AI & ML

Explain how email and Google Calendar work for OpenClaw agents, including the distinction between agent email and owner email, how gog and the Google Workspace skill are used, where related credentials/config live, and how to troubleshoot common setup or access issues. Use when someone asks how an OpenClaw agent accesses Gmail/Google Workspace/Calendar, where credentials are stored, how to use the agent inbox, how to give the agent write access to the owner's calendar, or how to guide another agent/user through the email or calendar setup model.

Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or

Control cmux workspaces, panes, surfaces, and agent sessions safely from macOS terminal workflows.

Anti-over-engineering guardrail that activates when an AI coding agent expands scope, adds abstractions, or changes files the user did not request.

Connect to MAXIA AI-to-AI marketplace on Solana. Discover, buy, sell AI services. Earn USDC. 13 MCP tools, A2A protocol, DeFi yields, sentiment analysis, rug detection.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected

Job search automation, auto apply, resume generation, application tracking, salary intelligence, and recruiter outreach using the JobGPT MCP server.

Compact the current conversation into a handoff document for another agent to pick up.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Compiled CLI covering all 52 endpoints of the Anytype local API — objects, properties, tags, search, chat, files — one binary, no MCP server needed.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debuggin

Routes, controller, Acorn routes, web.php, route:list, Route::get, Route::post, Route::resource, Route::apiResource, middleware, route model binding, API endpoint, RouteServiceProvider, named routes, resource controller, single-action controller, invokable controller, route group, route prefix, JSON response, rate limiting, token auth, Accept application/json, route cache, WP rewrite conflicts — using Acorn's Laravel routing inside WordPress/Sage/Bedrock

Eloquent, model, migration, relationship, hasMany, belongsTo, belongsToMany, Acorn Eloquent, custom table, wp_posts, wp_users, wp_postmeta, factory, query scope, scopePublished, global scope, make:model, make:migration, lando acorn migrate, $fillable, $casts, $timestamps, $primaryKey, HasFactory, db:seed, seeder — Eloquent ORM for custom and WordPress tables via Acorn

Creates custom WordPress Abilities for the WP MCP Adapter (WP 6.9+). An Ability is a PHP class extending Roots\AcornAi\Abilities\Ability that exposes a JSON schema and execute() method — auto-discovered by the MCP Adapter and callable via Claude's execute-ability tool. Covers: lando wp acorn make:ability, AbilitiesServiceProvider registration, JSON schema definition, discover-abilities validation. Invoke for: abilities, make ability, custom mcp endpoint, discover-abilities, execute-ability, acorn ability, abilities-authoring, mcp endpoint, wp ability, make:ability.

Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"

Plans parallel agents or worktrees with isolated ownership, validation lanes, and merge rules. Use only for safely separable work.

Models threats for a service, feature, endpoint, integration, or architecture: assets, attackers, boundaries, flows, and abuse cases.

Analyzes repeated agent failures or noisy routing and proposes evidence-backed changes to instructions, skills, gates, or runbooks.

Runs read-only parallel review of a PR, branch, commit, or diff across bugs, security, tests, maintainability, performance, and UI.

Merges agent or review outputs into one deduplicated, evidence-linked, severity-ranked actionable report.

当用户想测试或复盘某个 skill 的实际执行效果时使用——如“测一下这个 skill”“看看 agent 是否按 skill 执行”“生成 skill 覆盖率或溯源报告”。在隔离沙箱中发起一次 headless 盲测，逐步骤溯源并产出中文复盘报告。不要用于编写新 skill、调试业务代码、代码审查，或复盘当前会话已经发生的执行。

从一份或多份现有配置抽取可审阅的 agent-config.yaml，并跨 Windows、Linux、macOS 与 WSL 声明式同步 Codex ~/.codex/config.toml 和 Claude Code ~/.claude/settings.json。用于导入、去重、解决冲突、剔除配置项、初始化、检测、校验、渲染、预览差异、应用、检查状态或诊断；不用于凭据、登录状态、项目级配置、~/.claude.json、skills、agents、hooks 或 MCP 配置。

Use for writing, reviewing, debugging, testing, or diagnosing Python Bayesian models built directly with PyMC, including Model, coords/dims, Data, random variables, potentials, posterior sampling, prior/posterior predictive checks, and InferenceData output. Trigger on model geometry, shape errors, divergences, sampler choice, mutable prediction data, and probabilistic validation. Do not use for Bambi formula models, NumPyro/JAX programs, ArviZ-only analysis of existing draws, deterministic optimization, or general statistics without PyMC code.

Use for writing, reviewing, debugging, testing, or optimizing Python CVXPY optimization models. Trigger on Variable, Parameter, Expression, Constraint, Objective, Problem, DCP, DPP, DGP, DQCP, solver selection/status, dual values, mixed-integer, cone, or repeated parametric solves. Do not use for scipy.optimize-only, PyMC inference, symbolic algebra without optimization, or hand-written solver implementations.

Use for writing, reviewing, debugging, testing, or analyzing Python SimPy discrete-event simulations. Trigger on Environment, Event, Process, timeout, Resource, PriorityResource, PreemptiveResource, Container, Store, queues, interrupts, simulation clocks, replications, or SimPy monitoring. Do not use for asyncio services, wall-clock schedulers, continuous ODE solvers, or Monte Carlo code without an event-process model.

Write, debug, and test NumPyro probabilistic programs on JAX with correct shapes, PRNG keys, and inference choice.

Use for designing, creating, reviewing, or packaging GitHub Copilot and Agent Plugins for Visual Studio Code, including plugin.json, portable skills, MCP components, client-specific agents, commands, and hooks. Do not use for a single standalone skill, ordinary VS Code extensions, or installing an unreviewed plugin.

Use for writing, reviewing, debugging, migrating, or testing Python application configuration built with pydantic-settings. Trigger for BaseSettings, SettingsConfigDict, environment names, dotenv, secrets directories, nested settings, CLI sources, custom source precedence, and secret-safe startup configuration. Do not use for ordinary Pydantic model validation, direct os.environ access in a small script, or external secret manager administration.

Create, review, and debug GitHub Copilot reusable prompt files and slash commands in Visual Studio Code.

The current Pencil MCP tool surface, `execute` idiom catalog, transport table, and document-discipline rules. Read before any Pencil call, in either `cli-app` or `editor` mode.

Shared shell rules for portable, approval-friendly agent commands. Use when running git, GitHub CLI, builds, tests, cross-directory commands, or commands that write files.

Shared native Codex stage, checkpoint, goal, and agent-adapter contract.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).