Data & Analytics for Claude Code

Phase 1 of the BigQuery schema optimization pipeline — parses schema export files to count tables and fields, detect naming patterns and type inconsistencies, flag duplicate or nullable issues, and write a markdown analysis report plus strict JSON for phase 2. Use when starting a BigQuery schema audit from raw exports. Trigger with \"run schema phase 1\", \"analyze BigQuery schema\".

Phase 2 of the BigQuery schema optimization pipeline — reads the phase 1 report and schema exports to identify fields with >90% null rates, detect never-queried columns, and produce ranked removal and archival recommendations as a markdown report plus strict JSON for phase 3. Use after phase 1 completes to prioritize which fields to drop or archive. Trigger with \"run schema phase 2\", \"analyze field utilization\".

Phase 3 of the BigQuery schema optimization pipeline — evaluates proposed schema changes from phases 1-2 against dependent queries and systems, categorizes each change by risk level, estimates storage and cost savings, and produces an impact matrix as a markdown report plus strict JSON for phase 4. Use when deciding which field removals are safe to execute. Trigger with \"run schema phase 3\", \"assess schema change impact\".

Runs BigQuery field-utilization shell scripts to empirically validate phase 2-3 conclusions, reconciles manual vs. script findings, and writes a verification report. Use when phase 3 analysis is complete and you need script-backed evidence. Trigger with "run verification", "validate phase 3 findings".

Synthesizes BigQuery schema optimization findings from all prior phases into a prioritized implementation plan with rollback procedures, timelines, and success metrics. Use when all previous phase reports are complete. Trigger with "generate recommendations", "finalize schema optimization plan".

Selects chart types and encodings, designs EDA workflows, and audits existing visualizations for misleading charts, accessibility failures, and wrong library choices. Use when choosing how to visualize a dataset, building a dashboard spec, or catching bad charts in a notebook. Trigger with \"design this visualization\", \"audit our charts\".

> Analyze entire crypto portfolio with allocation, risk metrics, and...

Profile and optimize database queries

Create visual progress updates - charts, before/after comparisons, metrics...

Designs production RAG pipelines covering chunking strategy, embedding selection, retrieval patterns (basic, reranked, hybrid, multi-query), and evaluation metrics. Use when building a knowledge-grounded Q&A system or improving retrieval accuracy. Trigger with "design a RAG system", "help me build a knowledge base".

Designs retrieval reranking pipelines, relevance scoring systems, and learning-to-rank models with rigorous NDCG/MRR evaluation. Use when ranking quality is poor or a reranker is needed. Trigger with \"improve my search ranking\", \"design a reranking pipeline\".

> Comprehensive database replication management with streaming replication,...

Generate comprehensive terminal report of AI experiments

Compiles specialist agent outputs into tiered analytics narratives (mini pulse, daily brief, full deep-dive) in an advisory business voice — never touches raw data. Use when generating a polished analytics report for console, email, or Slack. Trigger with \"generate analytics report\", \"compile analytics brief\".

> Scan for top market movers across crypto, stocks, and forex with real-time...

Designs honest model evaluation frameworks — metric selection matched to business cost functions, statistical significance testing, calibration, and confusion analysis. Use when choosing eval metrics or comparing models. Trigger with \"design a model evaluation framework\", \"compare these models statistically\".

Search AI experiments and display formatted results

> Implement horizontal database sharding for massive scale applications

> Generate optimized SQL queries from natural language descriptions

> Generate optimized SQL queries from natural language descriptions

> Generate production-ready stored procedures and database functions

> Track crypto positions with entry prices, current values, and PnL calculations

> Track real-time prices across crypto, stocks, forex, and commodities with...

> Track crypto wallets across multiple chains with real-time balance and...

Analyzes web traffic source attribution, channel performance, AI referral trends, and redirect domain tracking to explain where visitors come from and why traffic changed. Use when diagnosing channel shifts or measuring AI-referral growth. Trigger with \"analyze traffic sources\", \"why did traffic change\".

Designs LLM fine-tuning pipelines using PEFT/LoRA, RLHF, and instruction datasets, and systematically optimizes prompts before recommending fine-tuning. Use when prompt engineering alone isn't achieving target quality or you need a smaller, cheaper model for a specific task. Trigger with \"design a fine-tuning pipeline\", \"optimize my prompts\".

Implement comprehensive data validation at database and application layers — type, range, format, referential integrity, and custom business-rule checks. Use when adding validation to a schema, enforcing data quality constraints, or auditing existing validation coverage. Trigger with \"add data validation\", \"implement validation rules\".

Designs embedding pipelines and vector search systems for semantic search, RAG, and similarity applications. Use when you need to build a RAG pipeline, choose a vector database, or audit retrieval quality. Trigger with \"design my RAG pipeline\", \"help me choose a vector database\".

Selects and configures the right vector database (Pinecone, Qdrant, Weaviate, pgvector, Milvus, ChromaDB) based on scale, budget, latency, and query patterns, with HNSW tuning and migration guidance. Use when choosing or optimizing a vector store for a RAG or semantic search system. Trigger with "which vector database should I use", "optimize my vector DB".

Adversarially verifies specialist analytics agent outputs — checks every number against raw data, flags hallucinated insights, logical contradictions, and sampling bias before the report reaches the user. Use when quality-gating an analytics pipeline before final delivery. Trigger with \"verify analytics outputs\", \"quality check the report\".

Real-time weather forecast with 7-14 day predictions, temperature,...

Show trending topics on X and curated tech news from 7 sources

Orchestrates YouTube data extraction via Apify actors — channel metadata, video details, search results — polling until complete and saving all datasets to disk. Use when collecting raw YouTube data for strategy analysis. Trigger with "scrape youtube channels", "fetch youtube data".

> Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.

> Query and search the EMBL-EBI Ontology Lookup Service (OLS) for biomedical ontology terms, definitions, and hierarchies across 250+ ontologies (e.g., GO, DOID, HP). Use when the user asks to search for terms, retrieve details, navigate hierarchies (parents, children, ancestors), look up properties and individuals, get autocomplete suggestions, or access ontology metadata and statistics.

> Query the ENCODE Registry of cis-Regulatory Elements (cCREs) via the SCREEN GraphQL API, or make custom queries to the ENCODE Portal REST API for experiments and files (ChIP-seq peaks, etc.). Use when you want to query regulatory annotations or raw experimental data across human cell types.

> Performs 3D structural searches of proteins against various databases (PDB, AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the user provides a physical 3D coordinate file (.cif, .mmcif, or .pdb) and wants to find structurally similar proteins. Do NOT use if the user only provides a protein sequence, gene name, or UniProt ID.