Skills directory · page 24

Build and submit iOS and Android apps with EAS to TestFlight, the App Store, or Google Play. Supports Expo and other React Native projects, plus existing native apps. Use for eas.json setup, release pipelines, signing, app versions and build numbers, store submissions, and listing metadata. For Expo websites and API routes, use eas-hosting; for adding React Native screens to a native app, use expo-brownfield.

Deploy Expo websites and Expo Router API routes to EAS Hosting - export the web bundle, run eas deploy for production and PR preview URLs, manage environment secrets and custom domains, and work within the Cloudflare Workers runtime. Also covers authoring API routes (+api.ts handlers, HTTP methods, request handling, CORS). Use when deploying an Expo web app or API routes, setting up EAS Hosting, or configuring hosting environments and domains. Not for native builds or store releases - use the eas-app-stores skill for those.

Use for anything related to EAS Observe - adding `expo-observe` to an Expo project (AppMetricsRoot/ObserveRoot HOC, markInteractive and ObserveInteractiveMarker, the useObserve hook, the Expo Router / React Navigation integrations for per-route metrics, the expo-image and Reanimated integrations, user-defined events via `Observe.logEvent`, error reporting via ObserveErrorBoundary and `Observe.reportError`, native crash reporting, source map upload for symbolicated stack traces, and runtime config such as sampleRate and dispatchInDebug), querying via the EAS CLI (`eas observe:metrics-summary`, `observe:metrics`, `observe:routes`, `observe:events`, `observe:session`, `observe:versions`, `observe:errors`, `observe:event`) or the Expo MCP `observe_*` tools, interpreting the resulting metrics (cold/warm launch, TTR, TTI, navigation cold/warm TTR, update download, and the TTI frameRate/device/network params for triaging slow startups), or shipping an Observe integration inside a third-party

Run and control a user's app on a remote iOS/Android simulator hosted on EAS cloud. Read before running any `eas simulator:*` commands - it has the current syntax for this experimental API. Use whenever the user needs a simulator they can't run locally - 'run my app on a cloud simulator', 'use eas simulator to run/install/screenshot my app', 'I'm on Linux/Cursor and need an iOS device', 'no sim on this box / headless CI', 'let an agent click through my app and screenshot it', 'test my dev build on a remote sim with live reload', 'stream a sim to my browser' - even when they don't say 'EAS Simulator' or 'cloud'. On a host WITHOUT a local simulator (Linux, CI, cloud sandbox) it's the default; on macOS, do NOT auto-trigger for a plain 'run on the simulator' - use it only for a cloud/remote/shareable sim, an iOS version they lack, or an agent-driven session. NOT for local sims (expo run:ios, Xcode, Android Studio), EAS Build/Update, web preview, or physical devices.

Configure and use EAS Update for over-the-air JavaScript and asset updates with expo-updates and EAS CLI. Use when setting up OTA updates, running eas update:configure or eas update, publishing to preview/staging/production channels, explaining branches/channels/runtime versions, testing updates, or debugging why an installed build still shows old code. Load for TestFlight, preview, or production updates that do not appear, including questions about cold launches or reopening the app. Not for update health metrics; use eas-update-insights for adoption, crashes, and rollout monitoring.

Check the health of published EAS Update: crash rates, install/launch counts, unique users, payload size, and the split between embedded and OTA users per channel. Use when the user asks how an update is performing, whether a rollout is healthy, how many users are on the embedded build vs OTA, or wants to gate CI on update health.

Development conventions and patterns for ECC. JavaScript project with conventional commits.

Convene a four-voice council for ambiguous decisions, tradeoffs, and go/no-go calls. Use when multiple valid paths exist and you need structured disagreement before choosing.

Read the repository's live state before answering, then guide the user through ECC's current agents, skills, commands, hooks, rules, installation profiles, and project onboarding flow.

Answer questions about ECC by reading the live repo surface — agents, skills, commands, hooks, rules, install profiles, and docs — instead of memory. Use when the user asks what ECC includes, how to install or reset it, which skill or command fits a task, or how project onboarding works.

ECC の現在のエージェント、スキル、コマンド、フック、ルール、インストールプロファイル、およびプロジェクトオンボーディングをガイドしています。ライブリポジトリサーフェスを読んでから回答するようユーザーをガイドします。

Map a described workflow to the right ECC command group with run-order and stop condition, or browse all command-group recipe families read live from the commands directory. Advisory only — never executes. Use when asked which commands run a workflow, the command sequence for a task, or to list ECC pipelines; not for executing the task (route to the command itself), single-command docs (use ecc-guide), or prompt rewrites (use prompt-optimizer).

