bundled/skills/document-skills/SKILL.md
Umbrella skill for document workflows (PDF/DOCX/XLSX/PPTX). Dispatches to the most specific document skill to reduce noise and improve routing precision.
npx skillsauth add foryourhealth111-pixel/vco-skills-codex document-skillsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill when the task is clearly “document work” but the exact format is not yet fixed, or when the user mixes multiple formats (e.g., “把论文里的表格做成 Excel,再导出 PDF 报告”).
Goal: fast dispatch to the most specific skill so we keep high hit-rate / low noise.
.pdf, “PDF”, “pypdf”, “pdfplumber”, “render pages”).docx, “Word”, “tracked changes”, “python-docx”).docx formatting/layout heavy and the doc skill is requested/required by your environment)..xlsx, .csv, .tsv, “Excel”, “openpyxl”, “pivot table”).pptx, “slides”, “poster”, “deck”, “PowerPoint”)development
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, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.
development
Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.
development
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.
development
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.