「rop」の検索結果

Use when a task needs the judgment of a Chief Data Officer — resolving conflicting metric definitions across dashboards, deciding whether a dataset should be retained or purged, assigning data ownership for a system feeding regulatory or board reporting, sizing a privacy/breach risk against a proposed data collection, or auditing data readiness before an AI/ML initiative kicks off.

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 a task needs the judgment of a senior property & casualty claims adjuster — scoping a water-damage or auto-collision loss, deciding total-loss vs. repair on a damaged vehicle, drafting or checking a reservation-of-rights letter, deciding when a claim needs an SIU fraud referral vs. a routine recorded statement, or working out whether a coverage dispute should go to appraisal or litigation. A reasoning aid, not licensed adjusting authority.

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 a task needs the judgment of a professional author — drafting or structurally revising a novel or narrative-nonfiction manuscript, writing a query letter or book proposal, evaluating a publishing contract's royalty and rights terms, or diagnosing why a manuscript is getting rejected.

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 a task needs the judgment of an auto-body-repairer — deciding whether a damaged structural component gets pulled or replaced, reconciling an insurance estimate against actual teardown damage, writing a supplement, determining whether a repair triggers ADAS recalibration, or checking a proposed repair against an OEM position statement.

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 a task needs the judgment of a Biomass Plant Technician — adjusting combustion parameters in response to actual measured fuel moisture content rather than a fixed setpoint, diagnosing a fuel feed interruption as mechanical bridging rather than a combustion issue, adjusting soot-blowing frequency to actual observed slagging conditions rather than a fixed calendar schedule, or monitoring emissions more actively given fuel batch variability rather than a "set and monitor occasionally" approach appropriate for consistent fossil fuel.

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 a task needs the judgment of an astronomer — calculating exposure time or signal-to-noise for a target, writing the feasibility math for a telescope-time proposal, reducing photometric or spectroscopic data, distinguishing a systematic error floor from statistical noise, or reviewing an observational result for calibration or upper-limit red flags.

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 a task needs the judgment of an Aerospace Engineer — reconciling a vehicle mass/weight budget against a certification limit, computing a structural margin of safety, choosing a means of compliance for an FAA certification basis, tracing a weight-growth overrun back to a design decision, or evaluating a propulsion/aerodynamics tradeoff against a range or payload requirement.

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 a task needs the judgment of a licensed Architect — programming a building's spatial/functional requirements against a budget, developing a design concept against a zoning/code envelope, evaluating a fee proposal or scope-creep request, resolving a code-compliance conflict between disciplines, or working through a construction-phase change order's cost and schedule impact.

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 a task needs the judgment of a Farmer, Rancher, or other Agricultural Manager — deciding a planting/breeding mix or acreage shift under price and weather uncertainty, sizing a hedge or crop-insurance coverage level, running break-even and diversification scenarios before a capital or input commitment, or evaluating land/herd management practices against long-term productive capacity.

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 a task needs the judgment of a livestock geneticist/animal breeder — selecting a sire against EPDs or genomic data, screening a proposed mating for inbreeding risk, deciding AI versus natural service, timing an estrus-synchronization protocol, or defending a breeding-goal tradeoff to a herd owner.

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 a task needs the judgment of an Animal Caretaker — triaging daily husbandry when kennel census exceeds staffing capacity, reading a Fear-Anxiety-Stress (FAS) score change or appetite/output drop against an escalation threshold, deciding brush-out vs. shave-down on a matted coat, or setting isolation and vaccination-lead-time protocol for a new intake or boarding admission.

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 proper ENCODE citations for publications, grants, and presentations. Use when the user needs to cite ENCODE data, create bibliography entries, write acknowledgment sections, or ensure compliance with ENCODE data use policy.

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。

Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility, TIN-based quality filtering, and detection-limit-aware interpretation. Handles batch correction (Harmony/Seurat), dropout awareness, cross-contamination artifacts, and platform-specific biases. Use this skill for ANY scRNA-seq integration task, cross-dataset comparison, cell atlas construction, or reproducibility assessment involving ENCODE single-cell 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。

Smart code scanner that detects Spring Boot patterns and routes to appropriate skills. Use when editing Java or Kotlin files in Spring Boot projects, working with pom.xml/build.gradle containing spring-boot-starter, or when context suggests Spring Boot development. Detects annotations (@RestController, @Entity, @EnableWebSecurity, @SpringBootTest) to determine relevant skills and provides contextual guidance. Uses progressive automation - auto-invokes for low-risk patterns (web-api, data, DDD), confirms before loading high-risk skills (security, testing, verify).

