Results for “tri-fold”

7 skills

matlab-prepare-signal-data

Use this skill when conditioning, loading, preparing, or labeling signal data for analysis or ML training. Covers: cleaning a single signal (fill gaps, remove drift, deoutlier, denoise, resample/align a time base) BEFORE analysis; building a `signalDatastore` pipeline; creating a `labeledSignalSet` for Signal Labeler; deriving labels (filename, folder, in-file, ROI, time-frequency ROI); stratified train/val/test splits; framing long signals; parallel processing; and shaping datastore output for `trainnet`. Triggers include "clean up this signal", "remove drift / detrend", "fill gaps", "remove spikes / outliers", "denoise", "resample to a uniform rate", "align channels", "labels from filenames", "stratified split", "prepare for Signal Labeler", and function names like `fillgaps`, `fillmissing`, `detrend`, `filloutliers`, `smoothdata`, `resample`, `synchronize`, `signalDatastore`, `labeledSignalSet`, `filenames2labels`, `folders2labels`, `splitlabels`, `framesig`, `framelbl`, `createDatastores`.

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Mapa i przewodnik po wyspecjalizowanych skillach platformy Soneta (enova365, Triva): soneta-programming (ORM, kod biznesowy), soneta-addon-planning, soneta-business-xml, soneta-form-xml, soneta-repx (wydruki DevExpress .repx), soneta-place-def-elementow, soneta-config (import/eksport XML, scan-folders, appsettings.json — porty i adresy komponentów), soneta-config-reg (rejestr konfiguracji ConfigReg, providery, *.reg.json), soneta-tools (narzędzia CLI: dbmgr, buscall, SonetaFrame), soneta-containers (docker compose, Apple container, Helm/Kubernetes, wersje obrazów, baza w kontenerze). Używaj gdy użytkownik: (1) rozpoczyna zadanie dla platformy Soneta i nie wiadomo, który skill wybrać; (2) pyta ogólnie o dodatki, moduły lub rozszerzenia Soneta ERP; (3) wspomina enova, Soneta Enterprise, Triva bez sprecyzowania warstwy (dane, UI, logika, płace); (4) chce poznać dostępne skille; (5) realizuje zadanie obejmujące wiele warstw platformy (np. moduł z bazą, formularzami i logiką).

lucassantana-dev

refactor-pipeline

Composite skill — safely refactor a module end-to-end with sequencing, parallel implementation, post-refactor cleanup, and rationale capture. Chains refactor-plan (phased plan + rollback) → three-man-team (architect/builder/reviewer in parallel) → fix-the-suite post-refactor → adr-write → docs-sync. Use for non-trivial refactors that need both careful sequencing and durable record.

bmad-testarch-ci

Scaffold CI/CD quality pipeline with test execution. Use when the user says "lets setup CI pipeline" or "I want to create quality gates"

ai-builder-club

dev-local-setup

Scaffold a one-command dev-local launcher for any codebase by investigating services, ports, and infra dependencies, then generating a single script with tmux session management.

AI 3D model generation agent. Generates text-to-3D and image-to-3D code (Python/JS/OpenSCAD) using Meshy, Tripo, Hunyuan3D, Rodin, Sloyd, and Stability APIs. Handles game pipeline integration, LOD, retopology, UV, and QC validation.

brycewang-stanford

Orchestrate the complete post-first-draft polishing pipeline for an academic LaTeX paper by invoking five existing skills in fixed order: (1) paper-polish, (2) paper-self-revise, (3) paper-style, (4) paper-polish again, (5) reference-verify. Trigger when user says "paper pipeline" / "paper-pipeline" / "论文流水线" / "全流程打磨" / "一条龙打磨" / "初稿打磨" / "full polish pipeline" / "run the whole pipeline", or wants the entire post-draft polishing sequence run on a paper folder. Use this skill whenever the user asks for several paper-finishing steps (polish + revise + style + reference check) on one manuscript in one go, even if they don't name every individual skill.