「uat」の検索結果

模型评估全流程。覆盖分类/回归/排序/生成/RAG/LLM 评估、A/B 测试、 在线监控、数据漂移检测、评估集构建、基准测试。 触发关键词：评估、指标、Precision、Recall、F1、AUC、BLEU、ROUGE、 A/B 测试、基准测试、数据漂移、模型监控、RAGAS、LLM-as-Judge。

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。

Strategic analysis gate for existing products — multi-dimensional evaluation (tech, product, design, business) using Design Thinking + 9 Windows (TRIZ) + Double Diamond. Outputs 2-3 qualified options with recommendations. Use BEFORE cm-planning for complex initiatives and enhancements on existing codebases.

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 an HLD note against linked ADRs, requirements, and architecture principles across six dimensions

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 an architecture artifact (ADR, HLD, LLD) against the vault's established architecture principles

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 proposed repository harness changes with pinned Darwin tools and explicit evidence 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。

Generate A-share end-of-day market review reports with Pandadata data, covering trade-date checks, index performance and valuation, market breadth, limit-up/down sentiment, industries/concepts, 龙虎榜, block trades, margin financing, northbound holdings, risk notes, and optional scheduled after-close automation. Use when the user asks for 今日复盘, 收盘总结, 每日市场报告, A股复盘, 龙虎榜复盘, 北向资金动向, or to set up an automated daily market review.

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。

Use when evaluating, comparing, installing, or recommending a Claude Code plugin, Agent Skill, MCP server, agent toolkit, or GitHub-hosted AI extension, especially when popularity is weak evidence or the candidate requests shell, network, filesystem, or credential access.

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。

Use EnterpriseRAG-Bench to evaluate an enterprise RAG or knowledge-agent system against a realistic synthetic company corpus with answer, recall, and comparative scoring.

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。

Add a runtime guard that evaluates agent actions, blocks dangerous commands or secret exposure, and audits new skills before they run.

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。

Score deep research agents on benchmark tasks using factual verification, report-quality scoring, and process evaluation before model or workflow changes ship.

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。

Run concurrent scripted conversations against a target agent to measure whether it stays on task, responds correctly, and holds up in repeatable test cases.

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。

Run a repeatable evaluation suite for browser agents against static web task snapshots instead of judging them from demos or one-off tests.

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。

Query Chinese A-share, ETF, index, financial statement, valuation, capital-flow, and technical-indicator data through the AShareHub Python SDK and hosted API. Use this skill when an agent needs structured China market data as pandas DataFrames.

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。

Expert competitive intelligence and strategy guidance for B2B/SaaS companies. Use when conducting competitive research, creating battlecards, analyzing win/loss data, building market landscape maps, positioning against alternatives, handling competitive objections, writing comparison pages, or developing sales enablement for competitive situations. Use for competitive monitoring, feature comparisons, and market intelligence gathering.

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。

Expert Architecture Decision Record (ADR) creation and lifecycle management based on Olaf Zimmermann's methodology. Use when creating ADRs, reviewing architectural decisions, evaluating decision readiness, writing MADR templates, assessing decision quality, or managing ADR logs. Covers the full lifecycle from readiness (START criteria) through creation, MADR formatting, completion (ECADR criteria), and ongoing maintenance.

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Map testable surfaces, audit existing tests for quality, and write test specifications that prevent AI shortcuts. Use when asked to "audit tests", "specify tests", "test architect", "map test coverage", or invoke /test-architect. Two modes — audit (evaluate existing tests against Beck's principles) and specify (write test specs for new code). Powered by Carmack × Beck quality-testing.md reference doc. Stack: Next.js App Router / TypeScript / Vitest / Cypress / tRPC / Prisma / Neon.

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。

World-class practice research. This skill should be used when the user asks what the best in the world does about a specific problem, technique, or situation — covering product, engineering, design, marketing, compliance, operations, org design, and any other domain. Use when the goal is to understand elite-tier practice, not to make a strategic decision. Distinct from best-in-world-strategy, which is for choosing between options.

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。

Excellence-first strategic decision support. This skill should be used when users need to choose between options, pressure-test a plan, evaluate risk, or make a specific decision — across security, product, growth, operations, org design, and finance. Use when there is a decision with tradeoffs to score and a recommendation to make. For pure research ("what does the best in the world do about X?"), use best-in-world-research instead.

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。

Template skill for a leadership-transition / executive cockpit — when someone steps into or covers a leadership role and needs to not drop anything. Produces a handoff doc + decision-rights map, an "open loops" tracker, a team-comms cadence, and a recurring report/update drafter. Trigger on "/exec-cockpit", "handoff doc", "decision-rights map", "open loops tracker", "cover for <role>", "interim <role>". Customize the placeholders to your situation.

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。

Nature-style remote-sensing manuscript reviewer skill for evaluating Earth-observation products, retrievals, machine-learning maps, validation design, uncertainty propagation, spatial transferability and claim-scope calibration.

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。

Use to evaluate a service or feature against Downe's 15 principles of good services.

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 user-facing interfaces against Nielsen's 10 Usability Heuristics. Complements /mycelium:service-check (Downe = service-level quality, Nielsen = interface-level 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。

Assess team structure against Skelton's Team Topologies. Evaluate cognitive load, interaction modes, and Conway's Law alignment.

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。

Use to analyze correction trends, surface recurring patterns, and graduate repeat corrections to guardrails or anti-patterns.

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。