LLM Mart Basic

用户直接运行 cm-test、要求分析当前分支相对主分支的业务影响，或说“测试已有功能”“根据代码生成用例”“用浏览器走查”时使用。无参数分析已提交差异、单测覆盖率与回归重点；明确说“补齐单测”时连续补测并重跑、审查。显式目标保留原模式，不擅自修产品代码。

UI 还原工程师 Skill，把已确认的设计基准像素级还原为生产代码（token 先行、原子顺序、按交付形态量化验收：Web 用 BackstopJS、App 用 Maestro+模拟器截图）；有基准才出场，不做业务逻辑

项目代码库上下文管理。通读项目生成参考文档(scan)，或加载文档辅助开发(dev)。

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

将产品讨论、问题研究、学术研究、根因假设、测试设计或对抗审查交给外部高能力模型，并由本地主执行者核验、裁决和留存证据；不修改代码或代替正式测试。

Extract a production-ready brand-lock.md from a brand's existing assets. Point it at a website URL, a brand book PDF, screenshots, or a written description and it produces the nine-section brand-lock the rest of shotkit consumes, with a confidence and source noted for every value

Turn a creative brief into a production-grade storyboard with shot specs, timing, on-screen text, and per-shot rationale. Use when the user describes a video brief, plans a video, references shots or beats, scripts a social video, or hands over a creative concept to break into sc

Render a structured storyboard (storyboard.md, shots.json, text-overlays.json, brand-lock.snapshot.md) into a single-file HTML preview that is shareable, printable, and offline. Use when the user wants to share a storyboard, export for review, hand off to an editor, or print a ha

Critique a generated image against its source storyboard shot and prompt, producing revision notes. Use when the user has generated an image and wants feedback before committing. Triggers on "does this match the brief", "review this render", "is this on-brand", "what should I cha

Generate model-specific prompts from shots.json. Outputs copy-paste-ready prompts for stills (Midjourney, Flux, Ideogram, GPT Image, Nano Banana, Seedream) and motion video (Kling, Veo, Seedance, Hailuo). Also runs a revision mode that reads a critique.json and re-emits prompts f

Use aai-cli to inspect and manage Confluence spaces, pages, comments, attachments, and page moves.

Use aai-cli to create local spreadsheet files, manage their sheet tabs, and read, update, or clear cell values — Excel (.xlsx/.xlsm) and delimited text (.csv/.tsv).

Use aai-cli to inspect and manage GitHub repositories, issues, pull requests, reviews, branches, source files, and Actions logs.

Use aai-cli to find Google Drive files and folders, read their metadata, download their content (including Google-native Docs, Sheets, and Slides), check who a file is shared with, and upload a local file back to Drive.

Use aai-cli to inspect HubSpot CRM records, files, events, conversations, visitor identification, and custom channels.

Use aai-cli to search and manage Jira issues, Jira Product Discovery ideas, projects, boards, sprints, comments, and attachments.

Work with Microsoft 365 through aai-cli by choosing the right Microsoft service and resource model, then using durable Graph credentials for Outlook, OneDrive, SharePoint, Teams, Excel, To Do, and Planner workflows.

Use aai-cli to read OpenPanel projects, raw event exports, aggregated insights (metrics, pages, referrers, devices, geo), and user profiles.

Use aai-cli to manage Pipedrive leads, persons, organizations, deals, labels, activities, notes, deal flow/stage history, and synced mailbox data.

Use aai-cli to query PostHog product analytics, read projects, execute HogQL event queries, list saved insights, inspect persons and cohorts, read team dashboards, and view release annotations.

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.

Generate a formatted bibliography from the most recent research session's findings.

Interactively refine research results by searching deeper into a specific subtopic or channel. Requires an active research session from /tome:research.

Export research findings to a format compatible with memory-palace's knowledge-intake skill.

Run a multi-source research session searching GitHub, HN, Lobsters, Reddit, arXiv, and Semantic Scholar. Use for multi-channel topic surveys.

Configure Azure MCP server with Azure CLI authentication

Refresh context with CLAUDE.md instructions

Sync allowlist from GitHub repository to user settings

Sync CLAUDE.md from GitHub repository

Update README.md plugin sections and download links

Configure GCloud CLI authentication

Configure Paper Search MCP (requires Docker)

Manage Supabase Edge Functions.

Automatically generates type definitions based on your Postgres database schema.

Initialize configurations for Supabase local development.

Link your local development project to a hosted Supabase project.

Connect the Supabase CLI to your Supabase account by logging in with your [personal access token](https://supabase.com/dashboard/account/tokens).

Network bans are IPs that get temporarily blocked if their traffic pattern looks abusive (e.g. multiple failed auth attempts).

Provides tools for creating and managing your Supabase projects.

Provides tools for managing environment variables and secrets for your Supabase project.

Starts the Supabase local development stack.

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.