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概要と使いどころ
Valuation criteria for developed market life insurance using Embedded Value (EV) methodology. EV Multiple 0.6-1.0x, PVFP + ANAV calculation, and why P/E is unreliable for life insurers.
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。
Iterative UI/UX polishing workflow for web applications. The exact prompt and methodology for achieving Stripe-level visual polish through multiple passes.
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 and discovers academic papers across multiple sources (Semantic Scholar, arXiv, Tavily, Exa, Gemini deep research, AMiner, Google Scholar) with adaptive engine selection based on query type. Returns ranked, deduplicated results with metadata (authors, venue, year, citations, abstract, PDF link). Use when the user asks to find papers / literature / publications / preprints / references on a topic, search for related work, look up a specific paper by title or DOI or arXiv ID, find papers by an author, find recent SOTA / state-of-the-art work, survey a research area, or run a deep / comprehensive literature search with synthesis.
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 of active analog circuits built around operational amplifiers and discrete gain stages — inverting, non-inverting, difference, and instrumentation topologies, negative feedback and loop stability (gain-bandwidth product, phase margin, compensation), active filters (Sallen-Key, multiple-feedback biquad), sinusoidal and relaxation oscillators, comparators and Schmitt triggers, voltage references (bandgap, shunt, series), and linear versus switching voltage regulators. Covers how to pick a topology, close a feedback loop that stays stable, set gain and bandwidth, and choose a power-conversion approach. Use when designing an amplifier, filter, oscillator, reference, comparator, or regulator, or when reasoning about feedback stability, loop gain, phase margin, or op-amp non-idealities.
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。
Primary and secondary source analysis for historical reasoning. Covers source classification, sourcing (author/context/purpose), corroboration across multiple sources, contextualization within time and place, and bias detection. Use when evaluating historical evidence, assessing source reliability, or constructing evidence-based historical arguments.
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。
Grammar of graphics, chart type selection, color theory, interactive visualization, dashboards, and the principles of honest, effective data display. Covers Tufte's data-ink ratio, Bertin's visual variables, perceptual principles, accessibility, small multiples, annotation, and the full workflow from exploratory plots to publication-quality graphics. Use when creating charts, designing dashboards, critiquing visualizations, or choosing how to display 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。
Pick among candidate outputs (code, configs, plans) by running them on diverse inputs and clustering by behavioural fingerprint, rather than by textual aggregation or log-probability. Activates when an executor returns multiple plausible candidates that need disambiguation, when output-majority voting would be the default choice, or when reviewing generated code that has not yet been validated. The 2026 evidence (Semantic Voting, arxiv 2605.08680v1) is that any execution-based selector dominates output-majority voting by 19-52pp; sketch-generated inputs beat random fuzz by 11.3pp. Triggers: "pick the best candidate", "majority vote on code", "select from N samples", "validate the generated output", "behavioural verification".
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。
Produce animated source control visualizations using Gource. This skill handles installation of Gource and ffmpeg, detection of repository metrics, preset-based configuration, single and multi-repo log generation, ffmpeg video encoding pipeline, headless rendering for server environments, caption generation from git tags, GitHub avatar resolution, and GSD output delivery. Use this skill whenever the user wants to visualize repository history, create a code evolution video, see project timeline animations, generate Gource videos, combine multiple repos into one visualization, or produce any kind of source control visualization. Also trigger when the user mentions "Gource", "repo visualization", "code history video", "project evolution animation", or asks to "show me what we built".
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。
Cascade the same edit pattern across N files safely. Use when applying the same refactor to multiple files (e.g. swap import paths across 11 scripts, rename a symbol, migrate a call signature). Detects the common-shape-across-files situation and turns an N-file cascade into a planned audit → apply → verify workflow instead of N sequential manual edits.
