Powered Prompt Parsing

Local-first visual generation runtime and studio for people and coding agents, with reproducible image and video workflows across multiple providers.

Scholar All-In-One: A research infrastructure for AI agents

Give your AI agent a real browser — with a human in the loop. Open-source MCP-native browser agent.

同花顺免费开源AI插件FQGate-agent（原插件名 tonghuasun-agent）：为 Codex、Claude Code、DeepSeek 等 AI 工具提供本机 A 股实时行情、K 线、Level-2、资讯、账户查询与可选交易能力。

A non-linear AI agent workbench — session is a tree: branch anytime, and context follows the branch

Production-grade AutoCAD MCP server for AI agents — 122 tools, dual COM (live AutoCAD) + headless ezdxf engines, ISO GD&T and dimension-tolerance validation for…

A DeepSeek coding agent harness: persistent shell, Ultra subagents, auto approval, Chrome MCP and session telemetry

Waku Waku! Waku Agent is a local-first AI agent harness you actually own, including loop, memory, eval, all in code built to stay legible as it grows.

Remote control for Claude Code, Codex, Grok, and Cursor on Mac or PC. View sessions, send tasks, and drive them remotely from your phone, PIN, or Ring. OpenClaw…

Next-gen AI-native server ops panel with an in-workspace SRE agent. Crash self-healing, safe rollbacks, Docker/game servers, and local Ollama support.

Professional cloud architecture diagrams with official AWS, Azure and GCP icons, from Terraform code or a plain JSON graph. MCP server + agent skill.

A ready-to-use self-growing desktop AI assistant for long-running tasks, memory, agents, tool reviews, MCP, and high-concurrency workspace automation. / 开箱即用的自我…

Collection of templates using the Alchemyst AI Platform for your next big AI app.

Fast, exact LLM decoding on Apple Silicon (MLX) behind an OpenAI-compatible endpoint

The open source AI research agent.

Open-source agent-native visual production workspace where humans and coding agents edit the same live canvas — local-first, BYOK image/video models.