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Found 1,719 Skills
Manages Clockify time tracking via the official Clockify REST API (v1): list workspaces and projects, create time entries with correct UTC timestamps. Use when the user wants to log time, track hours, record work in Clockify, or mentions Clockify or time entries.
Guides efficient Haskell aligned with GHC practice -- laziness and strictness, purity, fusion, newtypes, pragmas, Core reading, and space-leak avoidance. Use when writing or reviewing Haskell, optimizing or profiling, debugging strictness or memory, or when the user mentions GHC, thunks, foldl vs foldl', list fusion, SPECIALIZE, or UNPACK.
This skill should be used when the user asks to "create a power pages site", "build a code site", "scaffold a website", "create a portal", "make a new site", or wants to create a new Power Pages code site (SPA) using React, Angular, Vue, or Astro.
Use this skill for ANY multi-pane or multi-agent terminal orchestration in cmux. Required when the user wants to: run things in parallel in separate terminal panes, split the terminal, spawn a sub-agent (Claude Code, Codex) in another pane, fan out tasks across splits, send keystrokes or text to another pane (including ctrl-c), read terminal output from another pane, update sidebar status or progress bar, open a URL in cmux's built-in browser pane, or display markdown preview alongside the terminal. The cmux CLI is the ONLY way to do these things — Bash cannot split panes or spawn agents. Trigger phrases: 'in parallel', 'split pane', 'spawn agent', 'fan out', 'new pane', 'browser pane', 'sidebar', 'send to pane', 'read from pane', 'show the plan', 'ctrl-c to', '分屏', '并行', '开个 pane'. NOT for: single command execution, basic bash operations, or questions about tmux.
Bitcoin mempool monitoring — check transaction confirmation status, retrieve address transaction history, and inspect current mempool state. Data sourced from mempool.space.
Create multiplayer spatial board games using TabletopKit on visionOS. Use when building tabletop game experiences with boards, pieces, cards, and dice, managing player seats and turns, synchronizing game state over FaceTime with Group Activities, rendering game elements with RealityKit, or implementing piece snapping and physics on a virtual table surface.
Deploys Jupyter notebooks on TrueFoundry infrastructure with optional GPU support. Use when launching JupyterLab environments, setting up ML development workspaces, or running cloud-hosted notebooks for data exploration.
Pipeline orchestrator that classifies incoming coding tasks and routes them through the correct combination of skills in the right order at the right depth. Auto-activates on any coding task. Centralizes the decision logic for which skills to use, how deep each goes, and how artifacts pass between them. Handles three pipeline variants: standard (plan-interview, intent-framed-agent, context-surfing, simplify-and-harden, self-improvement), team-based (agent-teams-simplify-and-harden), and CI (simplify-and-harden-ci, self-improvement-ci). Use this skill whenever starting any coding work — it determines the appropriate pipeline depth and variant automatically. Does not replace individual skills; dispatches to them.
Use when need systematic innovation through comprehensive solution space exploration, resolving technical contradictions (speed vs precision, strength vs weight, cost vs quality), generating novel product configurations, exploring all feasible design alternatives before prototyping, finding inventive solutions to engineering problems, identifying patent opportunities through parameter combinations, or when user mentions morphological analysis, Zwicky box, TRIZ, inventive principles, technical contradictions, systematic innovation, or design space exploration.
Guide users through the Amore CLI for macOS app distribution — setup, releasing, code signing, notarization, DMG creation, S3 hosting, Sparkle updates, licensing, and configuration. Use this skill whenever the user mentions Amore, amore CLI, macOS app distribution outside the App Store, Sparkle updater setup, appcast.xml, notarization workflows, DMG creation, or self-publishing macOS apps. Also use when the user asks about release automation, S3 bucket hosting for app updates, EdDSA signing keys, or licensing with Stripe for macOS apps.
Databricks SQL query optimizer: analyzes a slow SQL query, rewrites it for speed using SQL-level optimizations only, validates byte-for-byte result equivalence, and benchmarks both versions with statistical significance testing. Use this skill whenever the user wants to optimize, speed up, tune, or benchmark a SQL query on Databricks. Trigger on: "/databricks-sql-autotuner", "optimize this SQL", "make this query faster", "tune my Databricks query", "benchmark SQL on Databricks", "speed up this spark SQL", "SQL performance on Databricks", "EXPLAIN this query", "why is my query slow on Databricks", "SQL query optimization Databricks", or whenever a user pastes a SQL query and mentions performance, slowness, or runtime.
Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks. Use when building batch or streaming data pipelines with Python or SQL. Invoke BEFORE starting implementation.