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Found 1,665 Skills
EffectComposer setup and architecture for Three.js post-processing pipelines. Use when setting up multi-pass rendering, combining effects, creating custom passes, managing render targets, or building reusable effect stacks. Foundation skill for all post-processing work.
Turns a free-form project description into PROJECT_MANIFEST.md and SOFTWARE_FACTORY_MANIFEST.md for a 6-agent software factory pipeline. Agent-agnostic: works in Claude Code, Codex CLI, Gemini CLI.
Workflow for learning CuTe Python DSL by reading, importing, profiling, and extracting reusable patterns from CUTLASS Blackwell example kernels. Use when: (1) studying CUTLASS CuTe DSL reference implementations, (2) importing CUTLASS examples into the project runtime infrastructure, (3) building CuTe DSL knowledge base entries from profiling experiments, (4) understanding CuTe DSL API patterns, TMA pipelining, warpgroup scheduling, or persistent kernel structure.
Guide for using Netlify Image CDN for image optimization and transformation. Use when serving optimized images, creating responsive image markup, setting up user-uploaded image pipelines, or configuring image transformations. Covers the /.netlify/images endpoint, query parameters, remote image allowlisting, clean URL rewrites, and composing uploads with Functions + Blobs.
Compress LLM responses to pure signal — Rocky's early notation style. Drop articles, filler, hedging. Best for pipelines and coding.
SimpleKPI integration. Manage Users, Organizations, Goals, Projects, Pipelines, Filters. Use when the user wants to interact with SimpleKPI data.
Sending telemetry data to Grafana Cloud — metrics via Prometheus remote write or OTLP, logs via Loki push or Alloy, traces via OTLP to Tempo, profiles via Pyroscope. Covers Alloy-based pipelines, direct SDK/agent integrations, cloud integrations catalog, and credentials management. Use when connecting an application or infrastructure to Grafana Cloud, setting up data ingestion, configuring remote write, or choosing between ingestion methods.
Meta-skill for understanding and customizing Mindfold Trellis — the all-in-one AI workflow system for 11 AI coding platforms (Claude Code, Cursor, OpenCode, iFlow, Codex, Kilo, Kiro, Gemini CLI, Antigravity, Qoder, CodeBuddy). Documents the original Trellis system design including architecture, commands, hooks, multi-agent pipelines, monorepo support, and task lifecycle hooks. Use when understanding Trellis architecture, customizing workflows, adding commands or agents, troubleshooting issues, or adapting Trellis to specific projects. Modifications should be recorded in a project-local trellis-local skill, not here.
MaxIQ platform help — AI-native revenue intelligence with EchoIQ conversation intelligence, InspectIQ pipeline visibility, ForecastIQ AI-driven forecasting, 9 AI agents (NoteTaker, Radar, Summarizer, Coach, Taskmaster, Watchdog, Forecaster, Revenue Planner, Deal Mapper), usage-based pricing (no per-seat), Salesforce/HubSpot CRM sync. Use when EchoIQ not capturing all meeting types, AI Coach scoring criteria not matching your sales process, CRM fields not auto-populating from calls, InspectIQ deal signals seem inaccurate, ForecastIQ predictions not matching reality, comparing MaxIQ vs Gong vs Clari for revenue intelligence, setting up AI Radar keyword tracking, or evaluating usage-based CI pricing vs per-seat alternatives. Do NOT use for designing outbound cadences (use /sales-cadence) or cross-platform coaching programs (use /sales-coaching).
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 should be used when the user asks to "implement a feature in Elixir", "refactor this module", "should I use a GenServer here?", "how should I structure this?", "use the pipe operator", "add error handling", "make this concurrent", or mentions protocols, behaviours, pattern matching, with statements, comprehensions, structs, or coming from an OOP background. Contains paradigm-shifting insights.
This skill helps the agent generate or update orchestration pipeline definitions for Google Cloud Composer to initialize orchestration pipeline or update the orchestration definition for orchestration of various data pipelines, like dbt pipelines, notebooks, Spark jobs, Dataform, Python scripts or inline BigQuery SQL queries. This skill also helps deploy and trigger orchestration pipelines.