Results for “pre-pr”

Parse FCS (Flow Cytometry Standard) files v2.0-3.1, extract events as NumPy arrays, read metadata and channels, and convert to CSV or DataFrame for flow cytometry data preprocessing.

Load pre-trained models from Hugging Face Hub, run pipeline inference, generate text, and fine-tune models on NLP, vision, audio, and multimodal tasks using the Transformers library.

Analyzes bootkit and rootkit malware that infects MBR, VBR, or UEFI firmware for pre-OS persistence, covering boot sector analysis, UEFI module inspection, and anti-rootkit detection.

Given a stock ticker, cost basis, and position purpose, classifies the holding scenario and returns concrete hedge recommendations (Long Put, Collar, Tier-down) with live option strikes and premiums.

Generate high-quality sentence and text embeddings for semantic similarity, clustering, and retrieval using 5000+ pre-trained models. Supports multilingual and domain-specific embeddings for RAG and semantic search.

Tracks institutional investor ownership changes and portfolio flows using 13F filings data to identify stocks with significant smart money accumulation or distribution.

Syncs App Store metadata with App Store Connect using the canonical asc metadata workflow, including pull, validate, preview, and apply steps for app-info and version localization fields.

Limpia y transforma texto en DataFrames usando expresiones regulares: extrae emails, teléfonos, fechas y precios, valida formatos como CUIL o CBU, y maneja datos inconsistentes con opciones de fuzzy matching.

Extract public web data via HasData APIs, including search engine results, structured data from ecommerce, travel, jobs, and local business platforms, with support for web scraping, pre-parsed APIs, and async jobs.

CPRA §1798.121 sensitive personal information restrictions and compliance. Covers all 9 sensitive PI categories including SSN, precise geolocation, racial/ethnic origin, biometric, genetic, health, and sex life data. Right to limit use/disclosure, permitted purposes, and implementation.

Review MATLAB code for quality, performance, maintainability, and adherence to MathWorks coding standards. Uses check_matlab_code and matlab_coding_guidelines. Use when reviewing code, checking style, finding code smells, assessing quality, or preparing code for handoff or publication.

Recommend continuing glucocorticoid replacement until hypothalamic-pituitary-adrenal (HPA) axis recovery after surgical resection of ACTH-secreting pituitary tumors. Use when managing postoperative patients following ACTH-secreting tumor surgery to prevent adrenal insufficiency during HPA axis recovery.

Buy and sell tokens on pump.fun bonding curve and pump swap AMM pool, and query SOL/token balances. Prefer runnable Node scripts in this skill folder; use @pump-fun/pump-sdk and @pump-fun/pump-swap-sdk for custom integrations.

Gera um plano de reconstrução bottom-up a partir das specs do Reversa e executa cada tarefa sob demanda, uma por vez, preservando tokens. Use quando quiser reimplementar o software do zero a partir das especificações geradas. Ativação: /reversa-reconstructor

Use when composing corner-anchored laser accents with thin beams, a bright emitter node, bloom, and atmospheric glow or fog. Prefer this over mengto-webgl-laser when lasers are layout corner ornaments, not a fixed full-screen WebGL beam.

Systematic audit and review by Referee 2. Two modes — "deck" reviews slide presentations for rhetoric, visual quality, and compile cleanliness; "code" performs cross-language replication and econometric audit of empirical pipelines. Use when reviewing slides, auditing code, or verifying replication.

Use to design VIP or tiered support programmes and to test whether higher tiers actually deliver better outcomes. Trigger for "VIP support programme", "service tiering", queue priority for premium customers, entitlement vs priority, tier inflation, or "does our enterprise tier get faster support".

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces. Also applies to any HTML-rendered output with interactive elements — investor decks, annual reports, product pages, slide presentations (Reveal.js, Guizang PPT), interactive documents, and landing pages that need premium feel beyond static aesthetics. Not for static Word/PDF generation (typography rules only).

Deploys Mobile Application Management (MAM) policies to protect enterprise data on managed and unmanaged mobile devices through app-level controls including data loss prevention, selective wipe, app configuration, and containerization.

Use for creating, reviewing, debugging, or packaging portable GitHub Copilot Agent Skills with SKILL.md, precise triggers, progressive disclosure, scripts, examples, and resources. Do not use for always-on repository rules, a single prompt command, custom agent personas, or Skill Foundry maintenance.

Maps the US federal privacy landscape including sectoral laws (HIPAA, GLBA, FERPA, COPPA, FCRA, ECPA, VPPA), FTC Section 5 enforcement, proposed federal comprehensive legislation, and the interaction between federal and state privacy regimes. Keywords: federal privacy, HIPAA, GLBA, FERPA, COPPA, FCRA, FTC, sectoral, preemption.

