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Found 2,806 Skills
Generate deep links to the Arize UI. Use when the user wants a clickable URL to open a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config.
Multi-agent swarm orchestration where AI agents spawn, coordinate, and self-organize into collaborative teams. Use when running parallel AI agent tasks, orchestrating multi-agent workflows across Claude Code / Codex / Cursor / custom agents, isolating agent workspaces via git worktrees, tracking task dependencies across agents, or running autonomous experiments. Triggers on: clawteam, agent swarm, spawn agents, multi-agent team, agent orchestration, parallel agents, agent coordination, swarm intelligence, agent spawn, clawteam spawn, agent worktree, agentic team, ml agent experiments, autonomous agents, agent team.
Retrieve a GitHub issue using the `gh` CLI, analyze it, and spawn a PM + developer team to address it. Accepts an issue URL, issue number, or `owner/repo#number`.
Template for creating router skills. Use as a starting point when building a new router that dispatches to multiple specialized skills. Copy and customize for your domain.
Operate Linear workspace issues, projects, and teams through Linear GraphQL API using UXC. Use when tasks require querying or creating issues, managing projects, or interacting with Linear workflow. Supports both Personal API Key and OAuth authentication.
Donella Meadows's System Leverage Points applied to any complex system — company, market, policy, or organization. Spawns a team of specialist agents — System Cartographer, Leverage Diagnostician, Counterintuitive Analyst, Paradigm Archaeologist, Dancing Advisor — who each apply a distinct lens from Meadows's framework to identify where you're wasting effort on low-leverage interventions. The lead synthesizes into a leverage audit: which level you're pushing at, which level you should be pushing at, and whether you're pushing in the right direction. Use when the user says "meadows this", "where's the leverage", "systems analysis", "why isn't this working", or describes a complex system that seems stuck despite effort. Works as a standalone analysis or paired with /munger.
Guides systematic PyTorch recommender-system model development across compact data facts, existing source code, configs, focused tests, and training loops without overloading context from broad research archives. Use when building, debugging, or refactoring torch/nn.Module RecSys models with Transformer/HSTU/attention blocks, sparse/dense/list feature fusion, pCVR/CTR heads, ablation axes, or competition codebases where many model ideas exist but bugs and interface drift must be controlled. 用来指导推荐系统 PyTorch 模型开发、Transformer/HSTU 建模、关键数据事实、特征交互、shape/debug、训练闭环和已有模型结构的系统化推进。
Migrate a Grafana plugin to React 19 compatibility. Use when the user asks to update a plugin for React 19, prepare for React 19, fix React 19 compatibility, upgrade to React 19, migrate to React 19, bump grafanaDependency to 12.3.0, externalize jsx-runtime, or run react-detect. Triggers on phrases like "update plugin for React 19", "React 19 migration", "prepare for React 19", "plugin React 19 compat", "grafanaDependency 12.3.0", "JSX runtime externals", "react-detect", "SECRET_INTERNALS", "ReactCurrentOwner", or "ReactCurrentDispatcher".
Automates declarative resource creation and provisioning for data pipelines, supporting BigQuery, Dataform, Dataproc, BigQuery Data Transfer Service (DTS), and other resources. It manages environment-specific configurations (dev, staging, prod) through a deployment.yaml file. Use when: - Modifying or creating deployment.yaml for deployment settings. - Resolving environment-specific variables (e.g., Project IDs, Regions) for deployment. - Provisioning supported infrastructure like BigQuery datasets/tables, Dataform resources, or DTS resources via deployment.yaml. Do not use when: - Resources already exist. - Managing resources not supported by `gcloud beta orchestration-pipelines resource-types list`. - Managing general cloud infrastructure (VMs, networks, Kubernetes, IAM policies), which are better suited for Terraform. - Infrastructure spans multiple cloud providers (AWS, Azure, etc.). - Already uses Terraform for the target resources.
Initialize a new Adobe App Builder project end-to-end without manual template selection. Maps user intent to the correct template, runs non-interactive initialization, and guides post-init customization. Use this skill whenever the user mentions creating an App Builder app, scaffolding a project, initializing with aio, setting up an Experience Cloud extension, adding actions or web assets to an existing project, or anything related to 'aio app init', even if they don't explicitly say 'App Builder'. Also use when users mention SPA templates, AEM extensions, API Mesh setup, Asset Compute workers, or MCP server projects. Also handles debugging and troubleshooting init failures — use when users report template not found errors, aio app init hanging or timing out, Node version mismatches, npm install failures after init, build errors right after project setup, wrong directory structure from extension templates, aio login or token issues, or aio app run showing nothing.
Stripped-back design emphasizing whitespace, clean typography, and restrained color for maximum clarity and focus.
Spawn, stop, change state, or manage a standalone animated 2D desktop sprite companion. Use when the user invokes `/eggs`, asks for an animated desktop companion, wants a roaming sprite character, or asks to stop/status/restart/change the companion process.