Results for “metric”

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.

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.

Executes authorized phishing simulation campaigns to assess an organization's susceptibility to email-based social engineering attacks, including scenario design, infrastructure setup, and metric tracking.

Gerencia contas do Instagram via Graph API: publica fotos, vídeos, reels, stories e carrosséis, agenda posts, responde comentários e DMs, coleta métricas, pesquisa hashtags e cria templates de conteúdo.

Quantifies the minimum accuracy gap needed between two models for a sampled micro-benchmark to reliably preserve their ranking, using the MDAD metric from Yauney et al. (2025).

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.

Measure Core Web Vitals on any URL — LCP, CLS, INP, TTFB, FCP — using the browser's own performance APIs. Grades each metric against Google's thresholds and produces an A-F report. Playwright MCP only, no signup.

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.

Benchmarks long-context language models across 20 sub-tasks spanning 3k–200k tokens, covering retrieval, reasoning, summarization, and instruction understanding, with exact-match accuracy as the primary metric.

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.

Write a rigorous, decision-grade experiment spec — falsifiable hypothesis, primary metric, guardrails, randomisation unit, exposure definition, method (A/B, holdout, switchback, quasi-experiment, MAB), MDE/duration plan, peek policy, validity threats, and pre-committed decision rule. Platform-agnostic. Load when the user has a candidate experiment and needs to spec it before launch, or says "spec this experiment", "write the test plan", "design this A/B test", "what's the hypothesis", "how big a sample do we need", "how long should we run this", "define the metrics for this test", or when the experimentation orchestrator routes here.

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.

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.

Voce e o precificador de features do REVERSA. Sua missao e cruzar o profile de cobranca do usuario com as metricas estruturais da feature ativa e produzir tres cenarios educativos em `_reversa_sdd/_pricing/<feature>/estimate.md` e `estimate.json`.

Compute fully-loaded cost-to-serve per channel, channel ROI under cash/LTV/marginal lenses, and optimal channel mix subject to strategic constraints for quarterly channel reviews.

Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics, including VPC Flow Logs, NAT, firewall, threat logs, latency, throughput, and Connectivity Tests.

Guides users through defining goals, metrics, and scope, then runs an autonomous loop of code changes, testing, measuring, and keeping or discarding results for any programming task with a measurable outcome.