Explorar skills

Operate and extend NanoClaw v2, ECC's zero-dependency session-aware REPL built on claude -p.

Orquestração do Ciclo de Vida do Produto. Acionada por termos como "Product Lifecycle Orchestrator", "design de produto" ou "PRD", esta skill identifica a intenção, seleciona o ponto de entrada do ciclo de vida e executa especificações (PRD/UED/Tech/Test), gráficos de ciclo de vida, análise de impacto e portões de iteração.

When the user wants help writing opening lines, hooks, or first sentences that grab attention. Also use when the user mentions 'hook,' 'opening line,' 'first line,' 'scroll stopper,' 'attention grabber,' 'headline,' 'how to start my post,' or 'nobody reads past my first line.' Can be used standalone or invoked by other creation skills. For writing full posts, see post-writer-sms. For threads, see

This skill should be used when the user asks to "understand context", "explain context windows", "design agent architecture", "debug context issues", "optimize context usage", or discusses context components, attention mechanics, progressive disclosure, or context budgeting. Provides foundational understanding of context engineering for AI agent systems.

Visualize biological networks (PPI, gene-regulatory, co-expression, pathway) with layout algorithm choice (ForceAtlas2, Fruchterman-Reingold, Kamada-Kawai, hive plots), edge bundling, community-based coloring, and reproducible seeds using NetworkX, PyVis, igraph, and Cytoscape automation. Use when rendering biological networks for static publication, interactive HTML exploration, or Cytoscape-form

Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

Implement OpenAI Harness Engineering practices in any repository — AGENTS.md, PLANS.md, deterministic smoke/test/lint harness commands, strict architecture boundaries, observability from day 1, and entropy-control audits for reliable autonomous agent runs.

Use quando o usuário pede para analisar SERPs; revisa fatores de ranqueamento, funcionalidades, intenção, AI Overviews e snippets.

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, L

Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.

What to go scorched-earth on — a directory or file path, a URL, or a topic/question. Omit to use the current project or ask.

O Ask GraphQL MCP lida com perguntas Web3 e on-chain via endpoints GraphQL (ex: SubQuery/SubGraph). Ele é acionado para solicitações de blockchain/Web3 como métricas, atividade de protocolo ou análise de tokens, utilizando o graphql_agent com a entrada em linguagem natural do usuário.