发现analytics & monitoring类别的 Claude 技能。浏览 47 个技能,找到适合您 AI 工作流程的完美功能。
Retrieves and decodes detailed transaction data from the Base mainnet using x402 micropayments.
Enables real-time log searching, metric querying, and incident triage directly within the AI agent workflow using Datadog observability.
Standardizes event tracking by implementing walkerOS's entity-action naming conventions and stateless data structures.
Guides developers through the Source-Collector-Destination architecture of walkerOS for building modular event processing pipelines.
Standardizes WordPress activity log messages using active voice and user-friendly language for audit trails.
Analyzes completed Claude Code sessions to verify tool execution, hook triggers, and artifact creation against specification files.
Profiles CPU and memory hot paths to generate flame graphs and evidence-backed performance reports.
Identifies critical implementation paths, entrypoints, and high-traffic files to streamline performance profiling and optimization tasks.
Generates evidence-based performance hypotheses by analyzing git history and specific execution paths.
Manages and compares performance test baselines to track version-over-version metrics and environment metadata.
Synthesizes performance investigation data into evidence-backed recommendations and actionable next steps.
Automates the recording of structured performance investigation notes, evidence, and decision-making logic within the AI state directory.
Guides the step-by-step creation of new walkerOS destinations using a standardized, example-driven development workflow.
Monitors production health by querying Sentry issues and event data through a secure, read-only interface.
Optimizes Google Cloud logging and monitoring with battle-tested patterns for structured logs, advanced filtering, and cost-efficient observability.
Enhances your Claude Code terminal with a real-time, customizable status bar featuring session metrics, Git context, and resource usage.
Monitors agent success rates, model latency, and execution costs to optimize AI workflow efficiency.
Standardizes multi-model validation through mandatory pre-launch checklists and structured progress tracking.
Analyzes codebases to identify performance bottlenecks, reduce bundle sizes, and accelerate build times across multiple technology stacks.
Monitor and record detailed agent session events, tool invocations, and performance metrics for deep observability.
Extracts and analyzes Agentforce session telemetry to debug agent conversations and optimize performance using Data Cloud STDM data.
Implements a mandatory tracking and validation framework for parallel multi-model AI executions to ensure structured results.
Optimizes marketing ROI through advanced attribution modeling, performance measurement, and automated reporting.
Visualizes Claude Code development cycles with a real-time monitoring dashboard for tasks, sessions, and project status.
Builds sophisticated analytics interfaces featuring KPI cards, interactive data visualizations, and real-time monitoring layouts.
Implements industry-standard observability using OpenTelemetry to provide deep visibility into system performance, logging, and distributed tracing.
Builds accessible, high-performance dashboards and data-driven interfaces using a systematic selection framework and comprehensive chart library.
Simplifies the process of adding manual data lineage tracking to Apache Airflow tasks using inlets and outlets.
Builds custom OpenLineage extractors to capture data lineage and metadata from Airflow operators.
Provides expert SaaS financial analysis and unit economics modeling for solo and bootstrapped founders.
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