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Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards. USE THIS SKILL WHEN: - You need to review or audit actuarial models (reserving, pricing, capital) - Someone asks about loss triangle analysis or reserve adequacy - You are evaluating IBNR calculations, chain ladder methods, or Bornhuetter-Ferguson - A project involves insurance pricing, GLM rating models, or ratemaking - You need to assess Solvency II SCR calculations or RBC compliance - Someone mentions actuarial opinions, ASOP compliance, or SOA standards - You are reviewing stochastic models, ESG configurations, or DFA frameworks - A codebase uses actuarial libraries (chainladder, lifetables, ChainLadder R package) TRIGGER PHRASES: "actuarial", "loss reserving", "IBNR", "chain ladder", "premium pricing", "mortality table", "Solvency II", "capital adequacy", "ratemaking", "GLM pricing", "risk-based capital", "reserve analysis", "actuarial opinion"

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。

Expert guide for WebAssembly (WASM) and Edge Computing. Covers WASI preview 2, Spin/Fermyon, Cloudflare Workers WASM, and high-performance browser computing / Panduan ahli untuk WebAssembly (WASM) dan Edge Computing. Mencakup WASI preview 2, Spin/Fermyon, Cloudflare Workers WASM, dan komputasi performa tinggi di browser.

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 agentic web data extraction with multi-strategy scraping (Crawl4AI v4, Firecrawl), LLM extraction loops, anti-bot bypass, and structured export / Ekstraksi data web cerdas dan agentic dengan scraping multi-strategi (Crawl4AI v4, Firecrawl), ekstraksi LLM, bypass anti-bot, dan ekspor terstruktur.

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。

Expert guide for structured logging (Pino, Winston), error tracking (Sentry), log aggregation (Axiom, Datadog), request correlation, and GDPR-compliant log management / Panduan ahli untuk logging terstruktur (Pino, Winston), pelacakan error (Sentry), agregasi log, korelasi request, dan manajemen log sesuai GDPR.

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。

Sort, hide, show, reorder, resize, pin, format, and color-code columns in a Datagrok TableView grid via the datagrok_exec tool. Use whenever the user asks to sort by a column (any direction), multi-sort, hide / show / reorder / pin / resize columns, freeze the first N columns, change number-format display, color-code cells (defaults and grid-only tint here; full per-type reference in datagrok-df-and-columns), set row height, or reset the grid back to defaults. Distinct from datagrok-df-and-columns (which owns column-level data metadata like semType, units, friendlyName, and is also where canonical color-coding lives) and from datagrok-viewers (which owns scatter plot / histogram / etc.). Does NOT cover filtering (`datagrok-filtering`), selection (`datagrok-selection`), custom cell renderer authoring (`create-cell-renderer`), saving / restoring layouts, or grid event handlers.

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 and rewrite a TikTok profile for 2026: photo, name (searchable), username, bio (80 chars, niche clarity is everything), link (unlocks at 1k followers, plus a pre-1k workaround), up to 3 pinned videos as proof, and one-line positioning. A profile visit follows a video, so the bio must instantly answer "what do I get if I follow". Triggers on "review my TikTok profile", "fix my TikTok bio", "what to pin on TikTok", "profile audit", "niche bio". Not for writing a video script (use tt-hook-scripter).

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。

店長が承認した発注案を、発注単位・締め時刻・便を確かめてから Dataverse の発注テーブルに登録し、登録結果を報告するスキル。承認の前に必ず最終の一覧（Render UI のグラフ付き）を見せ、登録後は HTML レポート「発注の記録」を作る。 Use when ユーザーが「この内容で発注して」「承認します」「発注を登録して」「さっきの発注はどうなった？」と依頼したとき、または tanpin-kanri の発注案が承認されたとき。 Dataverse MCP コネクタ（describe / read_query / create_record）を使う。create_record はこのスキルでだけ、店長の明示的な承認の後に、発注テーブルにだけ使う。

Engineering design cycle covering requirements elicitation, specifications writing, constraint identification, iterative prototyping, and design communication. Spans the full loop from problem definition through ideation, analysis, prototyping, testing, and redesign. Includes morphological charts, TRIZ, Pugh matrices, design reviews, and the distinction between functional and non-functional requirements. Use when framing engineering problems, generating design alternatives, writing specifications, or running design reviews.

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 skill by running a paired probe — the same task once with the skill loaded and once without — segment both traces into goal-directed phases, align phases, and emit a SIP report (surface anchoring, template copy, excess planning, task recovery, off-task artifact). Use whenever a skill is created, modified, or proposed for retirement. Pass-rate is BLIND to most skill effects: CTA (arxiv 2605.11946v1) shows a single skill can produce 522 measurable behavioural changes across 49 tasks while pass-rate moves only +0.3%. Triggers: "audit this skill", "is this skill helping", "retire skill", "before shipping skill", "behavioural impact of skill X", or any skill review event.

