「metrics」の検索結果

Light carved wood in a dark room in three.js, with procedural grain and pores, one warm key through a window, soft shadows that touch, light shafts, background rays and dust, then score the render out of 10 on an anchored rubric with a runnable headless scorecard and iterate until each item reaches the target. Use for oiled timber, kumiko, joinery and workshop scenes; wood that reads flat, plastic or washed out; volumetrics that lift the blacks; "score this out of 10"; or "get the lighting to 8".

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。

Extracts and structures source material (articles, transcripts, notes) into a talk summary with narrative arc, themes, metrics, and gaps. Auto-detects REX vs Concept type. Use when starting a new talk from any source material or auditing existing material before committing to a talk.

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。

Performs git archaeology, changelog analysis, and builds a verified factual timeline by cross-referencing git history with source material. REX mode only (skipped automatically in Concept mode). Use when building a REX talk and you need verified commit metrics, release timelines, and contributor data from a git repository.

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5-phase planning: PRD analysis, design review, technical decisions, dynamic research team, metrics. Produces a complete implementation plan + ADRs before any code is written.

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。

Autonomous improvement loop: scan codebase metrics, scaffold experiment files, run agent-driven iterations until metric improves

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。

This skill helps users automatically extract channel-level and video detail data from a specific YouTube channel via BrowserAct API. Agent should proactively apply this skill when users express needs like extracting channel video data, getting latest or popular videos from a YouTube channel, tracking competitor channel content, extracting video metrics such as views likes comments, retrieving subscriber count and channel info, monitoring posting cadence of a YouTube channel, gathering video data for content strategy analysis, getting earliest videos of a YouTube creator, analyzing engagement signals across a full channel, and downloading structured YouTube video details without manual scraping.

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。

Scrapes tweets from X (Twitter) by search query, user handle, or direct URL — returns full tweet data including text, author info, engagement metrics, media, and hashtags. Use when user mentions X, Twitter, tweet scraping, scrape tweets, get tweets, fetch tweets, twitter data, x.com data, tweet collector, tweet search, twitter search, social media scraping, twitter handle scraping, scrape user tweets, from:username, twitter keyword search, hashtag search, twitter timeline, twitter list scraping, collect twitter posts, export tweets, tweet analysis, twitter monitoring, search twitter, get twitter data, twitter api alternative, tweet dump.

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。

Searches Threads posts by keyword or hashtag and returns matching posts with engagement metrics, extracted from SSR-embedded JSON. Use when user asks to search Threads posts, find Threads content by topic, scrape Threads search results, collect Threads posts about a keyword, monitor Threads hashtag activity, pull Threads posts mentioning a term, gather Threads content by hashtag, search for posts on Threads, extract Threads search feed, get trending posts on Threads, find Threads discussions about a subject, or fetch recent or top Threads posts by keyword.

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。

Fetches public posts from a Threads user's profile page, extracting post text, engagement metrics, and media info from SSR-embedded JSON. Use when user asks to scrape Threads posts, get someone's Threads feed, pull posts from a Threads account, collect Threads content by username, download Threads user posts, extract Threads profile posts, monitor a Threads user's activity, retrieve recent posts from a Threads handle, gather Threads post data for a creator, or fetch all posts from a specific Threads profile.

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。

Trustpilot company profile lookup on trustpilot.com — input a company domain (e.g. apple.com, shopify.com, shopwagandtail.com) and extract company metadata: official display name, businessUnitId, TrustScore (1-5), star rating, total review count, last-12-months review count, primary category and all categories, verification flags (verifiedByGoogle, verifiedPaymentMethod, verifiedUserIdentity), claimed/closed status, website URL, contact info (email, phone, country, city, address, zip), profile image, and optional reply behavior metrics (averageDaysToReply, replyPercentage, negativeReviewsWithRepliesCount, companyUsesAIResponses). Detects company-not-found and returns isCompanyFound=false with the searched domain. Use when user mentions Trustpilot company info, Trustpilot TrustScore, look up Trustpilot rating, check Trustpilot stars, Trustpilot business profile, Trustpilot review count, Trustpilot company lookup, Trustpilot verification status, Trustpilot reply percentage, Trustpilot AI responses, business unit ID Trustpilot, get company rating from Trustpilot, scrape Trustpilot company, batch enrich domains with Trustpilot, bulk company info Trustpilot, fast domain enrichment with TrustScore, Trustpilot company metadata, Trustpilot brand monitoring, competitor TrustScore comparison, trustpilot.com domain enrichment, trustpilot company profile, trustpilot domain check, trustpilot business listing, check if company is on Trustpilot, Trustpilot category lookup, company contact info from Trustpilot. Also applies to lead-list enrichment with reputation scores, supplier vetting, agency or KOL vetting via review reputation, aggregator sites that need TrustScores for many domains, due-diligence workflows, and pre-outreach reputation checks.

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。

This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API. The Agent should proactively apply this skill when users request searching for YouTube videos and their comments, analyzing viewer sentiment for a specific video topic, gathering audience feedback on AI or automation, extracting a list of top videos and their viewer reactions, compiling YouTube video data along with user opinions, retrieving competitor video titles and related audience discussions, monitoring public response to specific YouTube search keywords, summarizing comments from search results for market research, tracking viewer engagement metrics and replies for trending topics, collecting YouTube video URLs and author details alongside community discussions, or automating the extraction of YouTube comments without manual scraping.

