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概要と使いどころ
Audit retirement planning software for projection model accuracy, asset allocation by age, Social Security optimization, tax-advantaged account strategy, withdrawal sequencing including Roth conversion ladders, Monte Carlo simulation quality, and inflation adjustment methodology..
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 manufacturing production optimization systems for OEE (Overall Equipment Effectiveness) calculation accuracy, Six Big Losses categorization, job shop and flow shop scheduling algorithms (LP, MIP, constraint programming, genetic algorithm), Theory of Constraints bottleneck 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。
Audit investment portfolio management software for mean-variance optimization, Black-Litterman model, risk parity allocation, VaR/CVaR risk metrics, Brinson performance attribution, tax-loss harvesting rebalancing logic, Sharpe ratio calculations, efficient frontier accuracy.
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 production-grade Vehicle Routing Problem (VRP) solver using Google OR-Tools — supports CVRP (capacity), VRPTW (time windows), VRPPD (pickup + delivery), multi-depot, multi-trip, heterogeneous fleet, driver hours-of-service (HOS) compliance.
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 commercial lease optimization software -- lease abstraction quality, rent optimization (market comparison, net effective rent, blend-and-extend modeling), ASC 842/IFRS 16 accounting compliance (ROU assets, lease liabilities, discount rate methodology, modification remeasurement).
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 smart grid and power distribution optimization code for power flow solver correctness, fault detection and restoration automation, distributed energy resource management, voltage regulation, SCADA integration, and cybersecurity posture..
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 bias-free, ATS-optimized, skills-based job description for 2026. Triggers: "job description", "JD", "write a JD", "open req", "we're hiring".
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。
Optimize mining extraction operations by analyzing ore grade control, processing plant throughput, metallurgical recovery rates, energy consumption, and water balance.
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。
Generative Engine Optimization (GEO) / Answer Engine Optimization (AEO) — make a site citable by ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Triggers: "GEO", "generative engine optimization", "AEO", "answer engine optimization", "AI search optimization".
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 nonprofit fundraising software for RFM donor segmentation, campaign performance modeling with A/B testing, recurring giving retention and failed payment recovery, major gift prospect scoring using capacity-affinity-propensity frameworks, event ROI calculation.
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。
Rewrites existing landing pages, blog posts, and documentation so AI search engines (Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini) cite them. Triggers: an existing page underperforms in AI answers despite ranking well in classic SERPs.
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 mental health care planning systems for treatment goal alignment, intervention scheduling, progress milestone tracking, multi-provider coordination, step-down/step-up criteria, and individualized care pathway optimization..
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 curriculum management software for learning outcome alignment, pacing guide optimization, standards coverage mapping (Common Core, NGSS, state standards), differentiation support, assessment design quality, and content gap detection across grade levels and subjects..
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 pharmaceutical batch production records for yield optimization, process parameter tuning, deviation trending, and cycle time reduction under cGMP compliance. Triggers: phrases: "optimize batch yield", "analyze batch records", "pharma manufacturing 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。
Four-phase skill for planning and executing large-scale codebase migrations using full-context AI analysis. Produces an impact map, ordered batch plan, subagent execution protocol, and cross-codebase validation pass. Optimized for Fable 5's 1M-token context window.
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。
Analyzes mobile app binary size -- asset audit for unused images and font subsetting, code stripping with ProGuard and tree-shaking, on-demand resources, dynamic feature modules, and app thinning strategies..
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。
Full-lifecycle blog engine with 31 sub-skills, 12 templates, 100-point scoring, and 5 agents. Routes requests to the right sub-skill: writing, rewriting, analysis, outlines, audits, schema, charts, images, repurposing, AI citation SEO, FLOW prompts, topic clusters, and multilingual publishing. Optimized for Google rankings, E-E-A-T, and AI citations. Supports any platform. Use when user says "blog", "blog post", "blog audit", "topic cluster", "multilingual blog", or any /blog subcommand.
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 SEO-optimized competitor comparison and alternatives pages. Covers "X vs Y" layouts, "alternatives to X" pages, feature matrices, schema markup, and conversion optimization. Use when user says "comparison page", "vs page", "alternatives page", "competitor comparison", "X vs Y", "versus", "compare competitors", or "alternative to".
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。
Write new blog articles from scratch optimized for Google rankings and AI citations. Generates full articles with template selection, answer-first formatting, Key Takeaways summary box, information gain markers, evidence-backed explanations, sourced statistics, Pixabay/Unsplash images, built-in SVG chart generation, optional FAQ sections, internal linking zones, and proper heading hierarchy. Supports MDX, markdown, and HTML output. Use when user says "write blog", "new blog post", "create article", "write about", "draft blog", "generate blog post".
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。
Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and evidence-backed explanations. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".
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 detailed content briefs for blog posts with target keywords, content outlines, competitive analysis, recommended statistics, image and chart suggestions, word count targets, internal linking architecture, template recommendations (12 types), TL;DR drafts, evidence-backed section planning, information gain prompts, and multi-channel distribution plans. Briefs are optimized for Google rankings and AI citation visibility as part of SEO. Use when user says "content brief", "blog brief", "write brief", "SEO brief", "article brief", or "content 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。
Diagnose and draft or explicitly apply paid-ad optimizations using evidence, financial constraints, experiments, and capability-gated adapters. Use for campaign optimization, budget reallocation, bid changes, pausing or archiving ads, requests to delete campaigns, search-term or negative-keyword actions, creative rotation, or improving CPA and ROAS.
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。
Toolkit for creating animated GIFs optimized for Slack, with validators for size constraints and composable animation primitives. This skill applies when users request animated GIFs or emoji animations for Slack from descriptions like "make me a GIF for Slack of X doing Y".
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 Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.
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。