LLM Mart Basic

Build a whole course on a subject, from scratch, on disk. A light survey of the domain, then the placement-quiz decision, then a deep multi-agent research pass that becomes an ordered taxonomy, a table of contents grouped into books and chapters, and a course folder that teaches

Placement quiz that finds someone's real level in a subject and writes it to PROFILE.md. Scenario questions in small batches, never definitions, with neutral options that cannot be eliminated by tone, plus self-report checks that separate knowing a word from being able to act on

Make a fig. A single looping animated SVG, one self-contained HTML file you can drop in an email or a slide. Use it when an idea moves (flows, loops, retries, queues, fan-outs). Faster than a paragraph, livelier than a static diagram. No player, no deck.

Search and fetch free, licensed stock images from the internet (Pexels, Pixabay, Unsplash, Openverse, Wikimedia Commons). Two jobs: add optimized WebP images to sites, blogs, and docs, or show a fitting photo right in the chat while answering about a topic. Use when the user want

Run a conservative, end-to-end art-direction photo pass over a whole website: audit where photos genuinely earn their place, define one visual language, source free images, melt them into the design, verify in both themes, and record credits. Use when the user asks for a "photo p

Use the Open Design content library: 151 design systems with real tokens (Apple, Vercel, Linear, Stripe, Notion, GitHub, Raycast, plus styles like brutalism and claymorphism), 71 design and frontend skills, and 114 rendering templates for decks, documents, video frames, and socia

Apply first-principles thinking and design-thinking to product, architecture, and communication decisions. Use this skill whenever the user is framing a problem, choosing between alternatives, debating a tradeoff, questioning a design, adding scope, or saying "should we…" / "that

Delegates one self-contained coding or research task to the Cursor CLI (cursor-agent), running it on the Cursor subscription's quota instead of Claude's. Use when the user asks to "delegate to Cursor", "offload this to cursor-agent", "have cursor do it", or wants to spend idle Cu

Writes one ready-to-teach chapter file for a learnable course from its brief: every lesson's opening question with plausible options, the correction, the plain-language explanation, the terms with their origins, and the end-of-chapter quiz. Use one per chapter when writing a book

Designs one track of a learnable curriculum: its chapters, its lessons, each lesson's hard opening question, the misconception it kills, its key terms and its teaching angle. Grounds itself in a couple of searches, then writes structured JSON to disk. Use one per track when build

Power search via Exa MCP. Modes: quick, deep research, code, docs, debug, news, compare. Use when searching the web, finding docs, debugging errors, or researching any topic.

Author a product brief by interviewing the user, then emit user stories, scope, success metrics, and a derived task list. Triggers on "write a brief", "create a brief", "spec this feature", "brief". A brief is a product spec (what/why), NOT a technical design (use propose) and NO

Design workflow in the RFC tradition. Forces reasoning before action: problem → alternatives → tradeoffs → design → risks → recommendation → impl plan. Two sizes with hard ceilings: one page for a bounded choice, a few pages for a real design question. Use when user says "propose

Execute a predetermined spec. Ingests a finalized brief (docs/brief/<slug>/ with brief.md status ready + tasks.md) or an Accepted propose (PROPOSAL.md), locks a definition-of-done contract, implements it on the strongest available engine (agent-teams / subagents / solo, with ultr

Report unfinished brief/propose/ship work in this repo and the exact command to resume each, ranked by what to do now. Use when the user asks "what's next", "what's left", "where do I resume", "/next", "la suite", or to re-orient after a context reset. Reads artifact frontmatter

Use GitHub issues as persistent cross-session resolution memory. Create, update, and re-read issues that are self-contained and re-readable cold, recording the hypothesis and the resolution. Triggers on "track this in an issue", "create an issue I can resume", "resume issue", "is

Read or hand-write the project progress ledger (.claude/trace.md). Use when the user says "/trace", "what did I do", "log this", "trace done", or wants to record or review what moved this session. The automatic Stop hook already logs file changes; this skill is the reader and the

Performs comprehensive, multi-layered research on any topic with structured analysis and synthesis of information from multiple sources. Use when the user needs thorough investigation, market research, technical deep-dives, due diligence, or comprehensive analysis on any subject.

Guides AI agents in using Tree Ring Memory for durable recall, project decisions, user preferences, warnings, future seeds, privacy-safe memory capture, and lifecycle-aware forgetting.

Guides AI agents in using Tree Ring Memory for durable recall, project decisions, user preferences, warnings, future seeds, privacy-safe memory capture, and lifecycle-aware forgetting.

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.

What do I know about a topic

Find and add missing connections

Audit structure and repair what is mechanical

Merge two pages

Record a dated metrics snapshot

The monthly structural review

Find unreachable pages

Outline a piece from your concept pages

Audit what should not be in the vault

Where a project stands

Create a project

Find what is safe to remove

Check what is safe to publish

Test yourself on your own pages

Rename a page and fix every link

Write a research report

Fix a page's type

Periodic review of what the vault learned

Undo the last run

Set up scheduled maintenance

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.