LLM Mart Basic

Запускает маркетинговую кампанию от начала до конца — анализ продаж, контент-бриф, генерация макетов, постановка рассылки в очередь. Принимает необязательные аргументы периода и канала. Командная форма: вызывается по имени.

Выносит топовых и слабых продавцов, находит сезонные паттерны и собирает двухнедельный контент-бриф, чтобы продвигать лидеров и распродавать залежавшееся. Принимает необязательное окно обзора 30, 60 или 90 дней. Командная форма: вызывается по имени.

Claude как наставник. Проводит собственника малого бизнеса через подключение первых двух инструментов, запускает один рецепт, чтобы сразу показать пользу, расспрашивает о бизнесе (сфера, размер, три главные головные боли), сохраняет этот контекст в память, чтобы им пользовались в

Парадная дверь плагина для малого бизнеса. Слушает, что владельцу нужно прямо сейчас — расплывчато или конкретно — и направляет к лучшему скиллу или команде для момента. Ещё и проводник: объясняет, что доступно, подсказывает, что попробовать дальше, и подстраивает рекомендации по

Проактивный налоговый штурман для ИП и малого ООО. По 3-5 фактам о бизнесе (форма, режим, примерный оборот, сотрудники) сам строит персональный налоговый календарь: что горит, когда срок, сколько примерно платить, и заранее предупреждает о приближении к НДС-порогу и лимиту УСН. Н

Готовит материалы к налоговому периоду — расчёт авансового платежа по УСН, учёт выплат подрядчикам (ГПХ/самозанятым), страховые взносы ИП «за себя» или предупреждение про НДС на УСН — и собирает пакет для передачи бухгалтеру. Принимает необязательные аргументы режима и года. Кома

Готовит материалы к налоговому периоду для собственников малого бизнеса на УСН и НПД: это пакет для бухгалтера, а не налоговая консультация. Четыре режима: авансовый платёж по УСН (доходы нарастающим итогом, ставка объекта «Доходы» 6% или «Доходы минус расходы» 15%, минимальный н

Читает пересланное письмо или обращение клиента, подтягивает статус заказа и оплаты из платежей и историю клиента из CRM, готовит ответ в тоне и голосе владельца, а при необходимости — оформляет возврат с явным подтверждением владельца. Триггеры: «подготовь ответ», «ответь этому

生成 B 站创作者「黑鸦」风格的视频标题：长标题、强情绪、多事件合并。适用于用户要求黑鸦风格，或希望把新闻、科技、游戏、娱乐等内容改写成有冲击力的中文标题。

Darwin Skill 2.0 (达尔文.skill 2.0): autonomous skill optimizer, v2.0 integrates Microsoft Research SkillLens (arXiv 2605.23899) 9-dim rubric + SkillOpt (arXiv 2605.23904) validation-gated design + human-in-the-loop checkpoints. Evaluates SKILL.md files using a 9-dimension rubric (s

Audit a site's Cross-Origin Resource Sharing (CORS) configuration for misconfigurations — wildcard origin with credentials, reflected arbitrary Origin, the 'null' origin, overly broad allowed methods, and risky credentialed CORS. Use when the user asks to "check my CORS config",

Audit project dependencies for known-vulnerable versions and risky pinning. Parses requirements.txt and package.json, matches a bundled offline advisory DB, optionally queries OSV.dev live, and warns about unpinned versions. Use when the user asks to "check dependencies for vulne

Audit a website's HTTP security headers and cookie flags — CSP, HSTS, X-Frame-Options, X-Content-Type-Options, Referrer-Policy, Permissions-Policy, COOP/COEP, version-leaking banners, and Secure/HttpOnly/SameSite cookies. Use when the user asks to "check my site's security header

Decode and security-audit a JSON Web Token — flag alg=none, missing/excessive expiry, symmetric-alg confusion risk, missing claims — and attempt an offline HMAC secret crack against a wordlist to detect weak signing keys. Use when the user asks to "decode this JWT", "is this toke

Static security analysis for Python source via AST walking — finds command injection, insecure deserialization, eval/exec, weak crypto, SQL injection, disabled TLS verification, hardcoded secrets and more, each tagged with a CWE. Use when the user asks to "audit this code for vul

Start robotics apps or demos from compatible examples for mapping/navigation, robot assistants, or pretrained manipulation. Choose a stack if none fits; not existing-app maintenance.

Deploy and debug headless robotics containers on Google Cloud Run.

Choose and structure training data for robot-learning projects.

Set up reproducible robotics environments with uv, Docker, or GPU hosts.

Visualize live or recorded ROS robot data remotely with Foxglove or Lichtblick.

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.

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.

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

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