本文へ移動
cccskills

「metric」の検索結果

2,237 件 ・ 関連度順

概要と使いどころ

Tests whether changes caused a metric move without a clean A/B test: DiD, synthetic control, IV, RDD. Use when asking did a launch cause lift.

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。

vasilyu1983/AI-Agents-public972026年10月12日 更新

Builds QA harnesses and agent evals. Use when evaluating tool, trace, red-team, regression, multi-agent, or carried-workspace coding trajectories. Not for metric design (ai-evals).

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。

vasilyu1983/AI-Agents-public972026年10月12日 更新

Measures AI coding impact and extension robustness. Use when tracking delivery, quality trajectories, cost, experience, pilots, scorecards, or leadership reporting.

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。

vasilyu1983/AI-Agents-public972026年10月12日 更新

Scores team or opt-in individual contribution quality from commit and PR history. Use when building engineering scorecards or coaching; for AI impact use dev-ai-coding-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。

vasilyu1983/AI-Agents-public972026年10月12日 更新

Generates a comprehensive milestone progress review including feature completeness, quality metrics, risk assessment, and go/no-go recommendation. Use at milestone checkpoints or when evaluating readiness for a milestone deadline.

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。

striderZA/OpenCodeGameStudios932026年10月7日 更新

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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。

ruvnet/agentdb922026年10月12日 更新

Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms

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。

ruvnet/agentdb922026年10月12日 更新

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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。

ruvnet/agentdb922026年10月12日 更新

launch

無料

Planning releases and reporting delivery work from GitHub PR history. Use when versioning, CHANGELOGs, rollout or rollback plans, engineering metrics, retrospectives, or stakeholder reports are needed.

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。

simota/agent-skills922026年10月14日 更新

Search TikTok e-commerce trending promotional video leaderboards via Kalodata and query detailed data for specific videos. Supports viewing high-ranking/high-view/hot-selling promotional videos by region, currency, language, and date range, and using videoId to retrieve views, likes, comments, shares, revenue, GPM, and advertising metrics. Trigger when users mention TikTok video search, TikTok video ranking, TikTok viral video chart, TikTok video detail, video analytics, kalodata video search/detail. Even if the user does not explicitly mention "kalodata", trigger this skill whenever their need involves viewing TikTok trending promotional video leaderboards or detailed sales and engagement data for a specific TikTok video.

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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Search and analyze TikTok product data including sales, influencer sales data, pricing, and commission rates across 16 TikTok Shop sites. Trigger when users mention TikTok product search, TikTok Shop product analysis, TikTok sales data, influencer sales, TikTok product selection, TikTok commission rate, TikTok product ranking, Nexscope data query, TikTok product search, TikTok sales, influencer sales, TikTok commission, TikTok product selection, short-video e-commerce, TikTok data. Even if the user does not explicitly mention "Nexscope" or "TikTok", trigger this skill whenever their need involves searching products on TikTok Shop or analyzing TikTok product performance 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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Nexscope Ozon Russia category drill-down product list by Russian category path. Returns all products in a category with complete metrics: sales, revenue, price, rating, stock, turnover, lost revenue, supporting multi-dimensional numeric filters, sorting, and currency conversion. Use for category bestseller mining, blue-ocean insight discovery, category ranking analysis, brand landscape observation. Trigger when the user mentions Ozon category drill-down, Ozon category products, Ozon blue-ocean mining, Ozon category bestsellers, Ozon category ranking, Ozon subcategory structure, Ozon niche SKUs, Nexscope category, Ozon category drill-down, Russian marketplace niche, Ozon niche mining, Ozon subcategory bestseller. Also trigger when the intent is to view all products and their sales/price/ranking performance under an Ozon category path, even without explicitly mentioning Nexscope.

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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Nexscope Ozon Russia seller drill-down product list by seller ID. Returns all SKUs under a seller with complete metrics: sales, revenue, price, rating, stock, turnover, lost revenue, supporting multi-dimensional numeric filters, sorting, and currency conversion. Use for store structure analysis, seller bestseller analysis, competitor store benchmarking. Trigger when the user mentions Ozon seller products, Ozon store analysis, Ozon seller drill-down, Ozon seller SKUs, Ozon store bestsellers, Ozon competitor store, Nexscope seller, Ozon seller drill-down, Ozon shop audit, Russian marketplace seller SKUs, Ozon store structure. Also trigger when the intent is to view all products and their sales performance under an Ozon seller ID, even without explicitly mentioning Nexscope.

