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.

Audit the rules/ directory for missing foundational principles; output gap list with priority and justification

Validate ~/.claude/settings.json hooks block — event names, file existence, executability, matcher syntax; --fix repairs common issues

Catch Resend-class bug (isError: false on HTTP 4xx/5xx) across all MCP server tool handlers

Healthcheck + drift detect + rotation-reminder across all MCP servers in ~/.claude/mcp-registry.json

Catch mock/live divergence in MCP eval golden tests (anti-pattern #2 from eval-mock-mode-discipline)

Catch the github-mcp class of bug — CallTools handlers that exist but are invisible to Claude because ListTools never advertises them (orphaned), or ListTools entries that have no handler (zombies)

Validate _router.md — check every referenced skill file exists; surface stale entries + orphan files; --fix prunes or stubs

List every active tool across all MCP servers and flag cross-MCP duplicates and semantic overlaps

Scaffold a new spawnable specialist agent def and register it in the agent taxonomy

Audit whether user-visible changes in the current session have matching CHANGELOG.md entries; report MISSING with suggested lines; --fix auto-appends

Repeatable pass upgrading an Angular admin dashboard into a compact black-and-cyan developer-cockpit PWA

Deploy an MCP server generated by forge-from-openapi --target=mcp-server; detect transport, deploy, smoke-test, print .claude.json snippet

Run the drift-detection checklist (incl. agent-drift signals); report + fix in-turn

Execute a PRP — TodoWrite breakdown, parallel implementation, validate every gate, deploy, prove on prod

Orchestrate the final review fan-out (integration + diversity + risk + release readiness)

Auto-generate a Claude Code skill (commands + types + client) from any OpenAPI 3.x spec URL or file path

Scaffold a complete Claude Code skill (commands + types + client) from a GraphQL endpoint or local schema file

Scaffold a complete OAuth2 callback + init Hono route pair (code exchange, PKCE, KV token storage) for a named provider

Scaffold an Amazon-style working-backwards press release for any feature, in Brian's voice. Outputs to docs/decisions/PR-{slug}.md and prints to stdout.

Vendor a third-party skill repo/URL into the owned layer — clone, compress to house style, cross-link, commit — in one keystroke

The fastest way to put Volcengine Ark in your terminal and your AI agent — go from prompt to generated media, multimodal answer, or deployed endpoint in a sin…

本地私有、开源的自进化跨平台 AI 内容发现 Agent：先理解你，再主动从 B站、小红书、抖音、YouTube、X、知乎、Reddit、微博等平台与开放 Web 寻找内容。（支持 deepseek harness 插件） | Local-first open-source cross-platform AI cont…

Persistent memory for AI coding agents — one verified kb_search replaces the grep/find/ls orientation loop. Cross-repo, CPU-only, zero token spend.

AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Co…

The batteries-included, No-Code FinOps automation platform, with the AI you trust.

Open-source 3D AI agent framework — GLB/glTF avatars with LLM brains, memory, emotions, and autonomous payments. MCP server · x402 · Solana/EVM · Three.js. Embe…

XLSX parser for LLMs, RAG, LangChain, LangGraph, CrewAI, Claude, MCP — turns Excel (.xlsx) into citation-ready JSON with formulas, charts, dependency graphs, an…

Hermes-Relay — Your Hermes AI agent, in your pocket — chat, voice, and control.

A minimalist, terminal-native coding agent written in C.

AI-powered OSINT agent with interactive REPL, MCP server, and CLI. 19 tools. Works with Claude, GPT-4, or local models. For authorized security research only.

AI pair programming in your terminal — one static binary, sub-ms startup, any model

Where data access meets operational intelligence

Build your own security agents. Open-source framework for agents with live, read-only access to your infrastructure, with no path to widen it. Reasons across AW…

Multi-workspace terminal aggregator with Claude Code AI integration

Go implementation of AI coding agent

Harness engineering beginner tutorial, from 0 to 1

Generate images directly in DeepSeek Harness chats

A smarter, self-hosted AI assistant — multi-user, multi-agent.

Turn any research paper into a commercialization report — 6 AI agents, TRL/MRL scoring, patent landscape, market intelligence, verified citations. DeepSeek / Op…

Power BI CLI - semantic models (.NET TOM) and PBIR reports for token-efficient AI agent usage, built for Claude Code