LLM Mart Basic

Use when "launch plan", "go-to-market", "GTM strategy", "how to launch", "launch checklist", "growth plan", or product is built and needs distribution strategy. Do NOT use for content generation (/content-gen) or SEO audit (/seo-audit).

Use when "privacy policy", "terms of service", "legal pages", "GDPR", "CCPA", "app store legal", or project needs compliance documents. Do NOT use for NDA or contracts.

Use when "audit memory", "check CLAUDE.md", "memory map", "rules audit", "context budget", "what loads in my session", or need to optimize agent context loading.

Use when "set up metrics", "track KPIs", "PostHog events", "funnel analysis", "when to kill or scale", "success metrics", or need analytics plan. Do NOT use for SEO metrics (/seo-audit).

Take a trained neural model to devices — ONNX export, int8 quantization, Core ML conversion, on-device benchmarking, download-on-demand delivery. Use when user says "сожми модель", "quantize the model", "convert to Core ML / ONNX", "model is too big for the app", "run the model o

Use when "run pipeline", "automate research to PRD", "full pipeline", "research and validate", "scaffold to build", "loop until done", "chain skills", or need multi-skill automation. Do NOT use for single skills (use the skill directly).

Use when "plan this feature", "create implementation plan", "write a spec", "battle plan", describing a feature/bug/refactor, or need task breakdown before building. Do NOT use for idea validation (/validate) or execution (/build).

Use when "reddit comment", "engage reddit", "build karma", "post to reddit", or need to participate in Reddit threads. NOT for thread discovery (/community-outreach) or social copy (/content-gen).

Use when "research this idea", "find competitors", "check the market", "domain availability", "market size", "analyze opportunity", or need evidence before validation. Do NOT use for idea scoring (/validate) or SEO auditing (/seo-audit).

Use when "retro", "evaluate pipeline", "what went wrong", "pipeline review", "check pipeline logs", or after pipeline completes and needs quality assessment.

Use when "review code", "quality check", "is it ready to ship", "final review", or after /build or /deploy completes. Do NOT use for planning (/plan) or building (/build).

Use when "scaffold project", "create new project", "start new app", "bootstrap project", "set up from PRD", or need project from PRD + stack template. Do NOT use for planning features (/plan) or PRD generation (/validate).

Use when "check SEO", "audit this page", "SEO score", "check meta tags", "SERP position", or need website SEO health check. Do NOT use for landing content (/landing-gen) or social media posts (/content-gen).

Use when "set up workflow", "configure TDD", "wire up dev workflow", or after /scaffold before /plan to generate workflow config. Do NOT use for founder setup (/init) or scaffolding (/scaffold).

Use when "design schemas", "structured output", "agent loop", "SGR", "constrained decoding", "tool dispatch", "Pydantic schema for LLM", or need to design a schema-guided reasoning pipeline for an agent or API. Do NOT use for general code review (/review) or planning (/plan).

Use when "audit skill", "review skill quality", "check skill", "skill score", "skill checklist", "is this skill good", or evaluating skill against best practices. Do NOT use for KB audits (/audit) or code review (/review).

Use when "help me decide", "should I do this", "evaluate decision", "STREAM analysis", "run decision framework", "pros and cons", or facing a high-stakes founder choice. Do NOT use for idea validation with PRD (/validate).

Use when "swarm research", "parallel research", "investigate fast", "3 agents", "team research", or want faster multi-angle alternative to /research. Do NOT use for solo research (/research) or idea scoring (/validate).

Build and hold a SwiftUI design system — a 12-column grid, spacing/type/radius/motion scales, surface levels, a component gallery, and the guards that stop it drifting back. Use when the user says "сделай по сетке", "дизайн-система", "разъезжается вёрстка", "магические числа в pa

Use when "validate idea", "score this idea", "should I build this", "go or kill", "generate PRD", "evaluate opportunity", or need idea scoring with PRD output. Do NOT use for deep research (/research first) or decision-only framework (/stream).

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.

Update implementation documentation including specs, status, and best practices

Use structured stepper approach for problem-solving and project development

Write unit and integration tests

Developer agent — implements features based on technical design, follows TDD patterns, and produces clean, tested code

Autonomous iteration loop — reads progress, selects role, executes, verifies, commits, and moves to next task without waiting

Pair programming mode — step-by-step collaboration with 5 confirmation checkpoints for learning and sensitive operations

Product Manager agent — analyzes requirements, creates REQ documents, and breaks down features into actionable items

Configure claude-hud as your Claude Code statusline

Grade this repo's CLAUDE.md / AGENTS.md (0–100) and return a worst-first fix list

Scaffold a CLAUDE.md for this repo from battle-tested templates, filled in with the project's real commands

Prompt optimizer — rewrite this request into an optimized prompt (ultrathink), then carry it out

Configure codex-hud statusline display options (guided interactive flow)

Show last 30 days Codex cost breakdown

Show today's Codex cost breakdown

Show last 7 days Codex cost breakdown

Configure or update the OpenAI Admin API key (enables /codex-hud:costs-*)

Install codex-hud statusline (automatic, idempotent)

Quick one-line summary of today's Codex activity (cost shown if Admin key configured)

Remove the codex-hud statusline integration (restores your previous statusline)

Показать состояние гейта качества 1С — какие файлы ждут проверки

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-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…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP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

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi 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…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.