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。

Scrapes posts from any public Facebook Page timeline, returning structured data including post text, author info, engagement metrics (likes/comments/shares), reaction breakdowns (like/love/haha/wow/sad/angry/care), hashtags and external links, and media type. Use when user wants to scrape Facebook posts, extract Facebook page content, get Facebook post data, collect Facebook engagement stats, download Facebook posts, monitor a Facebook page, crawl Facebook timeline, get Facebook reactions, get like count/comment count/share count from Facebook, Facebook post bulk export, Facebook social media analytics. Supports date range filtering (afterTime/beforeTime) and cursor-based pagination for bulk collection.

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。

Scrapes posts from any public Facebook Page or personal Profile timeline, returning structured data including post text, author info with profile picture, engagement metrics (likes/comments/shares), full reaction breakdown (Like/Love/Wow/Haha/Sad/Angry/Care as both array and flat counts), hashtags and external links, media assets with full thumbnail URLs and dimensions, page ad library status, and collaborators. Use when user wants to scrape Facebook posts, extract Facebook page content, get Facebook post data, collect Facebook engagement stats, download Facebook posts, monitor a Facebook page, crawl Facebook timeline, get Facebook reactions, get like count comment count share count from Facebook, Facebook post bulk export, Facebook social media analytics, get profile picture, get page ad library status, fetch Facebook collaborators. Supports date range filtering (afterTime/beforeTime) and cursor-based pagination for bulk collection.

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。

This skill helps users extract GitHub repository project details and contributor contact information using keywords, stars, and update dates. Agent should proactively apply this skill when users express needs like search for GitHub projects by keywords, find top open-source contributors in specific domains, extract developer contacts from GitHub repositories, discover trending repositories with high stars, gather contributor profiles and social links for tech recruiting, retrieve GitHub project descriptions and metrics, build developer communities by finding active contributors, search for repositories updated recently, collect personal website and Twitter links of developers, generate targeted leads for developer tools, or track active open-source contributors for collaboration.

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。

Extracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688, 1688.com, wholesale China, alibaba wholesale, B2B China sourcing, Chinese wholesale scraper, 1688 product scrape, 1688 offer, 1688 detail, extract 1688 data, pull 1688 listings, get wholesale price, 1688 supplier info, factory stats 1688, 1688 SKU variants, 1688 product attributes, 1688 shop score, DSR score 1688, 1688 buyer protection, 1688 cross-border, 1688 dropship. Also applies to: scraping bulk product data from 1688 by offer ID list, monitoring 1688 supplier metrics, extracting 1688 pricing tiers for resale 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。

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

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。

Audit a test file or suite; produce a severity-ranked diagnostic report. ALWAYS USE for tests that verify nothing, missing/tautological assertions, swallowed/broad exceptions, flaky/order-dependent tests, duplication, or magic values. Polyglot. DO NOT USE for direct edits: writing-mstest-tests owns supplied MSTest assertions/attributes/lifecycle; code-testing owns new tests. Exclude running tests, migration, assertion metrics (assertion-quality), raw .NET coverage collection (run-tests), non-.NET coverage collection/analysis (native tooling), project-wide .NET coverage/CRAP (coverage-analysis), named-target .NET CRAP (crap-score), behavioral/pseudo-mutation gaps (test-gap-analysis), test-mix/ happy-vs-error classification and trait distributions (test-tagging), or the testsmells.org catalog (test-smell-detection).

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。

Activation requires either supplied .NET coverage reports/percentages/line, branch, or condition metrics, or an explicit request to collect .NET coverage for analysis. USE FOR: interpreting that evidence, including Cobertura data, partial conditions, plateaus, target arithmetic, project-wide coverage-backed CRAP, and coverage-backed refactoring safety. Analyze supplied reports directly without rerunning tests or installing tools. DO NOT USE FOR: requests with neither coverage evidence nor explicit coverage-collection intent, including hypothetical change-survival questions (use test-gap-analysis); CRAP or refactoring safety for one named target (use crap-score); or requests owned by test-tagging, find-untested-sources, test-anti-patterns, run-tests, or code-testing.

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。

Audits existing tests in any language using formal, research-backed test smell names and the testsmells.org 19-smell academic taxonomy. Use when the caller asks for an academic or citable test-smell review, named smell categories, or a formal severity-ranked smell assessment. Covers Assertion Roulette, Conditional Test Logic, Mystery Guest, Eager Test, Sleepy Test, Unknown Test, Sensitive Equality, and the rest of the catalog across .NET, Python, JavaScript/TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++. DO NOT USE FOR a quick pragmatic test review (use test-anti-patterns), writing or running tests, framework migration, coverage, or assertion-diversity 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。

Design and verify a deterministic operational-value grader for any GitHub Agentic Workflow. Use when reasoning from workflow goals to measurable downstream outcomes, defining repository evidence, choosing outcome metrics, or creating an operational-value evaluator. Usage: /operational-value-designer OWNER/REPO WORKFLOW-NAME.

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。

Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-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。

Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.

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Audit and rewrite a LinkedIn profile end-to-end for 2026: headline, About 7-step, Featured, banner, photo, Experience metrics, Skills, custom URL, recommendations. Triggers on "review my profile", "rewrite my headline", "fix my About", "optimize banner", "profile audit", "LinkedIn bio". Converts resume-style profiles to ones that convert 3-5x better. Not for writing feed content (use linkedin-post-writer).

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 any TRES Finance report XLSX and produce an automatic findings summary. Trigger this skill whenever a user uploads a .xlsx file that came from TRES Finance and asks to "analyze", "summarize", "review", "check", "audit", "look at", "what does this show", "any issues", "anything interesting", or "walk me through" the report. Also trigger when the user uploads an Excel file and mentions TRES, reconciliation, balances, transactions, cost basis, roll forward, or ERP sync. The skill identifies the report type from the file structure, runs targeted analysis based on report-specific logic, and produces a clear findings summary highlighting anomalies, key metrics, and action items.

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。