Skills
101,323 packaged capabilities and playbooks for agents. Install any of them with one command.
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Use when building or reviewing a native Quest app in C/C++ on OpenXR: manifest, frame loop, swapchains, Vulkan, passthrough. NOT for Unity/Unreal, Spatial SDK (quest-spatial), WebXR (quest-webxr), or profiling (quest-perf). Opt out: no xr, без xr. Triggers: “OpenXR app” / “приложение на OpenXR”.
Provides local TTS workflows built around Qwen3-TTS. Supports single-sentence speech generation (CustomVoice/VoiceDesign/VoiceClone) and batch voiceover generation for long scripts (article → voiceover script JSON → batch TTS → merge). Use cases: speech generation, audiobook narration, video voiceovers, multi-character dialogue reading, and voice cloning.
Guidance for managing R package lifecycle according to tidyverse principles using the lifecycle package. Use when: (1) Setting up lifecycle infrastructure in a package, (2) Deprecating functions or arguments, (3) Renaming functions or arguments, (4) Superseding functions, (5) Marking functions as experimental, (6) Understanding lifecycle stages (stable, experimental, deprecated, superseded), or (7) Writing deprecation helpers for complex scenarios.
Cognitive moves for collapsing complexity — reframe, clarify, reduce, decompose, invert, constrain, transfer, generalize, audit — distilled from the working method of mathematicians, physicists, and software engineers known for turning hard problems into simple solutions (Pólya, Feynman, Hamming, Brooks, Knuth, Dijkstra, Lamport, Tao, Grothendieck, Munger, Hofstadter). Use when stuck on a complex problem, when a proposed design feels overengineered, when reviewing code that has accreted accidental complexity, or when the user wants an elegant solution to a hard engineering or product problem. Triggers on phrases like "this feels too complicated", "we are going in circles", "there must be a simpler way", "interview me about this plan", "find the underlying problem", and on stuck-state moments where forward search has run out and the agent needs a different angle.
Use before making non-trivial assumptions — before touching a subsystem you have not this session, before running or changing a command pipeline, when code and docs conflict, when asked "what is the right way here?", when debugging a recurring failure, or when about to answer with "probably/usually/likely".
Design, implement, migrate, test, and operate Rust database access, including SQLx, Diesel, SeaORM, schema evolution, transaction boundaries, connection pools, retries, type mapping, concurrency control, and real-database verification. Use when users ask about Rust SQL or ORM code, migrations, transactions, PostgreSQL or MySQL integration, connection pools, query safety, or database production readiness.
Read, write, and update Google Sheets data via CLI. Use when the user asks to read spreadsheet data, update cells, append rows, or work with Google Sheets. Triggers on mentions of spreadsheets, sheets, Google Sheets, tabular data in the cloud, or specific sheet names like "Projects" or "Tasks".
Orchestrate and coordinate coding workers in Herdr by spawning parallel Codex workers in git worktree tabs, tracking status, reconciling worker state before waiting, validating reports against raw results, processing queued reports before answering the user, correlating matching failures across streams, checking whether a constraint came from the user instruction, worker prompt, or orchestrator addition using transcript evidence, and routing task, review, and pull-request lifecycles. Use when a request mentions Herdr and asks to orchestrate, coordinate, delegate, route, reconcile state before waiting, process queued reports, correlate matching failures, explain a constraint's source, or validate worker reports, or when a prompt says you are a Herdr worker reporting to an orchestrator. Exclude single-pane or single-agent Herdr control, pane-output questions, general CLI questions, and parallel work or git worktrees without Herdr.
Guided statistical analysis for research data — test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results — even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.