Drafts evaluation-ready U.S. federal RFP responses across all standard proposal volumes (cover letter, technical, cost/price, reps and certs). Enforces FAR compliance, CPARS references, and Section L/M alignment. Use when preparing federal solicitation submissions, responding to government RFPs, or drafting procurement bids.

Pressure-test any business idea with a five-angle adversarial panel (Critic, Champion, Analyst, Investigator, Customer) that returns a single GO/RESHAPE/KILL verdict with the cheapest test to de-risk it.

Detects rootkit presence on compromised systems by identifying hidden processes, hooked system calls, modified kernel structures, hidden files, and covert network connections using memory forensics, cross-view detection, and integrity checking techniques.

Builds an investor, product, or sales pitch deck as a PPTX file from a written brief, extracting fundamentals, flagging gaps as TODOs, drafting slides with speaker notes, and rendering with python-pptx.

Creates and manages design token systems with three-layer architecture, generates CSS variables, validates token usage, and produces brand-compliant slide presentations with Chart.js and contextual decision logic.

Wrapper Pythônico ao redor do RDKit com interface simplificada e padrões sensatos. Preferido para descoberta de fármacos padrão: análise de SMILES, padronização, descritores, fingerprints, clustering, conformadores 3D, processamento paralelo. Retorna objetos nativos rdkit.Chem.Mol. Para controle avançado ou parâmetros customizados, use rdkit diretamente.

Create distinctive, production-grade frontend interfaces with high design quality. Use only when invoked by the `design` wrapper skill, OR when working outside a known site (no `~/Sites/<name>/` repo). Otherwise prefer `design`. Generates creative, polished code that avoids generic AI aesthetics.

Drafts professional legal letters for personal injury litigation including settlement demands, cease-and-desist, notice letters, and response correspondence. Tailors tone by recipient type. Use when drafting demand letters, pre-suit correspondence, insurance claim letters, cease-and-desist notices, or litigation response letters.

Redige o procedimento de producao antecipada de provas (CPC 381-383), enquadrando-o nas tres hipoteses do art. 381 (I — fundado receio de que se torne impossivel ou muito dificil verificar fatos na pendencia da acao; II — viabilizar autocomposicao; III — conhecimento previo dos fatos que justifique ou evite o ajuizamento), sem exigencia de urgencia nos incisos II e III, com competencia do foro da producao ou do domicilio do reu (381 §2), sem prevencao (381 §3), e sem o juiz se pronunciar sobre o fato (382 §2). Use quando o operador disser produzir prova antes, producao antecipada, perpetuar prova, pericia antes da acao, ouvir testemunha antes.

Checks how well a Linear cycle is prepared. Reports per-person load in working days against available days, tickets with no estimate, tickets nobody is assigned to, oversized tickets that need splitting, work that did not finish last cycle, on-call rotation cost, and how groomed the backlog behind the cycle is. Invoke when the user says "cyclotic", "cyclotic prep", "cyclotic prep next", "cyclotic review", "cyclotic init", "cyclotic configure", "cyclotic for" a person's name, "cyclotic show cards", "cyclotic list tickets", "cyclotic explain" a person's name, or adds "-v" or "verbose" to any of those. Also invoke when the user asks whether a cycle or sprint is ready, who is over or under capacity, what carried over from last cycle, which tickets still need estimates, how the backlog looks going into planning, what is in the cycle and at what sizes, or how one person's load adds up. Read-only against Linear.

Synthesize source-indexed proof-material items into the final proof-usage playbook. Use when Codex needs to cluster proof items by proof shape, de-duplicate across sources, design reusable taxonomy entries, update proof-usage indexes and source maps, or preserve material-ID links from cooked proof entries.

Prepare for SOC 2 audits by mapping Trust Service Criteria, building control matrices, collecting audit evidence, performing gap analysis, and assessing Type I vs Type II readiness.

Guides agents through the full lifecycle of NeMo-RL experiments: understanding recipes, launching reproducible runs, analyzing results, and preserving human oversight with git and TSV logs.

Deploy and configure Velociraptor for scalable endpoint forensic artifact collection during incident response using VQL queries, hunts, and pre-built artifact packs across Windows, Linux, and macOS environments.

Reads and preprocesses 5-minute stock candlestick CSV data, then clusters the time series using tslearn's TimeSeriesKMeans, including data cleaning, percentage change calculation, model training, saving, and representative sample extraction.