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Found 700 Skills
Profile a model running on MAX to find where it spends time and whether the GPU is saturated. Use when the user asks to "profile my model," "where is my model spending time," "why is inference slow," "is my GPU being utilized," "how much GPU am I using," "get a kernel breakdown," "capture an nsys/rocprof/ncu trace of max serve," or wants to measure MAX inference performance. Works for any model MAX can run — built-in architectures and custom ones loaded with --custom-architectures — from a pip or pixi install (max generate, max serve, or a Python script) on NVIDIA or AMD GPUs. Decide cheapest-first: a GPU utilization check, then a kernel breakdown, then a single-kernel deep dive only when one kernel dominates.
Use this skill to analyze a Salesforce Aura component bundle (.cmp, .app, .evt, .intf, Controller.js, Helper.js, Renderer.js) and produce a framework-agnostic migration blueprint (PRD.yaml / PRD.md / PRD.json) capturing public API, data requirements, slots, events, states, accessibility, styling, localization, and security posture. This is Phase 1 (analysis + PRD) only — it does NOT author or edit component code, wire adapters, or Jest tests, and does not write .html/.js/.css/.js-meta.xml. TRIGGER when the user says "analyze this Aura component", "migrate Aura", "convert .cmp", "produce a migration blueprint", "generate a PRD for this Aura component", or mentions aura:attribute, aura:handler, force:recordData, $Label, $Resource, component.get, cmp.find, or an input directory containing .cmp files. DO NOT TRIGGER when there is no Aura source (delegate downstream LWC authoring to experience-lwc-generate), for post-migration scoring, or for refactoring an existing modern component.
Fixed timestep game loop with interpolation for frame-rate independent physics. Separates physics updates from rendering, prevents spiral of death, and supports hitstop/slow-mo effects.
Comprehensive structural variant (SV) analysis skill for clinical genomics. Classifies SVs (deletions, duplications, inversions, translocations), assesses pathogenicity using ACMG-adapted criteria, evaluates gene disruption and dosage sensitivity, and provides clinical interpretation with evidence grading. Use when analyzing CNVs, large deletions/duplications, chromosomal rearrangements, or any structural variants requiring clinical interpretation.
Analyze and optimize slow SQL queries. Use when the user says a query is slow, asks to optimize or speed up SQL, wants to find anti-patterns, needs index recommendations, or asks for a query rewrite. Also use when EXPLAIN output shows full table scans or poor join strategies.
End-to-end SGLang SOTA performance workflow. Use when a user names an LLM model and wants SGLang to match or beat the best observed vLLM and TensorRT-LLM serving performance by searching each framework's best deployment command, benchmarking them fairly, profiling SGLang if it is slower, identifying kernel/overlap/fusion bottlenecks, patching SGLang code, and revalidating with real model runs.
Every Cal.com feature, plus offline agendas, composed booking flows, and analytics no other Cal.com tool ships. Trigger phrases: `book a meeting on cal.com`, `what's on my calendar today`, `find an open slot`, `reschedule my next booking`, `audit my cal.com webhooks`, `use cal-com`, `run cal-com-pp-cli`.
SpriteRendererComponent.SpriteRUID (world) and SpriteGUIRendererComponent.ImageRUID (UI) — native RUID type support (sprite / animationclip direct playback), thumbnail:// prefix for rendering avataritem / skeleton / animationclip as static thumbnail image, avatar item icon in inventory / shop / UI slot. Use when: assigning any RUID to a sprite renderer component, displaying an avatar item or resource as a thumbnail or icon, using animationclip directly in a renderer, rendering inventory item icons, displaying a thumbnail image in a world entity. Keywords: SpriteRUID, ImageRUID, thumbnail://, animationclip, RUID apply, RUID assign, thumbnail, item icon, sprite RUID, RUID to renderer
Amazon Redshift is NOT PostgreSQL — corrects PostgreSQL-derived LLM mistakes; covers Redshift-specific SQL, DDL, COPY/UNLOAD, system views, metadata discovery, and operational patterns. Applies ONLY when the task is about Redshift itself (cluster, Serverless workgroup, or Redshift SQL). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query, LATERAL, RETURNING. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow Redshift query, Redshift permission denied, Redshift disk full, Redshift system views, QUALIFY, PIVOT, MERGE, Redshift Data API, Redshift WLM, concurrency scaling, Redshift resize, Redshift Spectrum external tables. Does NOT apply to (defer to that service's own skill): Amazon S3 storage/bucket policies, Athena or Glue queries/catalogs, data-lake or Iceberg work outside Redshift, Aurora, RDS, or DynamoDB — but S3/Glue ARE in scope for Redshift COPY, UNLOAD, or data-lake queries (external schemas/tables on S3).
Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, JSON path), DIALECT 2 query syntax, FT.SEARCH / FT.AGGREGATE / FT.HYBRID command selection, vector similarity with HNSW or FLAT, hybrid retrieval combining lexical and vector ranking, RAG pipelines, zero-downtime index updates via aliases, and debugging with FT.PROFILE and FT.EXPLAIN. Use when defining a search index on Hash or JSON documents, writing FT.SEARCH queries with filters, sorting, aggregation, or vector KNN, tuning HNSW parameters, building a RAG retrieval pipeline, or troubleshooting slow or empty search results.
LangSmith tracing and trace debugging for AgentSeek templates. Covers CLI installation, adding tracing to LangGraph apps, querying traces, and inspecting run IO. Use when debugging agent backends, investigating slow traces, or adding observability to a template.
When you want to model personal financial scenarios — house purchase + rental income (ADU, bedroom rentals, house-hacking), renovation budgets, monthly cash flow forecasts, big-purchase decisions, savings/investment what-ifs. For personal life: a household (you + partner), household budgets, real-estate decisions. v0.1 ships with the house scenario template (purchase + rental scenarios) as the first use case. Architected so other personal-finance scenarios (refi, car, education, retirement, side income) slot in as additional templates. Outputs scenario comparison tables in markdown. Saves every scenario to ~/Documents/personal-cfo/ with an index at ~/.config/makerskills/personal-cfo/archive/ for revisit + comparison. Composes with decide (formalize the call after modeling), deep-research (rental comps, mortgage rates, market data), business-brainstorm (when the scenario is a small business / side hustle), second-brain (capture the analysis to outputs/). Triggers on "/personal-cfo," "model this scenario," "house math," "rental forecast," "monthly cash flow," "what if I rent out the ADU," "compare these housing scenarios," "should we buy this house," "house-hack math," "renovation budget."