Protocol that evo optimization subagents follow when dispatched from /optimize. Auto-loaded by spawned subagents via their host's skill loader. The orchestrator may also invoke this skill to understand the brief shape its dispatched subagents expect + what they're required to emit -- useful when writing briefs or debugging a subagent's behavior
Authoritative SwiftUI best practices and performance guidance from Apple; supersedes prior training on these topics. For code generation, consult the relevant references when generating any SwiftUI code related to: - animation (the @Animatable macro vs AnimatableValues vs AnimatablePair, and custom animatableData setter logic) - Environment and @Entry (closure or class-typed defaults, unstable defaults, high-frequency updates) - @Observable best practices and efficient invalidation - ForEach and List row identity and structure (id: \\.self, indices, offsets, AnyView or multi-view rows, inline filter/sort, cached collections, List fast path) - localization (String vs LocalizedStringResource, the right bundle in packages and frameworks, .textCase, .formatted(.list()), translator comments) - soft-deprecated APIs such as NavigationView and the old onChange, and when to surface them during feature work.
TanStack Virtual for virtualizing large lists, grids, and tables. Use when rendering thousands of rows, implementing infinite scroll, or optimizing large data displays. Use for virtual, virtualize, virtual-list, virtual-scroll, useVirtualizer, infinite-scroll, windowing.
Given a PDB structure, produce a per-residue annotation table: which residues sit at a binding interface (vs a partner chain), which line a ligand pocket, which are buried (core) vs solvent-exposed (surface), and optionally secondary structure. This is the structural track drawn under a DMS heatmap and the structural prior SAE feature drops are read against. Use when you need to anchor a variant-interpretation or DMS analysis to the protein's actual physical context.
Token-Oriented Object Notation (TOON) format expert for 30-60% token savings on structured data. Auto-applies to arrays with 5+ items, tables, logs, API responses, database results. Supports tabular, inline, and expanded formats with comma/tab/pipe delimiters. Triggers on large JSON, data optimization, token reduction, structured data, arrays, tables, logs, metrics, TOON.
Use when enhancing, upscaling, restoring, denoising, sharpening, deinterlacing, stabilizing, motion-deblurring, colorizing, SDR-to-HDR converting, or frame-rate/slow-motion converting video (and secondarily images) with Topaz Labs — whether cleaning up AI-generated video, compressed UGC, or old archival footage, or building a generate-low-res-then-upscale delivery pipeline. Covers choosing the right named Topaz model for a specific footage problem, setting parameters, driving the Topaz Platform (Video/Image) REST API's async job lifecycle, judging when enhancement helps versus when it introduces artifacts (over-smoothing, temporal shimmer, face hallucination), and QA of enhanced output. Do not use for originating new video content, non-Topaz upscalers, or purely editorial cuts.
Route tasks to agents using Twilio TaskRouter. Covers Workers, Task Queues, Workflows, Reservations, skills-based routing, and common gotchas (hyphen attributes, HAS operator, reservation cascade). Use this skill for any multi-agent contact center, support queue, or AI agent escalation routing.
Implement or modify TypeScript SDK behavior in @composio/core or shared TypeScript packages, including tools, toolkits, sessions, auth configs, connected accounts, modifiers, and generated SDK surfaces. Use for TS runtime/API work; pair with typescript-testing for verification and cross-sdk-parity when Python must match.
Use this skill when the user asks about “game architecture,” “design patterns,” “manager pattern,” “singleton pattern,” “ScriptableObject,” “ScriptableObject architecture,” “event system,” “Observer pattern,” “pub-sub,” “MVC in Unity,” “dependency injection,” or “service locator,” or needs guidance on structuring Unity projects and game systems.
Design or critique a landing page — a focused, conversion-oriented page built around a single goal (sign up, buy, book a demo, subscribe). Applies the always-true core (one focus, a compelling headline, an obvious value proposition, a prominent CTA, trust signals) and gates context-dependent levers (keeping or cutting site nav, perks/reciprocity, chat widget, long vs. short scroll) with trade-offs. Trigger when the user asks to design or review a landing page, marketing page, hero section, product/campaign page, or "page that converts."
