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Found 2,808 Skills
Configure cmux through ~/.config/cmux/cmux.json: settings (appearance, sidebar, notifications, automation, browser, shortcuts, set/get/validate by JSON path), customization (tab bar buttons, plus-button click and right-click menus, custom actions/commands/menus, right sidebar), and sidebar workspace groups (anchor workspaces, group CLI/socket ops, per-cwd group config). Triggers: 'cmux config', 'cmux.json', 'change cmux setting', 'set <x> in cmux', 'rebind a cmux shortcut', 'cmux-customize', 'customize cmux', 'tab bar button', 'add cmux action', 'workspace group', 'group sidebar', 'anchor workspace', 'workspaceGroups'.
Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_prep_search, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse → prep_search → index → query).
Create, manage, and query Databricks Genie Agents — curated, per-data natural-language agents (formerly Genie Spaces): build, export/import, migrate across workspaces, and ask questions of a *specific* Agent via the Conversation API. For general data questions or finding data across your workspace, use databricks-data-discovery (Genie One) instead.
Use when the user asks to "generate subject line variants", "pre-score my subject lines", or "will this subject get truncated / trigger spam filters"; produces a labeled subject + preheader variant set and a per-variant heuristic pre-score card — spam-trigger flags, length/truncation across desktop + mobile, emoji-count, and the inbox preview render (from-name + subject + preheader) — before any test is run. Not for the body copy or CTA — use email-creative-builder; not for the A/B test design or significance read — use send-experiment-designer; not for the profile-weighted EQS or the S1/S2/N1/D1 vetoes — use email-quality-auditor. 邮件主题行生成/主题行预打分/截断与垃圾词检查
Stop AI coding agents from shipping sloppy code — over-abstraction, drive-by refactors, obvious comments, extra files, unrequested deps, giant unreadable files, or fishing outside the workspace for “inspiration”. Use when writing or editing code, implementing features, fixing bugs, splitting or organizing files, or when the user mentions slop, cleanup, keep it simple, minimal diff, file too big, hard to navigate, or stay in the repo.
Migrate WPF applications to WinUI 3 — namespace replacement (System.Windows → Microsoft.UI.Xaml), control mapping (DataGrid→ListView, WrapPanel→ItemsRepeater, TabControl→TabView), threading (Dispatcher→DispatcherQueue), imaging (System.Drawing→BitmapImage), MVVM conversion to CommunityToolkit.Mvvm, and DynamicResource→ThemeResource. Use when converting WPF code, replacing WPF namespaces, or fixing migration build errors.
Run the solution space in two modes — DIVERGE prepares the workshop (traceable How Might We, seed ideas sealed until the humans have ideated, a timeboxed agenda and the board written zone by zone) and CONVERGE reads what the team produced and voted and writes the Value Map plus the prototype brief. Manually triggered, sixth station of the discovery pipeline; it never picks the winning idea.
Check progress, advance workflow, or dispatch freeform intent — the unified GSD situational command
Design agent-native applications where agents replace UI users as the primary actor. Use when designing MCP tools, agent-loop architectures, system prompt design, hooks policy, shared-workspace file patterns, or self-modifying agent systems.
One-time bootstrap of a persistent memory + self-evolution system for an agent workspace. Use when setting up memory for a new agent or workspace, or configuring dream/janitor crons.
Compact CLI reference for chat workers — dispatch, monitor, secrets, workers, automations.
Audits instrumentation health of existing Arize traces. Runs deterministic checks over a bounded span sample (orphaned/uncategorized/duplicate spans, flat structure, blank root I/O, unset status, missing token counts or children) and returns a ranked report. Use when the user asks why traces look empty/flat/broken, wants to verify instrumentation is healthy, find instrumentation issues, or why evals or token/cost dashboards show n/a or zero. To debug app behavior or errors, use arize-trace.