Explorar skills

Scaffold a GitHub agentic workflow from an existing skill

Expertise in product management lifecycle, from ideation to launch. Covers requirements gathering, user story creation, prioritization, and product strategy. Use this skill for product planning, writing PRDs, defining MVPs, or competitive analysis.

维护孩子的纵向画像三件套(weakness-profile / strengths / interests)。把零散观察提炼成 pattern,让 agent 在每次新对话开始时就知道孩子最近在哪些方向卡住、强在哪些方向、对什么感兴趣。当 daily-report 收尾时、weekly-report 跑完时、或对话里出现新观察时使用。

Modelagem Molecular com NumPy

Da Variação de DNA à Estrutura Proteica: AlphaFold2, AlphaFold3, RoseTTAFold com NumPy

Scaffold an advanced stateful agent skill with L4 patterns

Reference checklist for Basic Memory note quality — rules preventing self-referential content in subject-domain notes (the fourth-wall anti-pattern). Preloaded into knowledge-maintainer and knowledge-gardener agents via the skills frontmatter field.

Análise de redes biológicas, utilizando redes PPI do STRING, métricas de grafo NetworkX e detecção de comunidades Louvain. Realiza enriquecimento GO por módulo, exportação para Cytoscape e inferência de redes regulatórias gênicas com GENIE3.

Poll Telegram for new messages and write parsed task actions into the user's Notion Tasks DB. Handles "<N> done", "<N> push <day>", "<N> drop", "add: <text> [P<n>] [<n>min] [#type]", "morning <hours>", and free-form natural-language adds like "remind me to email a coauthor by Wednesday". Use this skill whenever the user says /capture, asks to check Telegram, says "process my replies", "did I get a

Modelos de Fundação Genômicos: Nucleotide Transformers, HyenaDNA e Evo com NumPy.

This skill should be used when the user asks to audit, health-check, or structurally validate one or more SPECIFIC named notes or a bounded topic cluster — 'audit these notes', 'check this note for orphans or broken links', 'fourth-wall check on [note]', 'validate the structure of [note]', 'spot-check [note]'. Runs a read-only audit inline. NOT for fixing issues (use /knowledge-maintain), NOT for

Aprendizado de máquina em bioinformática, abordando engenharia de características para sequências, classificação de promotores, divisões de treino/teste, regressão logística, floresta aleatória e armadilhas bioespecíficas.