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。

Sync official Anthropic documentation and analyze impact on project components. Runs docs/reference/update-claude-docs.sh, computes diffs, and reports impacts on the skill validator, plugins, and project documentation. Use when user mentions "sync docs", "update reference docs", "refresh docs", or "check doc changes".

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 skills against Anthropic best practices for frontmatter, structure, content, file organization, hooks, MCP, and security (62 rules in 8 categories). Use when creating new skills, updating existing skills, before publishing skills, reviewing skill quality, or when user mentions "validate skill", "check skill", "skill best practices", "skill review", or "lint skill".

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。

Guide users through structured collaborative documentation creation. Use when user wants to write documentation, update README, create architecture docs, draft proposals, technical specs, decision docs, refactor documentation, create API docs, or document code.

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。

Comprehensive SEO analysis for any website or business type. Orchestrates 52 sub-skills (52 active): full site audits, technical SEO (CWV/INP), schema, E-E-A-T content quality, images, sitemaps, GEO for AI Overviews, llms.txt generation, AI crawler audit, plus live GSC and Ahrefs MCP data. GSC: overview, drops, opportunities, brand-vs-nonbrand, cannibalization, compare, content-decay, index-issues, new-keywords. Ahrefs: overview, backlinks, keywords, competitors, content-gap, broken-links, new-links, anchor-analysis, dr-history, top-pages. Cross-MCP: serp, content-brief, brand-radar, site-audit-pro, report. Local: log-analysis, ai-content-check, internal-links, local, migration-check, obsidian-kb. AI Readability: llms-txt, robots-ai. Performance: lighthouse-audit, core-web-vitals, page-experience. Quality & AI Search: rich-results, ai-optimization, eeat-audit, helpful-content. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "GSC", "Ahrefs", "backlinks", "keywords", "search console", "domain rating", "local SEO", "migration", "lighthouse", "pagespeed", "LCP", "INP", "CLS", "page experience", "interstitials", "mobile friendly", "rich results", "rich snippets", "schema eligibility", "AI optimization", "AI search readiness", "EEAT", "trust signals", "helpful content", "people-first", "content quality gate".

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。

Show a domain's Domain Rating trend over time from Ahrefs. Reveals DR growth, drops, and significant changes. Use when user says "DR history", "domain rating history", "DR trend", "domain rating over time", or "DR changes".

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。

Per-type rich result eligibility checker. Given a URL or page type, determine WHICH Google rich results the page is eligible for, validate existing JSON-LD against Google's required/recommended properties per type, and produce a gap report. Use when user says "rich results", "rich snippets", "eligible rich results", "structured data types", or "schema eligibility".

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。

Convert simplified Chinese to Traditional Chinese (zh-TW), covering characters, Taiwan vocabulary, and phrasing. Use when the user asks to convert 簡體 to 正體/繁體, localise mainland Chinese text for Taiwan, fix simplified characters left in a document or repository, check whether content is written in proper zh-TW, or normalise variant forms such as 着/裏/爲 to the Taiwan standard. Handles both files edited in place and text pasted into the conversation. Runs on Python 3 standard library alone, with no OpenCC and no installed packages.

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 comprehensive OpenSpec specifications directly from the current project state. Use when the user wants to create or populate main specs by analyzing existing code, documentation, AGENTS.md, GitHub issues, and pull requests — without going through the change/proposal workflow. Ideal for bootstrapping specs on a project that already has working code but no specs yet, or for refreshing specs to match the current implementation.

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。

Rewrite raw meeting audio transcriptions into clean, accurate meeting minutes in Traditional Chinese. Use when the user has an unprocessed audio transcription file with recognition errors and needs it cleaned up into proper meeting minutes.

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。

Create a git commit with clear, conventional commit messages. You MUST read this when the user wants to commit staged changes, write a commit message, or finalize code changes with proper conventional commit format since it describes how to follow the user's specific requirements.

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。