数据库 MCP（PostgreSQL / MySQL / Redis）

HeroUI v3 React component library (Tailwind CSS v4 + React Aria). Use when building UIs with HeroUI — creating Buttons, Modals, Forms, Cards; installing @heroui/react; configuring dark/light themes with oklch variables; or fetching component docs. Keywords: HeroUI, Hero UI, heroui, @heroui/react, @heroui/styles.

HeroUI Native component library for React Native (Tailwind v4 via Uniwind). Use when building mobile UIs with HeroUI Native — creating Buttons, Cards, TextFields, Dialogs; installing heroui-native; configuring dark/light themes; or fetching component docs. Keywords: HeroUI Native, heroui-native, React Native UI, Uniwind, mobile components.

Use this when working on the ArchiveBox app, CLI, server, Docker image, Admin UI, REST API, data dirs, crawls, snapshots, and release/deploy scripts.

Bootstrap pointer that installs the external repo-scan skill from a pinned, reviewable commit. Use when repo-scan must be installed before running its cross-stack source-code asset audit; this ECC pointer does not perform the audit itself.

Provides instructions for implementing, integrating, or configuring Google Mobile Ads (GMA) SDK interstitial ads in Android, iOS, or Unity mobile applications. Use when the task involves setting up interstitial ads. Don't use for "rewarded interstitial" ads.

Generate Django database migrations for Sentry. Use when creating migrations, adding/removing columns or tables, adding indexes, or resolving migration conflicts.

Investigates a session recording by gathering metadata, person profile, same-session events, and linked error tracking issues in one pass. Use when a user provides a recording or session ID and wants to understand what happened — who the user was, what they did, what errors occurred, and whether there are related error tracking issues. Replaces the manual chain of session-recording-get, persons-retrieve, execute-sql, and query-error-tracking-issues-list.

OpenClaw Tideclaw alpha/nightly release automation: isolated branches, local fixes, release CI, branch retention, and forward-port to main.

Convert a legacy internal Ghost workspace package from JavaScript or CommonJS to the repository's TypeScript and ESM golden path while preserving file history and runtime compatibility. Use when modernizing an existing or newly migrated private package, including staged lib-to-src moves, JS-to-TS renames, consumer analysis, and package or archive verification.

Architecture and hard-won debugging lessons for customization enablement (plugins, MCP servers, agents, skills, instructions) in the agent host. Use when changing how customizations are discovered, published, enabled/disabled, or handed to a provider SDK; when a customization shows the wrong enabled state in the UI; or when a disabled MCP server or plugin is still reaching the model.

Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.

Unattended variant of continue-pr for automation (driven by utils/continue-all-prs.sh). Resolves conflicts - reworking stale features to reconcile with current master when a mechanical merge is not enough - fixes CI, addresses feedback, and pushes without ever asking the user. For interactive use, prefer continue-pr.

Review Supabase docs changes locally in ~/GitHub/supabase/supabase — either an open PR (triage, classify, verify) or your own branch before opening a PR (local self-review). Covers markdown pipeline, MDX content, tutorials, examples, Studio links, and docs tooling. Use when asked to review docs PRs, self-review a draft branch, check who has approved, verify build output, or evaluate supabase/supabase documentation changes.

Read-only Itô basket and prediction-market data skill. Index the live basket catalog, compare a basket against user-supplied research or a watchlist, build a source-grounded market brief, or draft a non-executable planning worksheet. Use when a user asks to browse or index Itô baskets, compare a basket against notes or a thesis, research prediction-market events/venues/liquidity, or plan a basket or market idea without trading. Never advises, orders, trades, reserves, or executes.

Inspect the availability of ML training on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed training manifest. Use after ito-compute has booked GPU nodes and the user wants pre-training, fine-tuning, or RL on that metal. ECC implements no training stack of its own.