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。
多语言本地化配音：把中文带货视频本地化为英语、日语、韩语、东南亚语（印尼/泰/越/马来/菲律宾）、西语等版本——本地化改写口播（不是直译）、选对 edge-tts 音色、生成对应字幕与花字，并用同一份 storyboard 一键渲染多语言成片。Use when the user wants dubbing, 多语言, 本地化, 翻译配音, 出海, localize a product video for TikTok Shop US/UK/SEA, English voice-over, or multiple language versions of one 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。
Hardware interfacing and peripheral management for Zephyr RTOS. Covers the sensor subsystem (channels, triggers, fetch/get), pin control (Pinctrl) and multiplexing, GPIO management using Devicetree specs, and SoC-level hardware configurations. Trigger when adding new hardware components, configuring pinmux, or developing sensor-based 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。
Developing for multicore systems in Zephyr RTOS. Covers Symmetric Multiprocessing (SMP), Asymmetric Multiprocessing (AMP) with OpenAMP/RPMsg, inter-processor communication (IPC) patterns, and Linkable Extensions (LLEXT). Trigger when designing for SoCs with multiple homogeneous or heterogeneous cores.
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。
Interrogate the user before implementing a non-trivial or ambiguous ask, converging on shared intent. Use when the user says "grill me", when an ask admits multiple interpretations, or before any sizable piece of work whose intent isn't fully clear.
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 "plan chunks", "break this down", "plan the implementation", or when a story has status planning and needs implementation details before building. Required before any story can be implemented. Transforms story sparks into detailed chunk-by-chunk implementation plans with full technical specifics, file lists, and risk analysis. Supports parallel planning of multiple stories via batch mode.
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。
A comprehensive guide for using ConfigHub to manage Kubernetes configuration across multiple environments using Configuration as Data principles. This rulebook covers installation, configuration management, variant handling, and operational workflows.
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 what to do next, asks for a plan under uncertainty, challenges stalled or low-trust work, requests multiple possible approaches before action, or needs an evidence-first loop that uses RT-ICA-style prerequisite checks, adversarial review, subagent coordination, real validation, and durable concern tracking.
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。
Integrate multiple source findings into an attributed synthesis or comparison. Use for combine these summaries, synthesize results, merge findings or multi-source analysis. Preserve claim-level provenance, coverage, qualifiers, conflicts and uncertainty rather than repeatedly compressing narrative summaries.
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。
Route requests to summarize files, URLs, images, inline text, or multiple sources. Select the requested format and preserve evidence, exact counts, uncertainty and source coverage through summarization, synthesis and agent-result relay.
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。
Assess and refactor oversized or multi-domain skills. First determines whether splitting or references/ extraction is appropriate — then executes the correct action. Use when a skill exceeds token thresholds (SK006/SK007) or covers multiple independent domains. Performs candidate assessment before any structural changes; cohesive single-intent skills are redirected to references/ extraction instead of splitting. When splitting is warranted — domain analysis gate, split plan, new SKILL.md generation, validation, and backwards-compatible facade conversion.
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。
Store instructional prose once and reference it from multiple skills or agents instead of duplicating it. Use when the same steps, rules, or reference material appear in two or more SKILL.md or agent files in one plugin, when deciding whether a shared doc belongs in the plugin-root docs directory or a single skill's references directory, or when tempted to use a symlink or a ../ path to share a file between components.
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 "install perlbrew", "set up Perl environment", "install Perl version", "manage Perl versions", "switch Perl version", "install plenv", or mentions Perl version management, development environment setup, or multiple Perl installations.
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。
Synthesize multiple independent structured review verdicts into one lossless deduplicated punch list. Use when findings from several review perspectives must be merged without inventing, dropping, or changing source verdicts.
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。
Verify multiple factual claims in backlog items, skill documentation, or plugin content. Extracts discrete claims, delegates each to the canonical factual-verification process, and aggregates VERIFIED/REFUTED/INCONCLUSIVE results. Use for "fact check", "verify claims", or a set of unverified factual assertions.
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。
Designs publication figures for social-science manuscripts. Covers chart choice, axes and scales, color and accessibility, legend order, captions that carry the title, and script-based reproducibility. Use when making, revising, or critiquing a figure for a paper, such as a coefficient plot, small multiples, a distribution, a trend, a map, or a network. Finished figure sets go to figure-table-audit for end-stage QA.
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。