'vision' 검색 결과

Unsupervised clustering and cell-type identification for high-dimensional flow, spectral, and mass cytometry - FlowSOM, PhenoGraph, FlowSOM-via-CATALYST, with UMAP/tSNE for visualization. Covers the type-vs-state marker distinction (cluster on lineage, test state within clusters), over-provision-then-metacluster, the Weber-Robinson benchmark, seed dependence and metacluster stability, why embeddings are for looking not measuring, and median-heatmap annotation/merging. Use when discovering populations without predefined gates, choosing a clustering algorithm, selecting the number of metaclusters, or annotating clusters into cell types.

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Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species ortholog/paralog calls. Use when pulling Ensembl-native data (Ensembl Gene IDs, version-pinned releases, archive endpoints for reproducibility), gene/transcript/exon structure with stable IDs, or VEP for variant annotation. Encodes the 15 req/sec rate limit, archive (e110.rest.ensembl.org) for reproducibility, Ensembl divisions (vertebrates / plants / fungi / metazoa / bacteria), and the symbol-vs-ID stability problem.

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Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.

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Automated cell behavior analysis from microscopy or XR lab recordings. Classifies cell motion phenotypes (migration, proliferation, apoptosis, division, quiescence), computes population-level quantitative metrics (growth rate, migration velocity, directionality index), and emits structured JSON for downstream reporting, plotting, or ELN integration.

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Process images, video, audio, PDFs with Gemini API. Generate images (Nano Banana 2), videos (Veo 3), speech (MiniMax TTS), music (MiniMax). Convert documents to Markdown. Multi-provider fallback (Gemini → MiniMax → OpenRouter). Activate when task references media files, asks to analyze/describe/transcribe/extract/generate/convert, or involves non-text binary files.

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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.

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Own the lifecycle of short-lived paid CPU/GPU hosts and attached resources, from bounded provisioning through verified permanent deletion. Use when renting, extending, retiring, or recovering billable remote resources; campaign scheduling belongs to run-ephemeral-hosts.

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Offload builds, tests, or artifact verification to authorized SSH hosts and isolated worktrees; synchronize remote fixes into dedicated coordinator commits and preserve reproducible build provenance. Use for spare development capacity and remote build troubleshooting. Paid provisioning requires a separate resource lifecycle contract.

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Determines if PAC/PRA ratio and PAC levels indicate positive or provisionally positive screening for primary aldosteronism. Triggered when a clinician has PAC and PRA results and asks “Is this screening test positive for PA?” or needs to interpret borderline results.

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Propose the next dependency-ready sprint from the ALREADY-DECOMPOSED roadmap — standup's active sibling. Reads docs/roadmap-execution-plan.md + the memory backlog, computes per-task readiness from the roadmap's machine-readable status, orders with roadmap-planner's graph engine, and emits a proposed task-set (sprint-plan manifest shape) with per-feature done-criteria, excluding unready tasks and naming their unmet prerequisite. PROPOSES ONLY — the human confirms/edits before /triage routes it (typically to the `power` track). Distinct from `sprint-plan`, which decomposes a fresh vision.

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Decompose an MVP vision into a sprint manifest — a prioritized feature list where every feature carries explicit done-criteria (a done-record reference, named edge tests, and a wiring test). Produces the sprint manifest that `sprint-oracle` checks for completeness. Use when planning a sprint of parallel work (Slice A of the sprint-mode epic). Not a workflow phase; the manifest it writes is the completeness contract a sprint is held to.

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Auri: assistente de voz inteligente (Alexa + Claude claude-opus-4-20250805). Visao do produto, persona Vitoria Neural, stack AWS, modelo Free/Pro/Business/Enterprise, roadmap 4 fases, GTM, north star WAC e analise competitiva.

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Audits and designs iOS/macOS/watchOS/visionOS interfaces against the Apple Human Interface Guidelines, including the Liquid Glass design language (announced WWDC25, shipped with iOS 26/macOS Tahoe, Sept 2025). Use when reviewing an Apple-platform mockup or app for HIG compliance, checking contrast or tap-target sizes, or designing native-feeling Apple UI (e.g., 'audit my iOS app against the HIG', 'is this text readable on Liquid Glass?').

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Challenge vision alignment, value, cost, risk and operating ownership at material scope or release decisions.

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Maintain vision, user journeys, evolving requirements and roadmap outcomes when intent or acceptance changes.

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Expert-level concrete design covering reinforced concrete beams, columns, slabs, footings, retaining walls, ACI 318 code provisions, and durability.

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Expert-level cell biology knowledge. Use when working with cell structure, organelles, cell signaling, cell cycle, cell division, cytoskeleton, membrane biology, vesicular trafficking, apoptosis, or cell biology techniques. Also use when the user mentions 'organelle', 'mitochondria', 'endoplasmic reticulum', 'Golgi', 'cytoskeleton', 'cell cycle', 'mitosis', 'meiosis', 'apoptosis', 'signal transduction', 'membrane potential', 'endocytosis', or 'cell migration'.

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Identify and add new AnimeGameData field deobfuscation mappings by comparing cleartext and obfuscated AGD revisions. Use when a new Genshin Impact build changes obfuscated JSON field names or when rust/istaroth-agd-regen/src/deob.rs needs a new version mapping block.

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[Workflow] Turn an idea or existing canonical specs into a reviewed provisional spec or reviewed, readiness-checked, prioritized planned tasks and stories; stop before implementation. --from=idea|spec --to=spec|tasks.

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Use when writing Terraform — AWS modules, resources, variables, outputs, remote state — even when the user just says 'provision this infra' or 'add an S3 bucket' without naming Terraform.

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Use when working with Laravel queues in production — Horizon dashboard, worker supervision, job metrics, balancing strategies — even when the user just says 'my jobs are piling up'.

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Form a committee of two high-reasoning agents to step back, do root cause analysis, and produce a plan. Use when stuck, looping, tunnel-visioning, or facing a hard planning problem.

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Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar third-party dashboard, or running a one-off migration or cutover. Don't invoke this for steps the agent can perform itself.

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Fine-tune LLMs and VLMs using Unsloth on HF Jobs (Hugging Face on-demand cloud GPUs). Use when users want to fine-tune language models, train VLMs (Vision Language Models), do continued pretraining, domain adaptation, or run UV scripts on HF Jobs. Triggers on requests involving Unsloth training, HF Jobs GPU training, Qwen3-VL fine-tuning, Gemma VLM training, or LoRA fine-tuning on cloud GPUs.

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