Use when completing tasks, implementing major features, or before merging to verify work meets requirements

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

Use when creating new skills, editing existing skills, or verifying skills work before deployment

Use when you have a spec or requirements for a multi-step task, before touching code

Multi-agent QA review team for code changes. This skill should be used when the user asks to "review my code", "run QA", "qa-team", "review this branch", "code review", "check my changes", or wants a comprehensive multi-perspective code review of the current branch's changes. Spawns parallel specialist agents (security, database, reliability, compatibility, data integrity, performance, frontend, copy) that independently review the diff and produce a converged report. Also includes two generalist reviewers for convergence validation.

Audits services/llm-gateway against PostHog/ai-gateway and updates services/llm-gateway/PARITY.md from current implementation evidence. Use when either gateway changes auth, attribution, billing, endpoints, providers, models, routing, or metadata; when reviewing a Python gateway change; or when asked to refresh, verify, or report gateway parity. This skill updates the parity record but does not migrate callers.

How to mirror the career-ops tracker to a Notion database and read records back as job leads.

GitHub supply-chain forensics: recovery, IOCs, reporting.

Create, read, edit .pptx decks with python-pptx.

Build, test, and deploy Python MCP servers.

Iterative Python via live Jupyter kernel (hamelnb).

Deploy a Worker live, no account, via wrangler --temporary.

End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration. Use when adding a machine learning capability to a codebase that has none, from problem framing through a baseline model.

A comprehensive verification system for Claude Code sessions. Use when verifying a Claude Code session's work before claiming it is complete.

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles. Use when a Claude Code workflow needs a formal eval before it is trusted or changed.

A comprehensive verification system for Claude Code sessions. Use when verifying a Claude Code session's work before claiming it is complete.

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles. Use when a Claude Code workflow needs a formal eval before it is trusted or changed.

Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks. Use when setting up write-time formatting, linting, or auto-fix hooks on file edits.

Idiomatic Rust patterns, ownership, error handling, traits, concurrency, and best practices for building safe, performant applications. Use when writing or reviewing Rust code and ownership, error handling, traits, or concurrency is in question.

Map a described workflow to the right ECC command-GROUP with run-order and stop condition, and browse all command-group recipe families. Adds a family-grouping + run-order + when-to-stop layer on top of the flat command catalog. Advisory only. TRIGGER when the user says which commands for X, what command group runs X, show ECC recipes, list ECC pipelines, or how do I run a workflow with ECC. DO NOT TRIGGER when the user wants the task executed directly, wants a single-command deep doc (use ecc-guide), or wants a draft prompt rewritten (use prompt-optimizer).

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders. Use when writing or reviewing Kotlin code and idiomatic structure or null safety is in question.

Idiomatic C# and .NET patterns, conventions, dependency injection, async/await, and best practices for building robust, maintainable .NET applications. Use when writing or reviewing C# / .NET code — DI, async, or general conventions.

Production-ready Dart and Flutter patterns covering null safety, immutable state, async composition, widget architecture, popular state management frameworks (BLoC, Riverpod, Provider), GoRouter navigation, Dio networking, Freezed code generation, and clean architecture. Use when writing or reviewing Dart and Flutter code — state, widgets, navigation, networking, or architecture.

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading. Use when writing or reviewing PyTorch training loops, model architectures, or data loading, or when a run will not reproduce.

Modern Perl 5.36+ idioms, best practices, and conventions for building robust, maintainable Perl applications. Use when writing or reviewing modern Perl 5.36+ code.

Nuxt 4 app patterns for hydration safety, performance, route rules, lazy loading, and SSR-safe data fetching with useFetch and useAsyncData. Use when building or reviewing a Nuxt 4 app, or debugging hydration mismatches and SSR-safe data fetching.

Idiomatic Go patterns, best practices, and conventions for building robust, efficient, and maintainable Go applications. Use when writing or reviewing Go code and idiomatic structure or conventions are in question.

Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use when presenting a plan for review, or when feedback like "move this, change that" is easier pointed at than typed.

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback. Use when evaluating academic or scientific work — papers, proposals, methods sections, or evidence quality — against a repeatable rubric.

Local-evidence production readiness audit for shipped apps, pre-launch reviews, post-merge checks, and "what breaks in prod?" questions without sending repo data to an external audit service. Use when auditing production readiness before launch, after a merge, or when asked what breaks in prod.