Deep knowledge about deploying applications to AWS (EC2, ECS, S3, CloudFront, Cloud Run).
日本語の概要は準備中です。原文の説明を表示しています。
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Deep knowledge about deploying applications to AWS (EC2, ECS, S3, CloudFront, Cloud Run).
日本語の概要は準備中です。原文の説明を表示しています。
Use when building APIs on Hono (Cloudflare Workers, Bun, Deno, Node), debugging route ordering, wiring middleware, validating with @hono/zod-validator, returning streaming responses, configuring CORS with credentials, handling errors via app.onError, or composing typed RPC clients. Triggers: c.env binding types, c.header + c.redirect interaction, missing await next() bugs, Set-Cookie not attaching to redirect, route-precedence surprises, JWT middleware setup, hono/client typed RPC end-to-end. NOT for Express/Fastify/Koa idioms, tRPC/GraphQL paradigms, or Next.js Route Handlers.
日本語の概要は準備中です。原文の説明を表示しています。
Expert debugger for Next.js + Cloudflare Workers + Supabase stacks. Systematic troubleshooting for auth, caching, workers, RLS, CORS, and build issues. Activate on: 'debug', 'not working', 'error', 'broken', '500', '401', '403', 'cache issue', 'RLS', 'CORS'. NOT for: feature development (use language skills), architecture design (use system-architect).
日本語の概要は準備中です。原文の説明を表示しています。
Structure persuasive speeches and formal arguments in forensic, legal, policy, and competitive debate styles. Use when the user needs to prepare talks, opening or closing arguments, policy pitches, public explanations, debate speeches, or mentions 'forensic speech', 'formal argument', 'persuasive speech structure', 'debate speech', 'opening statement', 'closing argument'. Turns structured claims into audience-tuned persuasive delivery.
日本語の概要は準備中です。原文の説明を表示しています。
Frontend stack decisions, Cloudflare deployment patterns, component systems, and internal tools architecture. Use for framework selection, deployment strategy, design system bridging, shadcn setup. Activate on "frontend architecture", "tech stack", "Cloudflare Pages", "component library", "internal tools", "shadcn setup". NOT for writing CSS (use frontend-developer), design critique (use design-critic), or backend APIs.
日本語の概要は準備中です。原文の説明を表示しています。
Write production-grade Dockerfiles, docker-compose configurations, multi-stage builds, and container optimization. Activate on "Dockerfile", "docker", "docker-compose", "container", "multi-stage build", "docker image", "container optimization", "docker security". NOT for Kubernetes orchestration, cloud-specific container services (ECS, Cloud Run), or CI/CD pipelines (use github-actions-pipeline-builder).
日本語の概要は準備中です。原文の説明を表示しています。
Designing HTTP cache headers that work correctly across browsers, CDNs, and shared proxies — `Cache-Control` directives per RFC 9111, `stale-while-revalidate` and `stale-if-error` per RFC 5861, the Vary header for varying responses, and surrogate keys for tag-based purging. Grounded in IETF RFCs and Cloudflare/Fastly docs.
日本語の概要は準備中です。原文の説明を表示しています。
Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, LoRA training for character consistency, motion graphics generation, and artist commissioning. Activate on 'AI video production', 'script to video', 'video generation pipeline', 'character consistency', 'LoRA training', 'cloud GPU', 'motion graphics', 'Wan I2V', 'InVideo alternative'. NOT for real-time video editing, video compositing (use DaVinci/Premiere), audio production, or 3D modeling (use Blender/Maya).
日本語の概要は準備中です。原文の説明を表示しています。
AI-powered calendar management and agent-based scheduling coordination. Covers calendar APIs (Google Calendar, CalDAV/iCal), AI scheduling assistants (Reclaim, Clockwise, Motion, Cal.com), building custom calendar agents with MCP, multi-calendar merging, timezone management, focus block protection, meeting fatigue detection, and agent-to-agent meeting negotiation protocols. Activate on: "calendar agent", "AI scheduling", "calendar coordination", "meeting scheduling", "calendar API", "focus time protection", "calendar optimization", "Google Calendar MCP", "Reclaim", "Clockwise", "Motion", "Cal.com", "smart scheduling", "calendar-aware agent", "timezone scheduling", "agent negotiation meetings". NOT for: manual calendar UI component design (use form-validation-architect), project management scheduling or Gantt charts (use project-management-guru-adhd), general time-tracking or pomodoro apps (use adhd-daily-planner for time-awareness), building the agent itself from scratch (use agent-creator).
日本語の概要は準備中です。原文の説明を表示しています。
Use when copy-catting, replicating, or adapting features from external systems, repos, apps, or ideas into the current project. Triggers on 'copy this from', 'replicate', 'clone this feature', 'how does X do Y', 'chom', 'like how X does it', 'port from', 'build like', '1:1 copy'. NOT for packing the current project (see mk:pack); NOT for one-shot URL-to-markdown fetches (see mk:web-to-markdown).
