Document Skills

Guidelines for structuring and documenting Jupyter notebooks for reproducibility and clarity.

Guide to analyze multiple documents (PDF, DOCX) against user-defined columns and produce a structured Excel output with citations. Use when the user wants to: (1) Extract specific information from multiple documents into a table, (2) Compare clauses or provisions across contracts, (3) Create a document review matrix with source citations. Triggers on: 'tabular review', 'document matrix', 'extract from documents', 'compare across documents', 'review multiple contracts'.

Analyzes sessions to extract patterns, preferences, and learnings. Use when you want to reflect on this session, capture what worked, document discoveries, or do a retrospective. Triggers on: what did we learn, session summary, reflect on session, capture insights, remember this session.

Generate Architecture Decision Records with AI. Use when documenting technical decisions.

Visualizes document relationships, identifies orphaned documents, and suggests missing connections.

Generate Architecture Decision Records with AI. Use when documenting technical decisions.

Generate Architecture Decision Records with AI. Use when documenting technical decisions.

Mermaid diagram generation for architecture visualization, data flow diagrams, and component relationships. Use for documentation, PR descriptions, and architectural analysis.

Materialize documentation for SQL syntax, data ingestion, concepts, and best practices. Use when users ask about Materialize queries, sources, sinks, views, or clusters.

Google Docs/Sheets management via ACSet condensation. Transforms documents into GF(3)-typed Interactions, tracks comments/cells, detects saturation when all comments resolved. Use for document workflows, spreadsheet automation, or applying ANIMA principles to Workspace documents.

Analytics engineering for reliable metrics and BI readiness. Build transformation layers, dimensional models, semantic metrics, data quality tests, and documentation. Use when you need dbt or SQL transformation strategy, metrics definition, or analytics data modeling.

Use this skill when asked to write, create, or help with KQL (Kusto Query Language) queries for Microsoft Sentinel, Defender XDR, or Azure Data Explorer. Triggers on keywords like "write KQL", "create KQL query", "help with KQL", "query [table]", "KQL for [scenario]", or when a user requests queries for specific data analysis scenarios. This skill uses schema validation, Microsoft Learn documentation, and community examples to generate production-ready KQL queries.

Data quality validation skill using Great Expectations for schema validation, expectation suites, data documentation, and automated data quality checks in ML pipelines.

Master AI-powered natural language data exploration with Lumen AI. Use this skill when building conversational data analysis interfaces, enabling natural language queries to databases, creating custom AI agents for domain-specific analytics, implementing RAG with document context, or deploying self-service analytics with LLM-generated SQL and visualizations.

Generate human-readable report from Intent files. Converts technical Intent specs into readable documents for stakeholders, team members, or documentation. Supports multiple output formats.

Generate comprehensive work summaries from daily notes or conversation context. Use for performance reviews, project retrospectives, or documenting completed work with timeline and impact.

Manage architectural decisions and insights in memory.jsonl. Use when you need to document strategic decisions, lessons learned, or architectural insights.

Generate comprehensive work summaries from daily notes or conversation context. Use for performance reviews, project retrospectives, or documenting completed work with timeline and impact.

Generate detailed architectural descriptions of IT systems from short prompts. Produces structured output with overview, components list, connections/integrations, and ASCII diagrams with annotated arrows. Use when user asks to describe, explain, or document architecture of any IT system - specific platforms (Camunda, Kafka, Kubernetes), cloud services (AWS, GCP, Azure), databases, microservices, or custom systems.

Expert in aggregating, processing, and synthesizing information from multiple sources into coherent insights. Use when building knowledge graphs, ontologies, RAG systems, or extracting insights across documents. Triggers include "knowledge graph", "ontology", "synthesize information", "GraphRAG", "insight extraction", "cross-document analysis".

Framework for creating session summary documents. Use when user says "daily summary", "generate summary", or similar. Provides structured markdown template with date verification, filename patterns, and formatting guidelines. Supports range-based naming for sessions spanning calendar boundaries. Extend with personal metrics and domain-specific content.

Connect to PostgreSQL, MySQL, or SQLite databases to explore schema structure, table relationships, and generate ERD diagrams. Use when the user asks to explore a database, document schema, or understand table relationships.