ECC ツール、エージェント、スキル、および実装のコスト監査を実施します。プロンプト入力トークンを分析して、計算効率を定量化します。

Evidence-first ECC Tools burn and billing audit workflow. Use when investigating runaway PR creation, quota bypass, premium-model leakage, duplicate jobs, or GitHub App cost spikes in the ECC Tools repo.

An evidence-first audit workflow for ECC tool burn and billing. Use to investigate runaway PR creation, quota bypass, premium model leakage, duplicate jobs, or GitHub App cost spikes in ECC tool repositories.

Turn raw footage into a finished edit in a specific genre/format — montage, documentary, tutorial, news, workshop, vlog, trailer, explainer. Use whenever the user wants the video "edited into a X", asks "what style should this be / what would make a good X", or hands over raw footage without spelling out every cut. This is the director: it understands the footage first, picks a treatment, then composes the other skills (edl-edit, cutting-rhythm, filler-removal, captions, reframe-social, video-transitions, video-overlay, audio-edit, color-grade, remotion-graphics, grok-video-edit) to execute it.

Turns Claude into a video editor's apprentice. Claude asks the editor to teach it how they work with each client, splits that workflow into stages, works the stages the editor hands over (one at a time, under their corrections), learns from their final cut, and writes everything into an editor skill plus one skill per client. Works with any editing or motion app (Premiere Pro, After Effects, DaVinci Resolve, Final Cut Pro, CapCut and others) through project files, scripting, MCP servers or computer use, in any language. Use it whenever a video editor, montage editor, motion designer or مونتير wants to teach Claude their workflow, onboard a new client or channel, start or continue an episode or project for a client, compare their final cut with Claude's work, or build/update a skill for a client or for themselves — even if they never say "skill" or "apprentice".

Build a multi-clip edit as an auditable JSON "edit decision list" (EDL) — a list of clips with source/in/out and a written rationale per pick — that one command renders to a finished video. Use whenever you're stitching several cuts/takes/segments into one video and want the edit to be reviewable, diffable, and re-runnable instead of a throwaway ffmpeg filtergraph. Covers the schema, the rationale discipline, multicam cutaways, and verifying the output by re-transcribing it.

Generate D2 database diagrams from Entity Framework Core models. USE FOR: EF Core database diagram, Entity Framework Core ERD, DbContext diagram, C# entity relationship diagram, PostgreSQL schema visualization, generate .d2 file from EF Core entities, Fluent API mapping diagram, migrations-based database diagram, table relationships, owned types, many-to-many join tables, indexes and constraints. DO NOT USE FOR: runtime debugging, database migration execution, schema deployment, SQL performance tuning, or draw.io diagrams.

Use for nontrivial Effect 4 work including services/layers, typed errors, Schema/JsonSchema, Config, runtime/concurrency, @effect/vitest, effect/ai and @effect/ai-*, effect/sql and @effect/sql-*, Effect Atom (@effect/atom-*), or @prb/effect-next.

Load when investigating production errors, latency, or trace data — triage order, index patterns, field names, and time-range syntax. Use before hand-rolling a query DSL call or guessing field names.

Master Electron desktop app development with secure IPC, contextIsolation, preload scripts, multi-process architecture, electron-builder packaging, code signing, and auto-update.

Write idiomatic Elixir code with OTP patterns, supervision trees, and Phoenix LiveView. Masters concurrency, fault tolerance, and distributed systems.

Draft professional emails for various contexts including business, technical, and customer communication. Use when the user needs help writing emails or composing professional messages.

Evidence-first mailbox triage, drafting, send verification, and sent-mail-safe follow-up workflow for ECC. Use when the user wants to organize email, draft or send through the real mail surface, or prove what landed in Sent.

Evidence-first inbox triage, drafting, send verification, and sent-mail safety follow-up workflow for ECC. Use when users want to organize email, draft or send through the real mail interface, or prove what was sent.

ECC用の証拠ベースのメールボックストリアージ、ドラフト作成、送信検証、および送信済みメールセーフフォローアップワークフロー。ユーザーがメールを整理したり、実際のメールサーフェスを通じてドラフトまたは送信したい、または送信済みメールに何が到着したかを証明したい場合に使用します。

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.

Use for any drip, nurture, onboarding, welcome or re-engagement email sequence to opted-in users, before writing emails. Plans timing, triggers and exits and scores the sequence with sequence_analyzer.py.

Email has the highest ROI of any marketing channel. $36 for every $1 spent. Yet most startups treat it as an afterthought - bulk blasts, no personalization, landing in spam folders. This skill covers transactional email that works, marketing automation that converts, deliverability that reaches inboxes, and the infrastructure decisions that scale. Use when: keywords, file_patterns, code_patterns.

