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Found 858 Skills
Fetch Oura Ring sleep data using the ouraclaw CLI. Use when the user asks about their sleep score, sleep data, sleep stages, HRV, heart rate during sleep, bedtimes, or any Oura Ring data. Triggers on "sleep score", "how did I sleep", "oura data", "sleep data", "last night's sleep", "sleep quality", "HRV", or any request for Oura Ring metrics.
Use when the user needs to inspect Google Cloud (GCP) logs, metrics, and monitoring signals via gcloud for incident triage, debugging, or operational analysis. Supports Cloud Logging queries, Cloud Monitoring time-series reads, and environment checks for a target project.
Choose the right metrics for a LaunchDarkly experiment, guarded rollout, or release policy. Use when the user wants to know which metrics to use, which is the primary metric for an experiment, what guardrails to add, or which events to monitor in a rollout. Surfaces what will auto-attach from existing release policies before making additional recommendations.
Configures best-practice alerting policies for Google Cloud Vertex AI / Agent Platform agents on Agent Runtime. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, and quality metrics (response quality, tool use, hallucination). Also use when provisioning online monitors for quality evaluation, or analyzing live metrics traffic footprints. NOTE: This skill currently only works for the Agent Runtime. Don't use for configuring general GCP alert policies or non-agent GCP alerting policies.
Use when building cloud-native apps. Keywords: kubernetes, k8s, docker, container, grpc, tonic, microservice, service mesh, observability, tracing, metrics, health check, cloud, deployment, 云原生, 微服务, 容器
Time-series database implementation for metrics, IoT, financial data, and observability backends. Use when building dashboards, monitoring systems, IoT platforms, or financial applications. Covers TimescaleDB (PostgreSQL), InfluxDB, ClickHouse, QuestDB, continuous aggregates, downsampling (LTTB), and retention policies.
Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.
Jungle Scout Keyword Expansion Tool: Expands a seed keyword into a list of related keywords with data such as search volume, trends, PPC bids, ranking difficulty, etc., covering 10 Amazon marketplaces including the US, UK, Germany, Japan, etc. This skill is triggered when users mention keyword expansion, keyword mining, long-tail keyword mining, related keywords, keyword suggestions, keyword expansion, PPC bid research, keyword competition, keyword discovery, Jungle Scout keywords, or terms like keyword expansion, keyword discovery, keyword scout, related keywords, long-tail keywords, keyword suggestions, PPC bid research, keyword competition, seed keyword expansion, keyword mining. Even if users do not explicitly mention "Jungle Scout", this skill should be triggered as long as their needs involve finding more related keywords and their metrics such as search volume and competition starting from a seed keyword.
Help users improve retention and engagement metrics. Use when someone is dealing with churn, optimizing activation flows, building habit-forming products, or trying to increase user engagement and lifetime value.
Measure what matters with proper event tracking, funnels, cohorts, and metrics. Use when setting up analytics, tracking features, or understanding behavior.
Analyze digital assets including cryptocurrency fundamentals, blockchain mechanics, DeFi protocols, and on-chain metrics. Use when the user asks about crypto investing, Bitcoin, Ethereum, staking yields, DeFi lending, impermanent loss, or on-chain valuation metrics. Also trigger when users mention 'blockchain', 'proof of stake', 'proof of work', 'smart contracts', 'NFTs', 'stablecoins', 'NVT ratio', 'TVL', 'crypto portfolio allocation', 'halving', or ask about risks and returns of cryptocurrency.
Compute and compare investment return metrics including TWR, MWR/IRR, CAGR, and annualized returns. Use when the user asks about portfolio performance calculation, comparing manager returns, linking sub-period returns, understanding why different return methods give different numbers, or converting returns across time periods. Also trigger when users mention 'how much did I make', 'annual return', 'compound growth', 'dollar-weighted vs time-weighted', 'what was my rate of return', 'geometric vs arithmetic mean', 'log returns', or ask about the effect of cash flows on reported returns.