日本語の概要は準備中です。原文の説明を表示しています。
Spin up a working LiveAvatar demo from a curated catalog — clones the reference repo, installs dependencies, provisions the LiveAvatar account, and fills the env file, then hands off the parts only a human can do. Use when: (1) User wants to try, test, see, or demo LiveAvatar, (2) User asks what LiveAvatar demos or examples exist, (3) User wants a sales agent / lead-qualification avatar, (4) User wants a LiveKit agent driving a LiveAvatar avatar, (5) User wants an avatar joining their own LiveKit room, (6) User wants a speech-to-speech avatar, a GPT-Live demo, a language-learning or tutor avatar, a customer-support avatar, a poker coach / game-style avatar, or an avatar with on-screen visuals/overlays, (7) User says "run the LiveAvatar demo", "show me LiveAvatar", "get me started with LiveAvatar", or "clone the LiveAvatar example", (8) User is evaluating LiveAvatar and wants something running before writing their own integration.
日本語の概要は準備中です。原文の説明を表示しています。
Prepare, submit and reconcile reviewed Fusion Automation jobs with exact sources, scoped authorization and explicit budgets. Not for arbitrary model-generated cloud scripts.
日本語の概要は準備中です。原文の説明を表示しています。
Turn a reference image or mockup into a working local frontend that matches it closely. Inspects the image, extracts the design system (layout, type, spacing, color, components), implements it, then screenshot-compares and iterates to close the gap. Use when the user says "image to code", "build this mockup", "code this screenshot", "make this design real", or provides a UI image to implement. Part of the Product Design set. Uses a browser tool for screenshot verification.
日本語の概要は準備中です。原文の説明を表示しています。
Resolve a verified cluster of Rembric issues from causal root to evidence-gated closure. Use after systemic triage identifies a shared root, or when the user asks to attack issues at the root, create a mechanism map, plan a deletion-first fix, or close a fixed/stale issue cluster. Use `diagnose` for a single defect whose reproduction is not yet established.
日本語の概要は準備中です。原文の説明を表示しています。
Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
日本語の概要は準備中です。原文の説明を表示しています。
Designs pooled sgRNA libraries for CRISPR knockout, interference (CRISPRi), activation (CRISPRa), Cas12a multiplex, base-editor, and prime-editor screens. Covers on-target scoring (Rule Set 2, Azimuth, DeepSpCas9, CRISPRon), off-target scoring (CFD, MIT), TSS-relative positioning for CRISPRi/a (Horlbeck, Dolcetto, Calabrese), PAM-variant chemistries, control-guide composition, oligo cloning architecture, and library QC. Use when choosing a genome-wide library (GeCKOv2 vs Avana vs Brunello vs TKOv3 vs Inzolia), designing a focused or paralog-focused custom library, picking CRISPRi vs CRISPRa TSS windows, deciding control-guide proportions, or diagnosing library skew and dropout in a freshly cloned pool.
日本語の概要は準備中です。原文の説明を表示しています。
Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.
日本語の概要は準備中です。原文の説明を表示しています。
This skill determines whether a patient using a hybrid closed-loop insulin pump can continue this therapy upon hospital admission. It is triggered by questions such as "Can hybrid closed-loop pump be continued given hospital constraints?"
日本語の概要は準備中です。原文の説明を表示しています。
Run 150+ AI applications in the cloud via the inference.sh platform. Triggers on "generate image with FLUX", "create video", "use Veo/Seedance", "run inference.sh", "infsh CLI", "single key for image+video+LLM". One API key covers image generation (FLUX, Reve, Seedream, Grok, Gemini), video (Veo, Wan, Seedance, OmniHuman, HunyuanVideo), LLMs (Claude, Gemini, Kimi, GLM-4), search (Tavily, Exa), 3D (Rodin), social (Twitter/X), and audio (TTS, voice cloning).
日本語の概要は準備中です。原文の説明を表示しています。
Diagnose why an existing implementation differs from reference evidence using AE/SSIM, pixel, section, computed-style, and transition diffs. Use for post-implementation mismatch or repair guidance; not baseline capture or full clone generation.
日本語の概要は準備中です。原文の説明を表示しています。
Capture baseline evidence from a live website URL: screenshots, scroll states, hover/click behavior, parallax, timers, and transition recordings. Use when reference artifacts are needed before implementation or comparison; not to build or diagnose a clone.
日本語の概要は準備中です。原文の説明を表示しています。
Clone or recreate a live website URL, page, or section as React + Tailwind with extracted DOM, CSS, assets, responsive layout, motion, and interactions. Use for live-URL implementation or fidelity repair; not capture-only or diff-only requests.
日本語の概要は準備中です。原文の説明を表示しています。
Measure, root-cause, fix, verify and record performance contention on a developer machine: cloud-sync daemons (iCloud Drive, OneDrive, Dropbox, Google Drive), file indexers, AI-tool MCP server fleets, and automation browsers left behind by tests and browser skills. Trigger when the machine is slow, apps freeze, browser or MCP tool calls time out, load exceeds the core count, or before and after any UI/UX/performance test run. Includes the L0–L4 optimisation scale and the test-hygiene contract.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level molecular biology knowledge. Use when working with DNA replication, transcription, translation, gene regulation, cloning, PCR, sequencing, CRISPR, epigenetics, or molecular techniques. Also use when the user mentions 'DNA replication', 'transcription', 'translation', 'gene expression', 'PCR', 'cloning', 'restriction enzyme', 'gel electrophoresis', 'Western blot', 'CRISPR', 'epigenetics', 'promoter', 'enhancer', or 'RNA splicing'.
日本語の概要は準備中です。原文の説明を表示しています。