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Found 12,122 Skills
Review test quality and audit test coverage for any module. This skill should be used when reviewing existing tests, auditing test gaps, writing new tests, or when asked to assess test health. It pipelines testing standards into the audit workflow to produce a prioritized gap report. The output is a report, not code — do not write test implementations until the report is reviewed.
A specialized skill for Gemini CLI that provides high-performance, fail-fast monitoring of GitHub Actions workflows and automated local verification of CI failures. It handles run discovery automatically—simply provide the branch name.
Use Birdeye MCP through UXC for token market data, trending and discovery workflows, price monitoring, and DEX-related reads with help-first live tool discovery and API-key auth.
Use a local QMD knowledge base through UXC over MCP stdio, with daemon-backed session reuse and typed retrieval flows that avoid repeated model warmup and unnecessary query-expansion latency.
Use Gate MCP through UXC for public spot and futures market data workflows with a fixed streamable-http endpoint and read-first guardrails.
Use OKX OnchainOS MCP through UXC for token discovery, market data, wallet balance, and swap execution planning. Use when tasks need OKX MCP tools such as token search/ranking/holder, price/trades/candlesticks/index, balance queries, and DEX quote/swap flows with help-first schema inspection and safe auth handling.
Grafana OnCall and Incident Response Management (IRM) — alert routing, escalation chains, on-call schedules, Jinja2 routing templates, Slack/mobile notifications, integrations (Alertmanager, Grafana Alerting, webhooks, PagerDuty), and incident lifecycle management. Use when setting up on-call rotations, configuring escalation policies, routing alerts to the right team, declaring and managing incidents, integrating with Alertmanager or Grafana Alerting, or configuring Slack-based alert workflows.
Cleft Notes platform help — Apple-native AI voice-to-notes app with on-device transcription that turns spoken thoughts into organized markdown notes with auto-headings. Use when setting up Cleft Notes for capturing voice memos and converting rambling thoughts into structured notes, configuring Obsidian or Notion sync to route Cleft notes into an existing knowledge base, troubleshooting recordings that fail after a couple minutes or produce garbled transcription output, setting up Zapier automations to send Cleft notes to project management or CRM tools, choosing between Cleft free and Plus plans, deciding whether Cleft or Voicenotes or AudioPen fits your voice capture workflow, or evaluating Cleft for ADHD-friendly voice-first note-taking on Apple devices. Do NOT use for comparing AI meeting note-takers across platforms (use /sales-note-taker) or reviewing a sales call for coaching (use /sales-call-review).
Whatfix platform help — Digital Adoption Platform (DAP), in-app Flows, Smart Tips, Beacons, Task Lists, Self Help widget, Product Analytics (funnels, Sankey charts, cohorts), Mirror sandbox training, NPS/custom surveys, Integration Hub. Use when Whatfix flows aren't triggering, users skip walkthroughs, Self Help widget isn't surfacing right content, product analytics look wrong, Mirror sandbox needs setup, Whatfix surveys have low completion, Integration Hub data isn't syncing, need help with Whatfix API or content tagging, setting up Whatfix for a new enterprise app, or comparing Whatfix to WalkMe or Pendo. Do NOT use for in-app messaging strategy across platforms (use /sales-in-app-messaging) or general customer feedback strategy (use /sales-customer-feedback).
Implement end-to-end Medallion Architecture (Bronze/Silver/Gold) lakehouse patterns in Microsoft Fabric using PySpark, Delta Lake, and Fabric Pipelines. Use when the user wants to: (1) design a Bronze/Silver/Gold data lakehouse, (2) set up multi-layer workspace with lakehouses for each tier, (3) build ingestion-to-analytics pipelines with data quality enforcement, (4) optimize Spark configurations per medallion layer, (5) orchestrate Bronze-to-Silver-to-Gold flows via notebooks. Triggers: "medallion architecture", "bronze silver gold", "lakehouse layers", "e2e data pipeline", "end-to-end lakehouse", "data lakehouse pattern", "multi-layer lakehouse", "build medallion", "setup medallion".
This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation depending on tool availability), library installation, and structuring notebooks for clarity. It also covers specific rules for data cleaning, plotting, and integrating with BigQuery SQL and machine learning workflows. Relevant when any of the following conditions are true: 1. The user request involves a data analysis, data exploration, data visualization, or data insights task that requires multiple steps, queries, or visualizations to answer. 2. The user explicitly requests a notebook (.ipynb). 3. You are creating, editing, or executing cells in a Jupyter notebook. 4. You need to query BigQuery from within a notebook. DO NOT use the Python BigQuery client library; instead, you MUST use the `%%bqsql` magics explained in this skill.
Work with any Upstash TypeScript/JavaScript SDK including Redis, Box, QStash, Workflow, Vector, Search and Ratelimit. Use when the user is working with any Upstash product or SDK.