Results for “fls”

Builds and reviews Apex code that constructs SOQL/SOSL at runtime, inspects schema metadata, and accesses fields dynamically, with guidance on injection prevention and FLS enforcement.

Writes Apex that calls Field Service Lightning scheduling APIs to book, schedule, grade, or optimize service appointments programmatically, including transaction-splitting patterns to avoid callout-DML conflicts.

Trains, evaluates, exports, and runs inference for FastFoundationStereo (FFS) stereo depth estimation models, a distilled variant of FoundationStereo with lower latency.

Perform coverage-guided fuzzing of compiled binaries using AFL++ to discover memory corruption, crashes, and security vulnerabilities.

Implements Apex code that calls the FSL scheduling API (GetSlots, schedule, GradeSlotsService, OAAS) with correct transaction boundaries, bulk patterns, and licensing considerations.

Runs R statistics analyses on local datasets, producing NLSS-format tables, narratives, and JSONL logs from CSV, SAV, RDS, RData, or Parquet files.

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

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

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.

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

Use when annotating VCF files with flanking sequence information (INFO/FS tag) or masking regions/variants in flanking sequences.

AFL++ is a fork of AFL with better fuzzing performance and advanced features. Use for multi-core fuzzing of C/C++ projects.

Integrates on-device and cloud machine learning into Flutter apps with TensorFlow Lite and Firebase ML Kit, covering image classification, object detection, OCR, face detection, and barcode scanning.

Assess SSL/TLS server configurations using the sslyze Python library to evaluate cipher suites, certificate chains, protocol versions, HSTS headers, and known vulnerabilities like Heartbleed and ROBOT.

Parse FCS (Flow Cytometry Standard) files v2.0-3.1, extracting events as NumPy arrays, metadata, and channel information, with support for creating and modifying FCS files.

Fuzz C/C++ projects with multi-core support using AFL++, a fork of AFL with better performance and advanced features.

Flash FPGA firmware on HSB Lattice boards and Leopard Imaging VB1940 cameras connected to NVIDIA devkits, with safety checks and multi-step upgrade/downgrade procedures.

Dense, machine-readable API reference for PyFixest — high-dimensional fixed-effects OLS/WLS/IV and Poisson (feols, fepois, feglm), clustered/robust standard errors, R-style formula syntax, and post-estimation. Use when writing or debugging Python fixed-effects regressions with the pyfixest package.

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

Provides a general step-by-step procedure for handling requests related to end, size, and fs, with placeholders for specifics.

Guides the configuration of pfSense firewall rules, NAT policies, VPN tunnels, and traffic shaping to enforce network segmentation and protect network zones.

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

Detect and respond to Adversary-in-the-Middle (AiTM) phishing attacks that use reverse proxy kits like EvilProxy, Evilginx, and Tycoon 2FA to bypass MFA and steal session tokens.

Implements sibling communication between Lightning Web Components using Lightning Message Service (LMS) or the legacy pubsub utility, covering message channel definition, publish/subscribe patterns, and scope selection.

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

Use this skill when the user asks about the FMCSA Drug & Alcohol Clearinghouse — full vs limited query, pre-employment vs annual query, query credit purchasing, who has access (employers, drivers, MROs, SAPs, state licensing agencies), reporting violations to the Clearinghouse, the "prohibited" status workflow, consent forms, or how to register/use the clearinghouse.fmcsa.dot.gov portal. Cite 49 CFR 382.701-727.

Use this skill when the user asks about FMCSA investigation types — Focused Investigation vs Comprehensive Review vs Compliance Review (CR) vs Investigation, when each is triggered, scope differences, on-site vs off-site, and how to prepare for each. Cite 49 CFR 385 Subpart C + D.

Explains the Financial Services Cloud data model, covering managed-package and Core FSC object structures, household relationships, financial account ownership, and the rollup framework, with SOQL query patterns.

TLS/SSL configuration audit. Tests protocol versions (SSLv2/3, TLS 1.0/1.1/1.2/1.3), cipher strength and ordering, certificate chain validation (intermediates, CT logs, OCSP stapling, pinning), known vulnerabilities (POODLE, BEAST, CRIME, Heartbleed, ROBOT, DROWN, Ticketbleed, GOLDENDOODLE), session management (ticket reuse, resumption, fixation), renegotiation attacks, TLS 1.3-specific issues (0-RTT replay, PSK modes, downgrade), HSTS deep analysis (preload, subdomains, bypass), and certificate revocation (CRL, OCSP responder, stapled response freshness). Compliance-mapped to PCI DSS 4.0 (full Section 4), NIST SP 800-52r2, and FedRAMP. Uses testssl.sh, sslscan, sslyze, openssl, nmap NSE scripts, and nuclei SSL templates. Multi-port scanning across 20+ TLS-bearing services.

Enables fast similarity search and clustering of dense vectors using FAISS, supporting billions of vectors, GPU acceleration, and various index types.

Extracts and reconciles medical provider, wage-loss, and insurance/lien data from personal injury plaintiff fact sheets and initial disclosures against builder draft responses. Use when the user mentions PFS analysis, medical provider reconciliation, wage loss audit, insurance lien tracking, PI discovery reconciliation, builder response validation, MDL plaintiff data extraction, FRCP 26(a)(1) disclosures, treatment chronologies, or specials spreadsheets.

Generate images using FLUX models via the inference.sh CLI, supporting text-to-image, image-to-image, and LoRA fine-tuning.

Apply functional programming patterns with fp-ts in React, covering state management, form validation, and data fetching for React 18/19 and Next.js 14/15.

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.