Results for “ce”

Coordinates startup operations by routing CEO, marketing, sales, launch, and social media tasks to specialized sub-skills, using a project knowledge base and frameworks like OKR and RICE.

Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.

Scans repositories for markdown and HTML documentation, classifies files as repo-local or centralizable content, generates an inventory report, and optionally consolidates content into a centralized docs repository.

Provides structured coaching for founders and first-time CEOs, covering archetype identification, delegation frameworks, energy management, calendar audits, leadership evolution, and blind spot identification.

Searches Polish marketplaces (Allegro, Ceneo, Google Shopping) to compare product prices and delivery options, presents a comparison table, and assists with checkout while leaving final payment to the user.

Use to keep localised help centre content current when the source language changes, detect stale translations, and prevent silent lag between markets. Trigger for "translations are out of date", localisation workflow, source of truth language, help centre i18n, translation drift after policy update, or non-English customers seeing old policy.

Automate spreadsheet operations including creating workbooks, writing data, formatting cells, upserting rows, and managing worksheets across Microsoft Excel and Google Sheets.

Sincroniza el registro central de skills con AGENTS.md y registry/AGENT_REGISTRY.md, detectando skills huérfanas o faltantes y auditando el ecosistema.

Embody the voice and comedy methodology of Jo Koy, using his signature techniques and cultural insights to craft humorous, family-centric stories and presentations.

Detect business email compromise (BEC) attacks using email gateway rules, behavioral analytics, and financial process controls.

Machine learning on genomic interval data (BED files) with the geniml Python package — region embeddings (Region2Vec), joint region+metadata embeddings (BEDspace/StarSpace), single-cell ATAC-seq embeddings (scEmbed), consensus peak sets / universes (build-universe), tokenization, BEDshift randomization, and BBClient/BEDbase caching. Use when training or using region/cell embeddings, clustering scATAC-seq, building a tokenization universe from BED collections, or any ML/feature-learning task over genomic regions. NOT for plain interval arithmetic (overlap/intersect/merge counts) — that is gtars, not geniml. Part of the AlterLab Academic Skills suite.

Manage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.

Use when a source must be reached through DergiPark, ULAKBIM TR Dizin, HEAL-Link, YOK Thesis Center, or an institutional library route, when off-campus access fails, or when a lawful retrieval plan is needed for Turkish, Greek, or European materials.

Generates 16:9 horizontal illustrations for Chinese articles using a hand-drawn, black-and-white style with the 'Xiaohei' character as the central figure, based on the article's key concepts.

Short clarifying interview before starting non-trivial engineering work — surfaces the actual requirement, what's explicitly out of scope, and what proves it's done. Use before writing code when the task's requirement, scope, or definition of done isn't already unambiguous. Not for trivial or fully-specified changes — that's ceremony, not clarity.

Esta habilidade deve ser usada ao trabalhar com LaminDB, um framework de dados de código aberto para biologia que torna dados consultáveis, rastreáveis, reproduzíveis e FAIR. Use ao gerenciar datasets biológicos (scRNA-seq, espacial, citometria de fluxo, etc.), rastrear workflows computacionais, curar e validar dados com ontologias biológicas, construir data lakehouses, ou garantir linhagem de dados e reprodutibilidade em pesquisa biológica. Aborda gerenciamento de dados, anotação, ontologias (genes, tipos de célula, doenças, tecidos), validação de esquema, integrações com orquestradores de workflow (Nextflow, Snakemake) e plataformas MLOps (W&B, MLflow), e estratégias de deployment.