全部能力

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML,…

Creates a complete Amazon Aurora database cluster with instances, handling cluster creation, instance provisioning, and Secrets Manager password management in…

Exports Amazon RDS or Aurora database snapshots to Amazon S3 in Apache Parquet format for analytics, backup, or data migration. Handles snapshot selection or…

OpenClaw stock analysis skill for US/HK/CN markets. Combines QVeris data sources (THS, Caidazi, Alpha Vantage, Finnhub, X sentiment) for quote, fundamentals,…

Grafana Cloud infrastructure monitoring — Kubernetes monitoring, cloud provider integrations (AWS, Azure, GCP), host and container monitoring, infrastructure dashboards, and collector setup. Use when setting up Kubernetes monitoring, connecting cloud provider metrics, configuring node exporter or cAdvisor, setting up infrastructure dashboards, or using the k8s-monitoring Helm chart.

Grafana Cloud Database Observability — query-level performance insights for MySQL and PostgreSQL. Covers setup with Grafana Alloy, query samples, visual explain plans, RED metrics, pg_stat_statements and Performance Schema integration, and correlation with application traces. Use when monitoring database performance, diagnosing slow queries, setting up database observability for MySQL or PostgreSQL (self-managed, RDS, Aurora, Azure, Cloud SQL), or correlating DB metrics with APM data.

Diagnose and fix bugs with root-cause analysis and verification. Use when you have a concrete issue report, failing behavior, runtime error, or test regression…

Grafana Cloud private network connectivity — AWS PrivateLink, Azure Private Link, and GCP Private Service Connect. Send telemetry (metrics, logs, traces, profiles) to Grafana Cloud without traversing the public internet. Eliminates cloud egress costs, meets compliance requirements (PCI-DSS, HIPAA). Use when setting up secure private telemetry ingestion from AWS/Azure/GCP, reducing egress costs, or meeting data residency/compliance requirements.

扩展和修改管理后台、开发者门户和运维控制台。适用于添加新的管理标签页、指标、监控功能或内部…

Build and deploy a Coralogix dashboard for a given service from its logs, spans, metrics, and service specs. Discovers telemetry via cx CLI commands, emits importable Coralogix JSON, verifies every PromQL and DataPrime query live through the `cx` CLI, and creates the dashboard via `cx dashboards create`. Use whenever the user asks to create, build, generate, or deploy a Coralogix dashboard, monitoring dashboard, or observability dashboard for a service, app, or pipeline.

Use this skill when the user asks to "set up parsing", "create parsing rule", "extract fields from logs", "regex extraction", "log parsing", "enrich logs", "add context to logs", "custom enrichment table", "lookup table", "geo enrichment", "create metric from logs", "events to metrics", "convert logs to metrics", "generate metrics from events", "recording rule", "precomputed metrics", "PromQL recording", "configure data pipeline", "transform log data", "data processing rules", "rule group", "enrichment settings", "E2M definition", "labels cardinality", "bulk delete rules", "enrichment limits", "search enrichment table", or wants to configure how Coralogix processes, enriches, or transforms ingested data.

Expert people analytics covering workforce analytics, HR metrics, predictive modeling, employee insights, and data-driven HR decisions. Use when building turnover prediction models, analyzing engagement surveys, running pay equity regressions, designing people dashboards, scoring flight risk, or advising HR leaders with workforce data.

Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.

Triage Antithesis test reports to understand what happened in a run: look up runs, check status, investigate failed properties (assertions), view metadata, download logs, inspect findings, and examine environmental details. Load after a run completes or when investigating a failure.

Detects and redacts Personally Identifiable Information (PII) like emails, phone numbers, and credit cards. Use when cleaning logs, datasets, or communications…

SQL optimization for OLTP systems: EXPLAIN analysis, indexing, schema design, migrations, HA, and security across major SQL platforms.

Route BigQuery-backed Looker Studio work into one stakeholder-reporting packet: dashboard-spec, slow-dashboard triage, refresh-shape choice, audience split, or exec-handoff. Use when the user needs KPI boards, PM/ops reviews, marketing / GTM reporting, product funnel summaries, or game/live-ops telemetry dashboards on top of curated BigQuery data. Route KPI explanation to `data-analysis`, repeated anomaly hunting to `pattern-detection`, telemetry/alerting coverage to `monitoring-observability`, and semantic-platform choice to `survey`.

Design, build, and optimize dashboards for RIA practice management with AUM tracking, revenue analytics, and KPI frameworks. Use when the user asks about…

Implement modal and modeless dialogs using Syncfusion Blazor Dialog component. Use this skill when creating dialogs, popup windows, modal confirmations, custom…

Route repeated pattern, rule, and anomaly work into one detection packet before suggesting tools or fixes. Use when the user needs reusable scans, suspicious repeated shapes, grouped outlier candidates, or first-pass anomaly triage across code, logs/events, telemetry, and metric tables. Choose one packet: text-prefilter, structural-code-rule, log-event-pattern, or metric-anomaly. Triggers on: repeated bug, suspicious spike, odd cohort, noisy event, code smell family, rule pack, anti-pattern, outlier, anomaly, fraud signal, or recurring issue. Route root-cause incident work to log-analysis, KPI/business explanation to data-analysis, repo tracing to codebase-search, remediation to specialist skills, and alert/incident operations to monitoring-observability.