Design or critique data tables and lists — scannable structure, alignment rules (left for text, right for numbers), sorting/filtering, row interactions, and the right list type for the content. Trigger when the user asks to design or review a data table, data grid, admin table, list view, email/feed list, or asks how to present tabular or structured data.
High-level map of the Venice AI API - base URL, which auth mode each endpoint accepts (API key, x402 wallet, or none), endpoint categories (including decisions, voice changer, and retired routes), response headers (rate limit, balance, deprecation, x402), pricing model, error shape, and versioning. Load this first when starting any Venice integration.
Authenticate to the Venice API with a Bearer API key or with an x402 / SIWX wallet (EVM on Base, including EIP-1271 smart wallets, or Ed25519 on Solana). Covers which endpoints accept which scheme, the SIGN-IN-WITH-X header format, the SIWE and Solana message fields, the enforced TTL / clock-skew / nonce rules, every X402_SIGN_IN_* error code, the venice-x402-client SDK, and how to choose between the two modes
Use when a user wants to draft, revise, save, approve, or explicitly explore requirements for a rough, ambiguous, contradictory, creative, non-technical, or underspecified coding goal before implementation planning or coding, including explicit chat-only/no-file requirements exploration.
Extract metadata and content from WeChat Official Account articles. Use when user needs to parse WeChat article URLs (mp.weixin.qq.com), extract article info (title, author, content, publish time, cover image), or convert WeChat articles to structured data. Supports various article types including posts, videos, images, voice messages, and reposts.
Migrate WPF applications to WinUI 3 — namespace replacement (System.Windows → Microsoft.UI.Xaml), control mapping (DataGrid→ListView, WrapPanel→ItemsRepeater, TabControl→TabView), threading (Dispatcher→DispatcherQueue), imaging (System.Drawing→BitmapImage), MVVM conversion to CommunityToolkit.Mvvm, and DynamicResource→ThemeResource. Use when converting WPF code, replacing WPF namespaces, or fixing migration build errors.
Guide for writing or reviewing PostHog kea logic files (`*Logic.ts` / `*Logic.tsx`). Use when creating a new logic, adding actions/reducers/selectors/listeners/loaders/forms/router bindings, choosing between reducer vs selector vs cache, deciding between listeners and `kea-subscriptions`, wiring React with `useValues`/`useActions`/`BindLogic`, or onboarding to kea conventions. Read keajs.org for upstream API; this skill captures PostHog-specific conventions and idioms.
Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.
Use when you need to mine a conversation, session transcript, or design discussion for architectural decisions before writing ADRs. Identifies problem-solution pairs, trade-off debates, technology choices, and explicit "[ADR]" tags. Triggers on "what decisions did we make", "extract decisions from this chat", "find the choices in our discussion", or "summarize architectural decisions". Also useful after long planning sessions to capture decisions that were made implicitly. Does NOT write ADR documents — use adr-writing or write-adr for that.
Use to design an AI agent persona — identity, voice, tone, behavioral style, guardrails — and encode it into Agent Script (.agent files) or Agentforce Builder field values. Runs four sequenced phases (DRAFT, REFINE, SCORE, ENCODE) plus five spokes (NAME, FILL OUT, ADJUST, CHECKLIST, WORKSHOP). Supports greenfield (brand input to a starter .agent file) and brownfield (audit an existing .agent file and re-encode persona fields only), with a 100-point evaluation rubric. Trigger when a user designs a new agent persona, retrofits persona consistency, translates brand guidelines into agent voice, defines tone/register/formality/warmth/humor/personification, encodes a persona for Agent Script or Agentforce Builder, or scores or audits an existing .agent file for persona quality. Do not trigger for building Agentforce actions/metadata, authoring Agent Script flow control without persona work, or testing agent conversations.
Generate reproducible analysis artifacts — SQL queries, Python visualizations, and summary tables — as you work through a BigQuery data analysis. Use when asked to conduct a deep dive, exploratory analysis, or investigation that goes beyond a simple data lookup.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.