可审查、可复用的 Agent Skills

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When the user wants to design, launch, or optimize an in-app referral / invite / share-to-earn program — including reward structure, mechanics, fraud prevention, deep link setup, and viral coefficient measurement. Use when the user mentions "referral program", "invite a friend", "refer and earn", "share to earn", "viral loop", "viral coefficient", "K-factor", "double-sided rewards", "give X get X", "referral rewards", "invite link", "share sheet", "Branch referrals", "in-app invites", or "how to make my app go viral". For deep link infrastructure that referrals depend on, see attribution-setup. For organic content-driven virality (UGC, creator), see creator-ugc-marketing.

Token-saving terse mode — no filler, no narration, just results

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Build clinical/healthcare deep-learning pipelines with PyHealth — loading EHR/signal/imaging datasets (MIMIC-III/IV, eICU, OMOP, SleepEDF, ChestXray14, EHRShot), defining tasks (mortality, readmission, length-of-stay, drug recommendation, sleep staging, ICD coding, EEG events), instantiating models (Transformer, RETAIN, GAMENet, SafeDrug, MICRON, StageNet, AdaCare, CNN/RNN/MLP), training with the PyHealth Trainer, computing clinical metrics, and using medical code utilities (ICD/ATC/NDC/RxNorm lookup and cross-mapping). Use this skill whenever the user mentions PyHealth, MIMIC, eICU, OMOP, EHR modeling, clinical prediction, drug recommendation, sleep staging, medical code mapping, ICD/ATC codes, or any healthcare ML pipeline that fits the dataset → task → model → trainer → metrics pattern, even if "PyHealth" isn't named explicitly.

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Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA.

When the user wants to run display, banner, or ad network campaigns. Also use when the user mentions "display ads," "banner ads," "ad network," "ad alliance," "programmatic display," "native ads," or "retargeting display." For strategy, use paid-ads-strategy.

Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.

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When the user wants to design, optimize, or audit website footers. Also use when the user mentions "footer," "page footer," "site footer," "footer links," "footer navigation," "footer SEO," "footer design," "footer CTA," "multi-column footer," or "footer sitemap." For main nav, use navigation-menu-generator.

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Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, visualization, and converting R-friendly single-cell formats such as Seurat or SingleCellExperiment RDS files into h5ad for Scanpy. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.

Production deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.

Use this skill when the user asks to "investigate incident", "triage this alert", "what's firing", "who got paged", "incident response", "check incident status", "SLO breaching", "error budget burned", "check service level", "SLI status", "who was notified", "check notification delivery", "verify alert routing", "MTTR", "incident severity", "error budget", "burn rate", "acknowledge incident", "resolve incident", "production incident", "what alerts are active", "incident timeline", "on-call triage", or wants to triage, manage, or respond to incidents using alerts, SLOs, and notifications.

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