Cosmos DB applications require correct authentication, partitioning, queries, and throughput choices. This skill provides practical Python SDK patterns for common NoSQL workflows.

Manual image inspection limits scale. This skill guides Azure AI Vision workflows for captions, OCR, objects, people, and smart crops.

Building reliable NLP workflows requires correct SDK setup and operation selection. This skill provides practical Python patterns for Azure AI Language text analysis.

Document extraction workflows require precise Azure REST SDK patterns and asynchronous operation handling. This skill provides practical TypeScript guidance for analysis, classification, and custom models.

Documents and media are difficult to convert into consistent, searchable data. This skill guides Python workflows using Azure AI Content Understanding analyzers and structured results.

Time-series monitoring requires reliable patterns for detecting unusual behavior. This skill provides Java examples for Azure AI client setup, analysis, training, inference, and model management.

Unclear events and inconsistent conversions make analytics difficult to trust. This skill creates decision-focused measurement plans, quality scores, validation steps, and governance guidance.

Amplitude workflows require careful tool lookup, ID resolution, and status checks. This skill guides Claude, Codex, and Claude Code through Rube MCP tool sequences for common Amplitude tasks.

Airflow pipelines often fail because dependencies, retries, sensors, and tests are designed inconsistently. This skill provides reusable patterns for production DAG design and validation.

Weak experiment design creates misleading results and wasted traffic. This skill applies hypothesis, metrics, sample size, tracking, execution, and analysis gates before decisions.

Choosing the wrong chart can hide or distort important data patterns. This skill helps Claude, Codex, and Claude Code select chart types, improve dashboards, and explain visualization choices.

Data work often needs clear queries, repeatable transformations, and careful interpretation. This skill guides SQL, pandas, statistics, and data cleaning workflows.

Manual web research and scraping can be slow and inconsistent. This skill guides Claude, Codex, and Claude Code through ScrapeGraph CLI workflows.

Agents often lose useful lessons from prior tasks. This skill shows how to store, judge, retrieve, and distill reasoning patterns with AgentDB-backed ReasoningBank.

AgentDB teams need faster vector search and lower memory use as datasets grow. This skill provides tuning guidance for quantization, HNSW indexing, caching, batching, and monitoring.

Recoup data and connected services require precise authentication, identifiers, and endpoint schemas. This skill guides reliable retrieval and approved external actions.

Agents often need spreadsheet logic without controlling Excel. This skill guides MCP and TypeScript workflows for WorkPaper formulas, file-backed edits, and local XLSX formula reports.

Agent teams need repeatable evidence before comparing models. PinchBench runs real-world OpenClaw tasks, grades outcomes, and can publish results to a leaderboard.

DEX research often requires several data sources and command formats. This skill routes read-only market, token, wallet, social, and live signal queries through Onchain OS.

Neon projects require careful choices for connections, migrations, scaling, and recovery. This skill provides focused guidance for dependable Postgres workflows on Neon.