928 件 ・ 関連度順
概要と使いどころ
Writes product-led content pages optimized for both search engines and AI engine citations. Produces markdown files with frontmatter, following page-type frameworks (comparison, guide, use case, learn, trust) with verified sources and no fabricated 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。
Takes existing content markdown files and builds production-final resource center pages on client websites using their existing tech stack and design system. Output is live-ready — no review pass, no placeholder content, no prototype styling. Implements hub pages, section listings, article pages, and cross-linking for Blog, Guides, Learn, and Comparisons sections.
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 screenshots, websites, moodboards, competitors, or visual examples are provided and the task needs design DNA extraction, comparison, remixing, or translation into an original design direction.
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。
Deep security audit for WordPress plugin/theme PHP code, covering issues beyond the basic sanitize/escape/nonce checklist — PHP object injection (unserialize), SSRF in remote requests, CSRF on state-changing GET handlers, mass assignment via $_POST loops, insecure file include / template injection, mail header injection, ZipSlip in archive extraction, type-juggling in auth comparisons, and TOCTOU race patterns in option/meta locks. Use after or alongside wp-security-audit when reviewing complex plugins, REST APIs, integrations that fetch remote URLs, file processors, or any code that handles uploads, archives, or self-rolled auth tokens.
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。
WooCommerce store operations through NV oOS Pro — product research, catalog cross-referencing, inventory lookups, and Shopify or Flowhub comparisons where integrations are configured.
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。
Given the product offering and existing page inventory, create new core landing and resource pages (homepage refresh, features, solutions, pricing, comparison, resource hubs, about) that capture core product intent using the query-fanout pattern. Use this skill whenever the user asks to "spawn pages", "generate landing pages", "create marketing pages", "build a pricing page", "add a solutions page", "build out the site", "fill in missing pages", or wants new top-level marketing/product pages. Output is one new page per route in the project's native file format (component or markdown), matching the existing page style and framework idiom.
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 the user asks to "package our proof points", "build reusable stat cards and case snippets", or "put proof where each pillar makes its claim"; turns claims-ledger-approved proofs into reusable proof modules — stat cards, case snippets, testimonial blocks, comparison proofs — each pinned to a message-house pillar and the ledger claim ID it substantiates, and flags any pillar making a claim with no approved proof behind it. Never adjudicates a proof: unverified or ledger-absent proofs are marked '[needs source]' and routed to the claims candidates. Not for adjudicating or substantiating claims — use offer-claims-registry; not for fabricating a benchmark to fill a gap — a missing proof is flagged, not invented; not for scoring narrative quality — use narrative-quality-auditor. 证据模块/证据卡/客户案例/主张对齐
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 the user asks to "build programmatic SEO pages", "generate pages at scale", "rank on a high-authority third-party site", "borrow domain authority", "build a vs / alternative page", "do local SEO", "optimize a Google Business Profile", or "fix NAP" — one page-build router with four modes: programmatic (template × dataset systems), parasite (barnacle publishing on Medium/Reddit/LinkedIn/GitHub), comparison (vs / alternative pages in four formats), and local (GBP + NAP + citations + location pages), each with its own thin/duplicate, honesty, or reputation-abuse guardrail. Not for finding what to target — use keyword-research or content-gap-analysis; not for drafting one standalone article — use content-writer; not for scoring a page for publish — use content-quality-auditor. 程序化SEO/批量页面/寄生SEO/借势权重/对比页/vs页/替代页/本地SEO/谷歌商家档案/NAP一致性
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 the user asks to "pick a launch date", "plan the launch window", or "set the embargo and lift time"; produces a candidate-window comparison table (conflict / tailwind / risk per window) built from industry-event cycles and the competitor launch calendar, a launch-week vs rolling-release format call, store-review buffer padding (labeled Estimated), and an embargo window definition (lift moment + timezone) submitted to the launch registry as a candidate. Not for judging the cultural moment itself — use trend-spotter; not for launch-day execution — use launch-day-conductor. 发布择时/发布窗口/竞品日历/禁运期窗口/审核缓冲
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 the user asks to "allocate my influencer budget", "optimize spend across tiers", or "compare budget scenarios"; produces a tier/platform/content allocation table, ROI and CPM/CPE projections, scenario comparisons, and mid-campaign reallocation moves. Not for building the full campaign plan — use campaign-planner. 达人预算分配/投放预算优化
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。
When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement.
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。
Trace BIRD routing-daemon behavior through the actual C source tree. Use for implementation questions, suspected upstream bugs, parser/keyword origins, filter instructions, protocol state machines, route attributes, birdc commands, stack traces, or BIRD 2 versus BIRD 3 source comparisons. Prefer a local checkout or exact upstream tag/commit and cite concrete files, functions, and revisions. Route config linting to bird-agent and active incidents to bird-troubleshooting.
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 working with Bigcommerce — bigCommerce store management including products, orders, customers, channels, shipping, inventory, storefront themes, and webhooks. Covers sales analytics, order fulfillment rates, inventory health, and multi-channel performance comparison.
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 working with Aws Step Functions — aWS Step Functions execution analysis, state machine management, error tracking, and performance optimization. Covers execution history, failure investigation, state transition metrics, Express vs Standard comparison, and workflow visualization.
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 working with Aws Batch — aWS Batch compute environment management, job queue analysis, scheduling policy review, and array job monitoring. Covers compute resource utilization, job status tracking, failure investigation, Fargate vs EC2 comparison, and queue priority 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。
Use when working with Aws Billing — analyze, break down, and report AWS costs and bills. Covers cost breakdown by service, account, or usage type; monthly/daily billing trends; cost anomaly detection; RI/SP utilization; cost forecasting; credit/discount analysis; and multi-account cost comparison. Uses anti-hallucination rules, mandatory currency/credit detection workflow, and reusable Cost Explorer functions.
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。
Claw Mar 23, 2026 Comparison 15 min min read OpenClaw vs Other AI Agent Frameworks - Comprehensive C GAP: agent framework / orchestrator SDK: competit
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。
Plan, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.
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 Tavily's multi-source research workflow for comparisons, market analysis, literature-oriented exploration, or detailed cited reports. Use only when bounded search and extraction are insufficient.
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。
X (Twitter) Scraper API and X API Alternative instructions for Xquik scraping and connected X account action planning. Also use for Xquik Radar or Xquik support tickets only when the user names that feature. Do not load or use this Skill for official X developer setup unless the user compares it with Xquik. Trigger when an X or Twitter task asks about posts, replies, likes, follows, messages, search, users, timelines, followers, exports, giveaways, draws, monitors, Xquik webhooks, MCP setup, SDKs, or API comparisons. Start read-only. Require confirmation for write plans, private reads, monitors, webhooks, support access, and metered bulk jobs. Not affiliated with X Corp.
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 recommender system quality for the CSX4207 Vinyl Record Store. Use whenever you must compute or report recommender metrics (Precision@k, Recall@k, HitRate@k, MRR, MAP@k, NDCG@k, coverage, diversity, novelty, serendipity, personalization), design an evaluation protocol/split, run a baseline comparison, or write the evaluation section of a course deliverable. Covers formulas, JavaScript reference implementations, and the reporting checklist.
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 the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.
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。
Activate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).
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 asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.
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。