Use when adding or reworking transactional email (React Email templates, Resend, Postmark, SendGrid or SES, preview, i18n, dark mode, deliverability). Builds the template system and provider integration end to end.

Write authentic, human-sounding emails that build relationships and drive action. This skill should be used when drafting welcome emails, follow-ups, newsletters, announcements, outreach, or any email communication. Integrates with human-writing principles to avoid AI tells. Particularly suited for community building, movement organizing, and personal relationship management contexts.

Use for any embedded or IoT hardware project (ESP32, STM32, Arduino, Pico, firmware, PCB, MQTT, Home Assistant, sensor dashboards), before buying parts. Picks the MCU, board and toolchain, decides where readings go and gives a phased build plan with time and cost.

Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.

Extend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. Use when processing long documents (32k-128k+ tokens), extending pre-trained models beyond original context limits, or implementing efficient positional encodings. Covers rotary embeddings, attention biases, interpolation methods, and extrapolation strategies for LLMs.

Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly with model variants. Covers SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.

Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.

Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity without proportional compute increase. Covers MoE architectures, routing mechanisms, load balancing, expert parallelism, and inference optimization.

Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.

Access European Nucleotide Archive via API/FTP. Retrieve DNA/RNA sequences, raw reads (FASTQ), genome assemblies by accession, for genomics and bioinformatics pipelines. Supports multiple formats.

Procure electricity and natural gas for commercial and industrial facilities: tariff and rate-schedule optimization, demand-charge mitigation, supplier RFPs, fixed/index/block-and-index hedging, renewable PPA and REC evaluation, and sustainability reporting. Use when procuring energy, optimizing utility tariffs, managing demand charges, evaluating PPAs, or building energy budgets and hedge strategies.

Codified expertise in electricity and gas procurement, electricity price optimization, demand charge management, renewable power purchase agreement evaluation, and multi-facility energy cost management. Based on over 15 years of experience from energy procurement managers at large industrial and commercial users. Includes market structure analysis, hedging strategies, load analysis, and sustainability reporting frameworks. Use when procuring energy, optimizing electricity prices, managing demand charges, evaluating power purchase agreements, or developing energy strategies.

電気とガス調達、料金最適化、需要料金管理、再生可能エネルギーPPA評価、およびマルチファシリティーエネルギー戦略のための符号化された専門知識。 Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis, hedging strategies, load profiling, and sustainability reporting frameworks. Use when procuring energy, optimizing tariffs, managing demand charges, evaluating PPAs, or developing energy strategies.

Pick the right advanced engineering skill: agents, RAG, MCP, CI/CD, databases, observability, release. Use whenever the user asks which skill fits a task.

Find which engineering skill fits a task: architecture, frontend, backend, QA, DevOps, security, AI/ML, data, cloud. Use whenever the user is unsure which skill to use; load only that one.

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions, for genomic research.

Operational controls for long-lived or cloud-hosted agent systems — runtime lifecycle (start, pause, stop, restart), observability (logs, metrics, traces), least-privilege safety scopes and kill switches, and rollout/rollback change management with audit logs and success/cost metrics. Use when running production agent fleets on PM2, systemd, or containers that need monitoring, incident response, or deployment gates.

Provision Microsoft Entra Agent Identity Blueprints, BlueprintPrincipals, and per-instance Agent Identities via Microsoft Graph, and configure OAuth 2.0 token exchange (fmi_path, OBO, cross-tenant) including the Microsoft Entra SDK for AgentID sidecar. USE FOR: Agent Identity Blueprint, BlueprintPrincipal, agent OAuth, fmi_path token exchange, agent OBO, Workload Identity Federation for agents, polyglot agent auth, Microsoft.Identity.Web.AgentIdentities. DO NOT USE FOR: standard Entra app registration (use entra-app-registration), Microsoft Foundry agent authoring (use microsoft-foundry).

Microsoft Entra Agent ID (preview) for creating OAuth2-capable AI agent identities via Microsoft Graph beta API. Covers Agent Identity Blueprints, BlueprintPrincipals, Agent Identities, required permissions, sponsors, and Workload Identity Federation. Includes Microsoft Entra SDK for AgentID (containerized sidecar) for polyglot agent authentication (Docker/Kubernetes), 3P agent integration, autonomous and interactive agent patterns. Triggers: "agent identity", "agent id", "Agent Identity Blueprint", "BlueprintPrincipal", "entra agent", "agent identity provisioning", "Graph agent identity", "entra sidecar", "agent id sidecar", "auth sidecar", "3P agent", "third-party agent identity", "polyglot agent auth".