This skill should be used when the user asks about "Tabular Editor documentation", "TE docs", "how to do X in Tabular Editor", "Tabular Editor features", "TE3 features", "C# scripts in Tabular Editor", "DAX scripts", "workspace mode", or needs to search Tabular Editor documentation. Provides efficient local search of TabularEditorDocs repository instead of unreliable web fetching.

Use when ready to document findings, generate a report, or summarize binary analysis results. Compiles analysis findings into structured reports - correlates facts from triage/static/dynamic phases, validates hypotheses, generates documentation with evidence chains. Keywords - "summarize findings", "generate report", "document analysis", "what did we find", "write up results", "export findings

Master AI-powered natural language data exploration with Lumen AI. Use this skill when building conversational data analysis interfaces, enabling natural language queries to databases, creating custom AI agents for domain-specific analytics, implementing RAG with document context, or deploying self-service analytics with LLM-generated SQL and visualizations.

Analyze unknown or inherited Excel files to understand what they do, document their purpose, audit formulas for errors, and assess maintainability risk. Use when: (1) User uploads an Excel file asking 'what does this do?', (2) User needs to understand an inherited/legacy spreadsheet, (3) User wants formula auditing or error detection, (4) User asks about spreadsheet risk, complexity, or documentation, (5) User mentions 'inherited', 'legacy', 'undocumented', or 'someone left' regarding Excel file

Use when ready to document findings, generate a report, or summarize binary analysis results. Compiles analysis findings into structured reports - correlates facts from triage/static/dynamic phases, validates hypotheses, generates documentation with evidence chains. Keywords - "summarize findings", "generate report", "document analysis", "what did we find", "write up results", "export findings

Generate compliance reports from OSCAL assessment results, SSPs, and POA&Ms in various formats. Use this skill to create audit-ready documentation, executive summaries, and detailed compliance status reports.

Logs and scores skill usage quality, tracking output effectiveness, user satisfaction signals, and improvement opportunities. Expert in skill analytics, quality metrics, feedback loops, and continuous improvement. Activate on "skill logging", "skill quality", "skill analytics", "skill scoring", "skill performance", "skill metrics", "track skill usage", "skill improvement". NOT for creating skills (use agent-creator), skill documentation (use skill-coach), or runtime debugging (use debugger skill

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

Generate structured comparisons and decision matrices across analyzed frameworks. Use when (1) comparing multiple frameworks or approaches side-by-side, (2) making architectural decisions between alternatives, (3) creating best-of-breed selection documentation, (4) synthesizing findings from multiple analysis skills into actionable decisions, or (5) producing recommendation reports for technical stakeholders.

Extract tables from PDFs and images to CSV or Excel. Support for scanned documents with OCR, multi-page PDFs, and complex table structures.

This skill generates interactive timeline visualizations using the vis-timeline JavaScript library. Use this skill when users need to create historical timelines, project timelines, event sequences, or any chronological data visualization with optional category filtering. The skill creates a complete MicroSim package with HTML, CSS, JSON data, and documentation.

Expert documentation generation for golden layers. Detects SCD types, documents business rules, metric definitions, aggregation logic, and data quality scoring. Use when documenting golden layer tables.

Expert documentation generation for staging transformation layers. Auto-detects SQL engine (Presto/Trino vs Hive), documents transformation rules, PII handling, deduplication strategies, and data quality rules. Use when documenting staging transformations.

Generates professional performance analysis reports from SDL3 HammerEngine benchmark results including statistical analysis, comparison tables, visualizations, and recommendations. Use when preparing performance documentation, analyzing optimization efforts, or generating milestone/release reports.

Create comprehensive HTML architecture diagrams showing data flows, business objectives, features, technical architecture, and deployment. Use when users request system architecture, project documentation, high-level overviews, or technical specifications.

Map workflows, extract SOPs, and identify automation opportunities through systematic process capture and AI tractability assessment. Use when documenting workflows, creating SOPs, conducting process discovery interviews, or analyzing automation opportunities. Grounds the SOP-first doctrine in tacit knowledge documentation and structured analysis.

Generate project assessment markdown documents from JSON data with WHY/WHO/WHAT

Comprehensive Microsoft Excel (.xlsx) document creation, editing, and