Loading...
Loading...
Found 50 Skills
Query and analyze a Dynatrace tenant's ACTUAL billing and usage data with DQL against dt.system.events — DPS consumption breakdown, cost-normalized spend ranking, included volume deduction, chargeback/showback, cost drivers, spending trends, cost investigation, metrics ingest optimization, query cost attribution, workflow total cost, and entity-level cost drill-down (RUM, hosts, synthetic, K8s). Also directs licensing/entitlement questions to the right resource (not available via DQL). USE ONLY to query/analyze the tenant's actual consumption. Do NOT use for conceptual 'explain' questions about how DPS billing/pricing works or what units/weights/the rate card mean — those belong to Dynatrace documentation. Also do NOT use for making a DQL query itself faster or cheaper to run (query optimization, reducing scanned data/consumption per run, filter-early best practices) — that belongs to dt-dql-essentials. This skill only MEASURES recorded consumption; it does not tune queries.
Instructions for using the DeepBase multi-driver persistence library. Use when a task requires data persistence, storage abstraction, multi-backend setups, data migration between drivers, or integrating DeepBase into a Node.js project.
Helps a founder build the case for raising prices and the moves that justify it; it drives toward a higher price and does not debate whether to raise. Three gated phases: (1) collect the reality (what you charge, what you promise, who buys) and diagnose which market the price has selected (the $1/$10/$100/$1,000-per-month ladder), the profit stakes (a 10% rise can be ~100% more profit), and whether the low price is strategy or fear, landing on a rough higher target; (2) brainstorm, judgment off, moves that justify a higher price — move up a market rung, price on value created not cost saved, build Love and Utility drivers, differentiate, repackage; (3) select, grilling each move down to a few that are good, strategy-consistent, buildable, and wanted. Load when the user asks how much to raise prices, what it would take to charge more, or why their price feels too low. Do NOT load to set the exact price, write the increase letter, define the ideal customer, or choose among the three pricing strategies.
Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD). Decades of experience writing reliable, optimized, and maintainable embedded code with deep expertise in memory barriers, DMA/cache coherency, interrupt-driven I/O, and peripheral drivers.
Decompose financial variances into drivers with narrative explanations and waterfall analysis. Use when analyzing budget vs. actual, period-over-period changes, revenue or expense variances, or preparing variance commentary for leadership.
Generate deep research reports on prediction market events using the Octagon Prediction Markets Agent. Combines real-time Kalshi market data with AI-driven analysis to surface price drivers, compare market vs. model probabilities, and identify potential mispricings across 120+ active markets.
Complete knowledge domain for Cloudflare Hyperdrive - connecting Cloudflare Workers to existing PostgreSQL and MySQL databases with global connection pooling, query caching, and reduced latency. Use when: connecting Workers to existing databases, migrating PostgreSQL/MySQL to Cloudflare, setting up connection pooling, configuring Hyperdrive bindings, using node-postgres/postgres.js/mysql2 drivers, integrating Drizzle ORM or Prisma ORM, or encountering "Failed to acquire a connection from the pool", "TLS not supported by the database", "connection refused", "nodejs_compat missing", "Code generation from strings disallowed", or Hyperdrive configuration errors. Keywords: hyperdrive, cloudflare hyperdrive, workers hyperdrive, postgres workers, mysql workers, connection pooling, query caching, node-postgres, pg, postgres.js, mysql2, drizzle hyperdrive, prisma hyperdrive, workers rds, workers aurora, workers neon, workers supabase, database acceleration, hybrid architecture, cloudflare tunnel database, wrangler hyperdrive, hyperdrive bindings, local development hyperdrive
Help users define the strategic context for their product by identifying the right competitive alternatives, unique value drivers, and target segments to win a market category.
Install ADBC (Arrow Database Connectivity) drivers with dbc. Use when the user wants to install database drivers and connect to databases.
Build employee turnover prediction models to identify flight risk and retention drivers. Use this skill when the user needs to predict which employees are likely to leave, identify retention risk factors, or prioritize HR interventions — even if they say 'attrition prediction', 'who is going to quit', or 'employee retention model'.
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, detect outliers, find key drivers, or leverage generative AI capabilities in BigQuery.
Builds, configures, debugs, and optimizes AWS observability using CloudWatch (Logs Insights, Metrics, Alarms, Dashboards, EMF), X-Ray, CloudTrail, and ADOT. Covers Log Insights query syntax (fields, filter, stats, parse, pattern, join, subqueries), alarm configuration (metric, composite, anomaly detection, missing data treatment), dashboard design, custom metrics (PutMetricData, EMF, metric filters), X-Ray tracing (ADOT, sampling rules, annotations vs metadata), ADOT collector config, and CloudTrail auditing. Use when the user mentions CloudWatch, Log Insights, alarms, INSUFFICIENT_DATA, dashboards, custom metrics, EMF, X-Ray, traces, sampling, CloudTrail, who deleted, ADOT, OpenTelemetry, observability, monitoring, synthetics, canaries, or troubleshooting alarm behavior. Do NOT use for application logging setup, container log drivers, or security threat detection.