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ai

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gaming

519

data-viz

Build modern, interactive data visualizations and dashboards using code-based component libraries (shadcn/ui, Recharts, Tremor, Nivo, D3, Victory, visx). Use this skill whenever the user asks to visualize data, build dashboards, create analytics views, chart metrics, tell a data story, build a reporting interface, create KPI cards, plot graphs, or explore a dataset — even if they mention PowerBI, Tableau, Streamlit, Metabase, Looker, Grafana, or similar tools. Also trigger when the user says "make a dashboard", "show me the data", "chart this", "visualize trends", "build an analytics page", "data story", or anything involving turning raw data into interactive visual interfaces. If the task involves presenting data visually — this is the skill. Always prefer building a real, interactive, code-based UI over exporting to or recommending a BI platform.

AltimateAI

development

containers

519

build-cpo-image

Build and push control-plane-operator container image. Auto-applies when testing CPO changes that require deploying to a live cluster.

openshift

devops

containers

519

build-ho-image

Build and push hypershift-operator container image. Auto-applies when testing HO changes that require deploying to a live cluster.

openshift

devops

code-quality

519

sql-review

Pre-merge SQL quality gate — lint 26 anti-patterns, grade readability/performance A-F, validate syntax, and scan for injection threats. Use before committing or reviewing SQL changes.

AltimateAI

testing-security

testing

519

dbt-unit-tests

Generate dbt unit tests automatically for any model. Analyzes SQL logic (CASE/WHEN, JOINs, window functions, NULLs), creates type-correct mock inputs from manifest schema, and assembles complete YAML. Use when a user says "generate tests", "add unit tests", "test this model", or "test coverage" for dbt models.

AltimateAI

testing-security

testing

519

e2e-test-runner

Provides the ability to run and iterate on HyperShift e2e tests. Auto-applies when implementing features that require e2e validation, fixing e2e test failures, or working on tasks that need live cluster testing.

openshift

testing-security

cms-platforms

518

skill-creator

Guide for creating, iterating, and distributing effective skills. Use when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. Also handles skill export (download as ZIP) and publishing to Wegent system.

wecode-ai

development

testing

518

browser

Complete real user web tasks end-to-end via browser-tool, navigate, interact, wait for page state, extract results, and provide evidence when needed.

wecode-ai

testing-security

mobile

516

release-manager

Manage and execute AdMob plugin releases. Use when bumping versions, generating changelogs, or validating GitHub release assets to ensure consistency across Godot, Android, and iOS.

poingstudios

development

mobile

516

sync

Rigorous multi-platform feature synchronization for Godot AdMob. Use when adding or modifying ad formats, consent flows, or bridge methods to ensure GDScript, C#, Android, and iOS implementations are perfectly in sync.

poingstudios

development

technical-docs

516

doc-master

Synchronize documentation with code changes. Use when modifying APIs, installation steps, or project requirements to ensure MkDocs, README, and AGENTS.md are accurate.

poingstudios

documentation

data-engineering

515

batch-research

批量数据采集技能，负责分批并发调度 researcher agent 抓取所有数据源。

miantiao-me

data-ai

cms-platforms

515

publish-weekly

使用 Payload REST API 将周刊写入 CMS（发布为草稿），通过 users API Key 认证。

miantiao-me

development

literature-writing

515

chinese-writing

中文写作技能指南，用于生成高质量的周刊、博客及科技资讯类文章。

miantiao-me

lifestyle

code-quality

515

azd-preflight

**WORKFLOW SKILL** — Runs `mage preflight` from `cli/azd/` and auto-fixes failures. Covers linting, formatting, copyright, spelling, build, and tests. Iterates fix-then-rerun cycles until all checks pass. INVOKES: mage CLI, go CLI, golangci-lint, cspell, bash/sh, ask_user. USE FOR: azd preflight, run preflight, preflight checks, pre-commit checks, azd lint, azd build and test, validate azd changes, check azd code quality, mage preflight. DO NOT USE FOR: deploying azd (use azure-deploy), changelog (use changelog-generation), creating PRs (use pull-request), running only unit tests without the full suite.

Azure

testing-security

full-stack

514

create-module

Create a new NestJS module with controller, service, model, and schema files. Use when adding new feature modules, API endpoints, or business domains.

mx-space

development

data-engineering

512

aws-architecture-diagram

Generate validated AWS architecture diagrams as draw.io XML using official AWS4 icon libraries. Use this skill whenever the user wants to create, generate, or design AWS architecture diagrams, cloud infrastructure diagrams, or system design visuals. Also triggers for requests to visualize existing infrastructure from CloudFormation, CDK, or Terraform code. Supports two modes: analyze an existing codebase to auto-generate diagrams, or brainstorm interactively from scratch. Exports .drawio files with optional PNG/SVG/PDF export via draw.io desktop CLI.

awslabs

data-ai

machine-learning

512

finetuning-setup

Selects a base model and fine-tuning technique (SFT, DPO, or RLVR) for the user's use case by querying SageMaker Hub. Use when the user asks which model or technique to use, wants to start fine-tuning, or mentions a model name or family (e.g., "Llama", "Mistral") — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, validates technique compatibility, and confirms selections.

awslabs

data-ai

machine-learning

512

finetuning

Generates a Jupyter notebook that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, and RLVR trainers, including RLVR Lambda reward function creation.

awslabs

data-ai

machine-learning

512

model-evaluation

Generates a Jupyter notebook that evaluates a fine-tuned SageMaker model using LLM-as-a-Judge. Use when the user says "evaluate my model", "how did my model perform", "compare models", or after a training job completes. Supports built-in and custom evaluation metrics, evaluation dataset setup, and judge model selection.

awslabs

data-ai

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