「metrics」の検索結果

Build supplier performance scorecards with KPIs, quality metrics, delivery performance, cost management, and improvement plans

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Create professional equity research earnings update reports (8-12 pages, 3,000-5,000 words) analyzing quarterly results for companies already under coverage. Fast-turnaround format focusing on beat/miss analysis, key metrics, updated estimates, and revised thesis. Includes 1-3 summary tables and 8-12 charts. Use when user requests "earnings update", "quarterly update", "earnings analysis", "Q1/Q2/Q3/Q4 results", or post-earnings report.

日本語の概要は準備中です。原文の説明を表示しています。

Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models

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Apple Human Interface Guidelines as structured design values — system colors (incl. increased-contrast variants), the full Dynamic Type ramp, Liquid Glass rules and budgets, layout and hit-target metrics, SF Symbols, and HIG-to-SwiftUI component mappings. Use when styling or reviewing any Apple-platform UI: picking a color, size, spacing, corner radius, or hit target; writing .glassEffect / material code; choosing an SF Symbol; or answering 'what does the HIG say about X'.

日本語の概要は準備中です。原文の説明を表示しています。

Designs effective KPI dashboards with proper metric selection, visual hierarchy, and data visualization best practices. Use when building executive dashboards, creating analytics views, or presenting business metrics.

日本語の概要は準備中です。原文の説明を表示しています。

Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.

日本語の概要は準備中です。原文の説明を表示しています。

Monitor cloud infrastructure and applications using metrics, logs, and traces to provide real-time observability into performance, health, and reliability. Use when the user requests cloud monitoring or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Visualize and map user flows with Mermaid diagrams, decision points, error states, and conversion metrics to optimize user journeys. Use when the user requests user flow mapping or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Design privacy-aware observability for AI agents using traces, spans, structured events, metrics, cost attribution, dashboards, alerts, and investigation workflows. Use when instrumenting an agent, debugging intermittent tool or model failures, defining service-level objectives, analyzing latency or spend, auditing agent decisions, or preparing production monitoring.

日本語の概要は準備中です。原文の説明を表示しています。

Evaluate a single retort experiment run. Score the generated code against the task's TASK.md requirements, run its build and tests, compute metrics, and emit a structured evaluation report plus a machine-readable findings file.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Landscape Ecologist. Use when a task calls for Landscape Ecologist judgment. Reasons from scale-explicit pattern-process feedbacks, configuration over composition, and functional rather than graphical connectivity through FRAGSTATS, landscapemetrics, Circuitscape resistance surfaces, NLMR neutral models, and block cross-validation, while treating MAUP grain artifacts, classification error propagation, isolation-by-distance confounding isolation-by-resistance, and resistance surfaces unvalidated by movement as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Green Chemist. Use when a task calls for Green Chemist judgment. Reasons from Anastas–Warner 12 principles, Trost atom economy, and PMI/MMI/E-factor mass metrics; selects solvents via CHEM21/GSK/ACS GCIPR guides, integrates catalysis and LCA (ISO 14040), and aligns REACH/CSS with ACS GC&E benchmarking.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Data Scientist. Use when a task calls for Data Scientist judgment. Reasons from CRISP-DM business estimands, leakage-safe sklearn Pipelines and nested CV, SQL/warehouse semantic metrics, A/B power and SRM/AA guardrails, causal DAG covariate discipline, and Model Cards/Datasheets while treating train-test leakage, Simpson's paradox, peeking, and PSI>0.25 drift as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Conservation Biologist. Use when a task calls for Conservation Biologist judgment. Reasons from IUCN Red List A–E and Green Status recovery metrics, PVA/Ne, occupancy and distance sampling (unmarked, msocc, RMark), prioritizr/Marxan SCP, Conservation Evidence and ROSES synthesis, counterfactual impact evaluation, METT/SMART PAME, and eDNA false-positive models while treating pseudoreplication, GBIF effort bias, offset baselines, and Red List≠priority conflation as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Anatomist. Use when a task calls for Anatomist judgment. Reasons from homology, EPB, and von Baer principles through gross dissection, diceCT/μCT/MRI pipelines, UBERON–PATO EQ annotation, MorphoSource/oVert digitization, geometric morphometrics, and NAV/TA2 nomenclature while treating fixation shrinkage, segmentation artifacts, landmark homology error, and collection bias as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them and iterates until every page is visually clean). Spec 046 Q46–Q50.

日本語の概要は準備中です。原文の説明を表示しています。

Med peer benchmarking: select actual biotech/pharma peers via the med universe (drug/indication overlap where possible) and compare med-relevant metrics — pipeline depth, catalyst density, cash position, margins, valuation multiples.

日本語の概要は準備中です。原文の説明を表示しています。

Turnaround analysis, stagnation detection, performance inflection, operational improvement, restructuring analysis, management change impact, cost cutting effectiveness, business transformation, recovery trajectory, operational metrics improvement

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Captions living in 3D space around a talking head: a camera flies between the speaker and the words (whip-in, parallax truck, push), caption groups sit at different depths so camera moves pull them apart, hero words hide BEHIND the speaker through an alpha matte, a ring of words wraps round the speaker and turns in front of them, focus racks between depths, and text steps at 15 fps with ghost motion blur. Works in any type style (editorial serif, bold sans) or hand-drawn (p5.brush write-on). Trigger on: "3D text", "3D camera captions", "text around / behind the speaker", "camera moves through the text", "depth captions on my avatar video". Covers prep (portion, padded plate, matte, word clock, font metrics), the shot grammar, depth rules, QC, and limits.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze influencer performance metrics across TikTok, Instagram, YouTube, Bilibili, and Kuaishou. Compare engagement rates, audience growth, content consistency, and cross-platform presence for data-driven partnership decisions.

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Assesses genetic health of populations for conservation using effective population size estimation (GONE2 for recent Ne trajectory, NeEstimator for contemporary Ne, Stairway Plot 2 and PSMC for historical Ne), F-statistics (hierfstat), runs of homozygosity (detectRUNS), and genetic diversity metrics. Use when estimating effective population size, detecting inbreeding or bottlenecks, or assessing genetic diversity in threatened species from microsatellite or SNP data.

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Calculates species richness, diversity, and turnover using the Hill number framework with iNEXT coverage-based rarefaction/extrapolation, asymptotic diversity estimation, and beta diversity partitioning (betapart turnover vs nestedness). Compares assemblages using coverage-standardized rather than size-standardized rarefaction. Use when quantifying biodiversity from species abundance or incidence data, comparing diversity across sites, or constructing rarefaction curves. Not for clinical 16S microbiome alpha/beta diversity (see microbiome/diversity-analysis).

日本語の概要は準備中です。原文の説明を表示しています。

Validate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics. Use when verifying alignment data quality before variant calling or quantification.

日本語の概要は準備中です。原文の説明を表示しています。

Assess genome assembly quality using QUAST for contiguity metrics and BUSCO for completeness. Essential for evaluating assembly success and comparing assemblers. Use when evaluating assembly completeness and quality.

日本語の概要は準備中です。原文の説明を表示しています。