Results for “lsf”

SLF4J - Simple Logging Facade for Java. Standard logging API that abstracts underlying implementation (Logback, Log4j2). Provides parameterized logging and MDC support. USE WHEN: user mentions "slf4j", "java logging api", "parameterized logging", asks about "how to log in Java", "logger facade", "MDC in java", "logging best practices java" DO NOT USE FOR: Logback configuration - use `logback` instead, Log4j2 configuration - use Log4j2 skill, Node.js logging - use `winston` or `pino` instead, Python logging - use `python-logging` instead

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.

Exploit SSRF vulnerabilities in AWS EC2-hosted applications to extract IAM credentials and User Data from the Instance Metadata Service, including techniques for bypassing basic filters against IMDSv1.

Detect and exploit Server-Side Request Forgery vulnerabilities by identifying user-controlled URL parameters, testing for internal service access, cloud metadata endpoints, and file scheme reads, with bypass techniques for common filters.

Detect and exploit Cross-Site Request Forgery vulnerabilities by testing for missing or predictable CSRF tokens, absent SameSite cookie attributes, and JSON endpoints accepting text/plain Content-Type, with payloads and bypass techniques for security testing.

Provides multi-language code navigation via persistent LSP daemons, supporting definitions, references, hover, symbols, and diagnostics for Python, TypeScript, Rust, Go, and more.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Enforce quality, security, and accessibility standards for Salesforce Lightning Web Components, Aura components, and Visualforce pages.

Builds a custom LWC lookup component with typeahead search via Apex SOSL/SOQL, debounce, keyboard navigation, and pill UI for cases where standard pickers fall short.

Spark by Lightspark: statechain-derived L2 with FROST threshold signatures, leaf architecture, Lightning compatibility. Beta launched April 2025; managed by Spark Operators (SOs). USE WHEN: integrating with Spark, evaluating Spark vs Ark vs Lightning, designing leaf-based UTXO trees.

Style Lightning Web Components using SLDS design tokens, styling hooks, scoped CSS, and ::part() while avoiding common pitfalls like !important and shadow-DOM piercing.

Fine-tune instruction-following LLMs with Unsloth's optimized SFTTrainer, covering dataset formatting, chat templates, training configuration, and thinking-model patterns.

路飞（少年漫）认知与表达框架（压缩蒸馏）：自由宣言、橡胶脑洞战、伙伴羁绊 触发：海贼王 等。虚构；非暴力教唆

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

Comprehensive guide to rlhf. Master the concepts, implementation, best practices, and real-world applications of rlhf in professional environments.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debug...

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

Theme Salesforce Lightning base components and custom LWCs using SLDS Styling Hooks, covering global and component hooks, shadow DOM considerations, Experience Cloud theming, and SLDS 2 migration.

You are an expert in LLM observability and evaluation. You think in terms of traces, spans, and metrics. You know that LLM applications need monitoring just like traditional software - but with different dimensions (cost, quality, latency).

Foundational SPARQL patterns covering RDF querying, triple patterns, graph patterns, and semantic web fundamentals. Use when querying RDF data or working with knowledge graphs. This is the entry point for SPARQL development.

Expert NIST Cybersecurity Framework (CSF) advisor covering CSF 2.0 and CSF 1.1. Use this skill whenever a user asks about NIST CSF, cybersecurity risk management, the six CSF functions (Govern, Identify, Protect, Detect, Respond, Recover), CSF profiles, implementation tiers, gap assessments, organizational profiles, community profiles, CSF core subcategories, informative references, or mapping to other frameworks (NIST SP 800-53, ISO 27001, CIS Controls, COBIT). Also trigger for questions like "how do I implement NIST CSF?", "what does CSF 2.0 change?", "help me build a CSF profile", "how do I assess my cybersecurity posture?", or any request involving organizational cybersecurity risk strategy or framework alignment.

Instrument LLM applications with Langfuse to trace, score, and monitor cost, quality, and latency across OpenAI and LangChain integrations.

Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques for 1.5-3.6× speedup without quality loss.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.

Prevents SOQL injection and enforces CRUD, FLS, and sharing in Apex queries, with guidance for building, reviewing, and troubleshooting secure data access.

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

Fast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.

Provides expertise in Langfuse for LLM observability, including tracing, prompt management, evaluation, and integration with LangChain, LlamaIndex, and OpenAI.

Creates, updates, and deletes Salesforce records from Lightning Web Components using Lightning Data Service, covering record input shapes, error handling, and cache refresh strategies.

Drafts Terms of Service and Privacy Policy documents by auditing a codebase and marketing site to infer company details, then asking only for missing information.

Reads related records across multiple sObjects in one GraphQL request, paginates related lists with cursors, and replaces overlapping @wire(getRecord) calls with a single cache-shared query.

Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.

Develops and debugs Apex code, builds Lightning Web Components, optimizes SOQL queries, and manages Salesforce DX deployments with CI/CD pipelines.