Results for “logcat”

Log and search local text entries from the command line. Use when adding quick notes, searching past entries, or exporting a simple activity log.

Reference for building real-time voice and multimodal AI applications with Pipecat, covering pipelines, speech services, LLMs, transports, and deployment.

Provides a reference for building real-time voice and multimodal AI agents with Pipecat, covering pipeline architecture, speech services, LLM integration, transports, and deployment.

Logback - flexible and powerful logging framework for Java and Spring Boot applications. Successor to Log4j with native SLF4J support, async logging, and automatic file rotation. USE WHEN: user mentions "logback", "spring boot logging", "java logging configuration", asks about "logback-spring.xml", "rolling file appender", "async logging in java" DO NOT USE FOR: SLF4J API usage - use `slf4j` instead, Log4j2 - use separate Log4j2 skill, Node.js logging - use `winston` or `pino` instead, Python logging - use `python-logging` instead

Documentation and capabilities reference for Daily

Reference for building real-time voice and multimodal AI agents with Pipecat, covering pipelines, speech services, LLMs, transports, and deployment.

Documentation and capabilities reference for Daily

Documentation and capabilities reference for Daily

Imported skill input from langchain

Documentation and capabilities reference for Daily

debug-logging

Build cross-platform AI chat interfaces with Makepad using MolyKit, including async utilities, chat widgets, and OpenAI-compatible client integration.

Java logging with SLF4J facade, Logback, and Log4j2 implementations. Covers configuration, log levels, structured logging, async logging, and production best practices for Spring Boot applications. USE WHEN: user mentions "java logging", "spring boot logging", "slf4j setup", asks about "how to log in java", "logback vs log4j2", "java logging best practices" DO NOT USE FOR: Node.js logging - use `nodejs-logging` instead, Python logging - use `python-logging`, Kotlin-specific logging - similar but has nuances

Documentation and capabilities reference for Daily

Deploy Meta's LlamaGuard moderation model to filter LLM inputs and outputs across 6 safety categories using HuggingFace, vLLM, or FastAPI.

Documentation and capabilities reference for Daily

Reference for building real-time voice and multimodal AI applications with Pipecat, covering pipelines, speech services, LLM integration, and transports.

Fetches and analyzes LangSmith execution traces to debug LangChain and LangGraph agents, investigating errors, tool calls, and performance.

Computes the LogAUC metric using the torchmetrics implementation for binary, multiclass, or multilabel classification tasks.

Loki is a horizontally scalable log aggregation system built by Grafana Labs. Unlike traditional log platforms that index the full text of every log line, Loki indexes only metadata labels, making it significantly cheaper to operate. It integrates natively with Grafana for querying and visualization, and uses LogQL — a query language inspired by PromQL — to filter, parse, and aggregate log streams.

Use when a human asks to check wallet balances or send/transfer BTC, SPACE, DOGE, or OPCAT to an address; do not use this skill for on-chain content publishing, remote service delegation, or identity/network management.

{'CRITICAL': 'Use for MolyKit AI chat toolkit. Triggers on:'}

Reads and analyzes application logs for debugging and monitoring.

Analyzes application logs to identify errors, performance issues, and security incidents

Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel batch processing, returning native rdkit.Chem.Mol objects. Use when running standard cheminformatics pipelines on molecule tables with minimal boilerplate; for low-level control, custom sanitization, or specialized algorithms prefer alterlab-rdkit. Part of the AlterLab Academic Skills suite.

Documentation and capabilities reference for Daily

Documentation and capabilities reference for Daily

Route LangSmith work into one workflow packet before touching SDK code. Use when the user needs LangSmith tracing, offline evals, annotation/review queues, prompt-registry decisions, audit/gap review, or cross-service trace propagation for an LLM app or agent workflow. Choose one packet: trace-debug, eval, review, prompt-registry, propagation, or audit. Triggers on: LangSmith, LangChain tracing, `@traceable` / `traceable`, `wrap_openai` / `wrapOpenAI`, datasets, experiments, annotation queues, feedback criteria, Prompt Hub, run trees, trace IDs, or production confidence for an AI feature. Not for generic SLO/alert design, non-LangSmith deployment orchestration, or runtime guardrails outside LangSmith.

Logging in Acorn/WordPress — Log::debug(), Log::error(), Log::channel(), custom log channels, daily log files, stack channel, Slack log notifications, exception handling logging, WordPress debug.log integration, WP_DEBUG_LOG, structured logging, context arrays, monolog handlers, log levels, emergency info warning error debug, lando logs, lando ssh tail log

Documentation and capabilities reference for Daily

Provides the RDKit cheminformatics toolkit for low-level, fine-grained molecular primitives — SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure/SMARTS search, 2D/3D coordinate generation, similarity, and reaction handling. Use when custom sanitization, specialized fingerprint or descriptor algorithms, reaction enumeration, or conformer generation demand direct API control; for a high-level pandas-friendly wrapper over RDKit prefer alterlab-datamol, and for turning molecules into ML feature vectors prefer alterlab-molfeat. Part of the AlterLab Academic Skills suite.

Documentation and capabilities reference for Daily

Documentation and capabilities reference for Daily

Documentation and capabilities reference for Daily

Reference for building real-time voice and multimodal AI applications with Daily and Pipecat, covering pipeline architecture, AI service integrations, transports, and client SDKs.