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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Nexscope Ozon Russia brand drill-down product list. Returns all products under an Ozon brand display name (Russian/Latin) with complete metrics: sales, revenue, price, rating, stock, turnover, lost revenue, supporting multi-dimensional numeric filters, sorting, and currency conversion. Use for brand benchmarking, competitor analysis, brand product structure research, SKU-level bestseller analysis. Trigger when the user mentions Ozon brand drill-down, Ozon brand products, Ozon competitor brand analysis, brand structure, brand SKUs, brand bestsellers, Ozon brand sales, Nexscope brand, Ozon brand products, brand drill-down, brand competitor analysis, Russian marketplace brand SKUs, brand revenue share. Also trigger when the intent is to view all products and their sales/price/rating performance under an Ozon brand, even without explicitly mentioning Nexscope.

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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Amazon product discovery and potential bestseller mining via Nexscope data. Triggered when users mention product mining, potential bestsellers, high-conversion product selection, click growth analysis, market growth opportunities, keyword-based product selection, FBA profit screening, niche market product discovery, seller origin filtering, Nexscope data, FBA profitability screening, keyword-based product selection. Even if users do not explicitly mention "Nexscope", this skill should be triggered whenever the task involves keyword-driven Amazon product selection based on conversion rates, click volume, and profitability 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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Advanced Amazon product search and filtering powered by Nexscope data, supporting multi-dimensional criteria including category, price, monthly sales, keywords, BSR rank, review count, rating, package dimensions, weight, fulfillment type, and more. Trigger when users mention Nexscope product selection, Amazon product search, advanced product selection, BSR filtering, sales rank filtering, keyword-based product discovery, category search, competitor screening, niche product discovery, historical rank filtering, or similar terms. Even if the user does not explicitly mention "Nexscope," trigger this skill whenever the request involves multi-criteria Amazon product search, sales-metric-based filtering, or advanced product selection beyond simple keyword search.

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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Use Nexscope data to find and analyze competitors on Amazon, covering 12 marketplaces, with product metrics including sales, BSR, pricing, ratings, and growth trends. Trigger when the user mentions competitor lookup, competitor analysis, ASIN reverse lookup, competitive product research, finding similar products, market competitor discovery, product benchmarking, competitor sales estimation, analyzing competitor listings, competitor analysis, ASIN reverse lookup, competitor sales, competitor research, Nexscope, market competitor discovery, competitor trends. Even if the user does not explicitly mention "Nexscope" or "competitor lookup", if their need involves discovering and analyzing Amazon competitors by ASIN, keyword, seller name, brand, or category, this skill should also be triggered.

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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Use Nexscope market statistics capability to output a market statistics dashboard by category node, including top listing average rating, average price, BSR, sales, seller count, and new product related metrics, suitable for quickly assessing the market quality and competitive landscape of a category. Trigger when the user mentions category market statistics, market selection dashboard, market fundamentals assessment, node market quality, top product statistics, Nexscope market statistics, category statistics. Even if the user does not explicitly mention "Nexscope", if the need is to view aggregated statistical results by category node, this skill should also be triggered.

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。

nexscope-ai/nexscope-ecommerce-skills912026年10月14日 更新

Interpret learning analytics data and translate dashboard findings into actionable teaching decisions. Use when reviewing LMS data, quiz patterns, or engagement 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。

nota-america/forgecat-agent-profiles912026年9月24日 更新

Run metric-driven optimization loops. Use when improving measurable outcomes such as search relevance, clustering quality, build performance, prompt quality, or scored behavior through experiments.

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。

nota-america/forgecat-agent-profiles912026年9月24日 更新

pricing

無料

When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' or 'should I offer a free plan.' Use this whenever someone is figuring out what to charge or how to structure their plans. For in-app upgrade screens, see paywalls.

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。

nota-america/forgecat-agent-profiles912026年9月24日 更新

Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.

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。

nota-america/forgecat-agent-profiles912026年9月24日 更新

stats

無料

Display project statistics — phases, plans, requirements, git metrics, and timeline

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。

buildomator/buildomator902026年10月14日 更新

retro

無料

Engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with trend tracking. Per-person breakdowns, shipping streaks, and actionable improvements. Use when asked for "retro", "weekly review", "what did we ship", or "engineering retrospective".

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。

Rune-kit/rune862026年8月16日 更新