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Found 234 Skills
Extract and analyze Agentforce session tracing data from Salesforce Data 360. Supports high-volume extraction (1-10M records/day), Polars-based analysis, and debugging workflows for agent sessions.
Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
INVOKE THIS SKILL when working with LangSmith tracing OR querying traces. Covers adding tracing to applications and querying/exporting trace data. Uses the langsmith CLI tool.
Idiomatic context.Context usage in Golang — creation, propagation, cancellation, timeouts, deadlines, context values, and cross-service tracing. Apply when working with context.Context in any Go code.
Golang everyday observability — the always-on signals in production. Covers structured logging with slog, Prometheus metrics, OpenTelemetry distributed tracing, continuous profiling with pprof/Pyroscope, server-side RUM event tracking, alerting, and Grafana dashboards. Apply when instrumenting Go services for production monitoring, setting up metrics or alerting, adding OpenTelemetry tracing, correlating logs with traces, migrating legacy loggers (zap/logrus/zerolog) to slog, adding observability to new features, or implementing GDPR/CCPA-compliant tracking with Customer Data Platforms (CDP). Not for temporary deep-dive performance investigation (→ See golang-benchmark and golang-performance skills).
Add Opik tracing to an existing codebase. Detects language (Python/TypeScript), identifies LLM frameworks, adds appropriate decorators and integrations, marks entrypoints, and wires up environment config. Use for "instrument my code", "add opik tracing", "add observability", or "trace my agent".
Instrument, trace, evaluate, and monitor LLM applications and AI agents with LangSmith. Use when setting up observability for LLM pipelines, running offline or online evaluations, managing prompts in the Prompt Hub, creating datasets for regression testing, or deploying agent servers. Triggers on: langsmith, langchain tracing, llm tracing, llm observability, llm evaluation, trace llm calls, @traceable, wrap_openai, langsmith evaluate, langsmith dataset, langsmith feedback, langsmith prompt hub, langsmith project, llm monitoring, llm debugging, llm quality, openevals, langsmith cli, langsmith experiment, annotate llm, llm judge.
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.
Observability audit worker (L3). Checks structured logging, health check endpoints, metrics collection, request tracing, log levels. Returns findings with severity, location, effort, recommendations.
Run MassGen experiments and analyze logs using automation mode, logfire tracing, and SQL queries. Use this skill for performance analysis, debugging agent behavior, evaluating coordination patterns, and improving the logging structure, or whenever an ANALYSIS_REPORT.md is needed in a log directory.
Composable binary security suite for static analysis, dynamic tracing, contract capture, baseline drift, and policy gating. Triggers: "binary security", "reverse engineer binary", "black-box binary test", "behavioral trace", "baseline diff", "security suite".
strace and ltrace skill for system call and library call tracing. Use when a binary behaves incorrectly without crashing, diagnosing file-not-found errors, permission failures, network issues, or unexpected library calls by tracing syscalls and library function calls. Activates on queries about strace, ltrace, syscall tracing, library interception, ENOENT, EPERM, strace -e, or diagnosing binary behaviour without a debugger.