Results for “metrics”

Implements a complete observability stack with Prometheus metrics, Grafana dashboards, Jaeger distributed tracing, and structured logging, including heartbeat-based absence detection for scheduled jobs on Google Cloud.

Evaluates speaker verification models by computing true positive rate at fixed false positive rate thresholds, probing embedding space separation of same-speaker versus different-speaker pairs.

Query Google Analytics 4 (GA4) data via the Analytics Data API. Use when you need to pull website analytics like top pages, traffic sources, user counts, sessions, conversions, or any GA4 metrics/dimensions. Supports custom date ranges and filtering.

Query Google Analytics 4 (GA4) data via the Analytics Data API. Use when you need to pull website analytics like top pages, traffic sources, user counts, sessions, conversions, or any GA4 metrics/dimensions. Supports custom date ranges and filtering.

Deploy, debug, and operate the RTVI-CV 2D detection/tracking microservice and call its REST API for stream management, health checks, and metrics.

Fetch any X/Twitter post as clean LLM-friendly JSON, converting x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics.

Transforms a raw product idea into four planning files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with kill criteria.

Query EAS Update health metrics from the CLI: crash rates, install/launch counts, unique users, payload size, and embedded vs OTA user splits per channel.

Compares 2–5 audience segments side by side across key metrics, identifying winners, losers, and significant differences to inform product decisions and personalization strategy.

Compares the performance of two or more audience segments across key metrics side by side, using Adobe Analytics data to determine winners, losers, and spreads for each metric.

Scrapes tweets from X (Twitter) by search query, user handle, or direct URL, returning structured data including text, author info, engagement metrics, media, and hashtags.

Collects tweets from an X (Twitter) user profile timeline by handle, supporting tweets, replies, or media-only modes, and returns structured data with engagement metrics and pagination.

Extract public Trustpilot company profile data from a company domain, including TrustScore, star rating, review counts, verification flags, category, contact info, and optional reply behavior metrics.

Access AI-ready drug discovery datasets and benchmarks from Therapeutics Data Commons, covering ADME, toxicity, drug-target interactions, and molecular generation with standardized splits and evaluation metrics.

Build clinical deep-learning pipelines with PyHealth: load EHR, signal, and imaging datasets, define prediction tasks, instantiate models, train with the PyHealth Trainer, and compute clinical metrics.

Reduces SOC alert fatigue by tuning detection rules, consolidating duplicate alerts, implementing risk-based alerting, and measuring alert quality metrics to maintain analyst effectiveness.

Consulte métricas de uso de recursos para serviços Railway. Use quando o usuário perguntar sobre uso de recursos, CPU, memória, rede, disco ou desempenho do serviço, como "quanto de memória meu serviço está usando" ou "meu serviço está lento".

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

Validates, tests, and scores the quality of skills within a claude-skills ecosystem using Python scripts that check structure, syntax, runtime, and multi-dimensional quality metrics.

Calculate and model paid-media financial metrics including CPA, CPL, CPC, CPM, ROAS, MER, break-even targets, contribution margin, LTV:CAC, impression-share opportunity, budgets, forecasts, and experiment economics.

Analyzes past agent sessions to identify recurring failures and skill gaps, then automatically creates or patches skills and runs self-evolution to fix them, tracking improvement over time.

Collect local and remote Redpanda diagnostics bundles and inspect broker process info using the `rpk debug` command group, including triaging enterprise features from captured logs, metrics, and profiles.

CAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Use for CAPA investigations, 5-Why analysis, fishbone diagrams, root cause determination, corrective action tracking, effectiveness verification, or CAPA program optimization.

Five-phase pipeline (triage → clarify → research → PRD → plan) that turns a raw idea into four linked files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with mermaid user journey and kill criteria.

CAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Use for CAPA investigations, 5-Why analysis, fishbone diagrams, root cause determination, corrective action tracking, effectiveness verification, or CAPA program optimization.

Five-phase pipeline (triage → clarify → research → PRD → plan) that turns a raw idea into four linked files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with mermaid user journey and kill criteria.

Five-phase pipeline (triage → clarify → research → PRD → plan) that turns a raw idea into four linked files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with mermaid user journey and kill criteria.

Five-phase pipeline (triage → clarify → research → PRD → plan) that turns a raw idea into four linked files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with mermaid user journey and kill criteria.

Five-phase pipeline (triage → clarify → research → PRD → plan) that turns a raw idea into four linked files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with mermaid user journey and kill criteria.

Five-phase pipeline (triage → clarify → research → PRD → plan) that turns a raw idea into four linked files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with mermaid user journey and kill criteria.

Five-phase pipeline (triage → clarify → research → PRD → plan) that turns a raw idea into four linked files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with mermaid user journey and kill criteria.

Synthesizes recent conversations about any topic across Reddit, Hacker News, the open web, and optionally X/Twitter into a single briefing with citations, engagement metrics, and cross-platform pattern analysis.

Generate a comprehensive product strategy using the 9-section Product Strategy Canvas, covering vision, market segments, costs, value propositions, trade-offs, metrics, growth, capabilities, and defensibility.

Extracts structured channel-level and video detail data from a YouTube channel via the BrowserAct API, including metrics like views, likes, comments, and subscriber count.

Gather keyword metrics, related terms, questions, full SERP benchmark, top-page extractions, and deep web research for a target keyword, then emit a beat spec the outline must satisfy. Triggered by /research <keyword> or as the first content stage of /blog-pipeline.