LLM Mart Basic

Use when the user has written (or wants to write) a `ModularPipelineBlocks` subclass in a local Python file and needs to package it into a Hub-uploadable directory. Covers the workflow from a single `block.py` file to a published custom-block repo that consumers can load via `Mod

Use when the user wants to run a diffusers pipeline from a terminal (one-off generation, batch jobs, smoke-testing a new model), run on HF Sandbox hardware via `--remote`, introspect a pipeline's input schema before calling it, or attach a LoRA at inference time. Prefer this over

Use when adding a new model or pipeline to diffusers, setting up file structure for a new model, converting a pipeline to modular format, or converting weights for a new version of an already-supported model.

Use before opening a PR, or whenever asked to self-review a diffusers contribution. Applies the same rubric as the `@claude` CI (checks the diff against references/review-rules.md, traces call paths for dead code). Reports findings grouped by severity, flagging what to fix before

Guide for performing Chromium version upgrades in the Electron project. Use when working on the roller/chromium/main branch to fix patch conflicts during `e sync --3`. Covers the patch application workflow, conflict resolution, analyzing upstream Chromium changes, and proper comm

Guide for performing Node.js version upgrades in the Electron project. Use when working on the roller/node/main branch to fix patch conflicts during `e sync --3`. Covers the patch application workflow, conflict resolution, analyzing upstream Node.js changes, building, running the

Write unit and E2E tests for Grafana frontend code (React/TypeScript, any package or feature area) to the conventions this repo expects. Use when adding, backfilling, or reviewing frontend tests; when a test only asserts "it rendered" or "it's defined"; when reviewing AI-generate

Write unit and E2E tests for Grafana visualization panels and viz utilities to the conventions this repo expects. Use when adding, backfilling, or reviewing tests for panels (barchart, timeseries, table, xychart, heatmap, canvas, etc.), grafana-ui viz components (Table, uPlot, Vi

Drive and verify the Kody app with a Feature Map and one CLI. Use when changing UI, account routes, preview deploys, or proving a Cloud Agent change with a real origin, session, and /health SHA.

Discover, wait for, sign in, create specific user data, and assert a PR preview deploy. Use on medium or high risk PRs, after pushing a ready-for-review PR, or when the user asks to test the preview URL.

Imported from modem-dev/ossrules/public/files/kody/.agents/skills/remix.

Take a change through a pull request in the pnpm repository — opening it, then staying with it after every push until CI is green and the review round is quiet. Use when opening a PR, after pushing to one, when a check fails, or when review comments arrive.

Run the tests that cover a change in the pnpm repository, in the Rust workspace (pnpm/, pnpr/) or the TypeScript CLI (pnpm11/), and recognize the cases where a scoped run passes without testing anything. Use whenever verifying a change before committing or pushing, or when decidi

Review PyTorch pull requests for code quality, test coverage, security, and backward compatibility. Use when reviewing PRs, when asked to review code changes, or when the user mentions "review PR", "code review", or "check this PR".

Use when modifying or reviewing Qwik core package code under packages/qwik, especially reactive primitives, signals, VNodes, cursor behavior, QRLs, optimizer-facing runtime behavior, or Qwik core tests.

Use when writing, modifying, or reviewing Qwik docs content or docs-site code under packages/docs, including docs routes, MDX content, generated LLM outputs, docs build behavior, or docs-specific e2e tests.

Use when creating, modifying, debugging, or running Qwik Playwright e2e tests under e2e/, including router, adapters, docs, CLI, and React integration suites.

Use when modifying or reviewing the Qwik optimizer under packages/optimizer, Rust transform code, WASM/NAPI bindings, optimizer snapshots, or optimizer-facing runtime behavior.

Use when modifying or reviewing Qwik Router code under packages/qwik-router, including runtime routing, buildtime route generation, middleware, adapters, SSG, markdown/MDX handling, or router tests.

Use when a user says "add a ty diagnostic", "write this new ty diagnostic", "change a ty error message", "review ty diagnostics", or asks to add, update, or review ty checks, diagnostic messages, subdiagnostics, or concise output behavior.

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.

A green PR, a controller reporting success, and not one line of the new code running

Export a page or set of pages

What is missing from my understanding

Export the graph for outside analysis

Report the shape of the graph

Prepare a handoff brief

Quick health check

Find pages that swallowed the graph

Rebuild the index

Import an exported chat history

Ingest book or article highlights

Ingest your own finished work

Ingest newsletters without duplicating

Ingest an academic paper

Ingest a PDF

Clip and ingest a web page

Ingest a voice note

Ingest a video or podcast transcript

Ingest new material from raw/ into the wiki

Scaffold a new vault

Install the skills, commands and agents

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.