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。

Observational drawing and visual perception techniques for art education. Covers contour drawing, gesture drawing, negative space, proportion and measurement, value mapping, spatial depth cues, and the cognitive shift from symbolic to perceptual seeing. Use when teaching drawing fundamentals, analyzing observational accuracy, or developing visual literacy in any medium.

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。

OpenStack Nova compute service skill for deploying, configuring, operating, and troubleshooting cloud compute infrastructure. Covers instance lifecycle management (create/stop/start/reboot/resize/migrate/evacuate), compute scheduling with filters and weights, flavor management, live migration procedures, hypervisor management (KVM/QEMU via libvirt), placement service for resource tracking, CPU pinning, NUMA topology, huge pages, cell mapping, VNC/SPICE console access, and capacity planning. Use when deploying compute via Kolla-Ansible, managing instances, debugging scheduler failures, or planning compute 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。

Devicetree management for Zephyr RTOS. Covers syntax, bindings, overlays, Hardware Model v2 (HWMv2), and advanced node/property deletion patterns. Trigger when defining hardware topology, creating overlays, or mapping pins and peripherals.

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。

Foundational skills for Zephyr RTOS development. Covers essential Embedded C patterns (BIT, CONTAINER_OF), real-time concurrency primitives (mutexes, semaphores, spinlocks), hardware literacy (datasheet-to-DTS mapping), and defensive programming. Trigger when writing core application logic, drivers, or troubleshooting foundational behavior.

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。

Amazon product search, cart management, price tracking, and shopping list via Playwright + DuckDB MCP server

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。

Runs deterministic Python quality checks against a path or scope — formatting, linting, type checking, and typing-boundary policy. Use when checking or fixing code quality via prek, ruff, ty, pytest, or the check-typing-boundaries policy script. Reports results grouped by category; fixes only when explicitly requested.

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。

Dasel v3 query patterns for Hibernate .hbm.xml mapping files — entity-table binding, Java property-to-column extraction, one-to-many set/list/bag relationship tracing, many-to-one foreign key discovery, batch scanning across 60+ HBM files. Use when querying Hibernate ORM class mappings, extracting schema metadata from Java persistence layer, or auditing entity-column relationships in enterprise legacy codebases.

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。

Turns a raw Qualtrics conjoint export into analysis-ready long-format data: implementation identification, reshaping, choice-profile alignment, reference categories, and pilot exclusion. Use when a conjoint CSV needs cleaning, reshaping, or debugging before AMCE estimation.

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。

Reviews an existing conjoint study for threats to inference and returns severity-ranked findings on design integrity, estimation, measurement error, external validity, and interpretation, including the guardrail against reading an AMCE as majority preference. Use when the user asks whether a conjoint design or analysis holds up, has referee comments on a conjoint, or wants a second opinion on estimation or interpretation. New designs go to conjoint-design, reshaping to conjoint-cleaning.

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。

Dynamic agent composition and management system. USE WHEN user says create custom agents, spin up custom agents, specialized agents, OR asks for agent personalities, available traits, agent voices. Handles custom agent creation, personality assignment, voice mapping, and parallel agent orchestration.

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。

Maps your company's GTM motion (PLG, SLG, or Hybrid) to concrete funnel stages with inputs, outputs, and qualification criteria per stage. Detects motion type from website + Exa research, then produces pre-close + post-close stage definitions, the FETE mapping (Fit / Engagement / Tier / Eligibility), and closed-lost re-entry paths. Triggers - "funnel strategy", "funnel stages", "pipeline stages", "sales process", "lead qualification", "GTM motion mapping", or any work defining how leads flow through the business. Upstream - recommended company-context, icp-research. Downstream - feeds lifecycle-marketing, outreach-emails, content-strategy. NOT for lead scoring logic (use /lead-scoring) or lifecycle email campaigns (use /lifecycle-marketing).

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。

Require corresponding tests for every Go code change, E2E coverage whenever developing tests, and immediate diagnostic remediation while agents edit code; select, run, and maintain AuthCrunch tests through pinned tested, browser tests, automation fixtures, coverage artifacts, and CI gates.

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 building or refining an Ideal Customer Profile (ICP), defining target personas, mapping buyer psychographics, or discovering where prospects gather online. Triggers: 'build my ICP', 'define target customer', 'who should I sell to', 'refine ICP', 'persona mapping'.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for IPA runtime analysis, Frida hooks, Objective-C or Swift method tracing, Keychain inspection, SSL pinning bypass, URL scheme handling, and iOS request-signing recovery. Use when the user asks to hook an IPA, trace Objective-C or Swift runtime behavior, inspect Keychain or plist state, bypass pinning, analyze deeplinks or universal links, or replay accepted iOS requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Android APK hooking, Frida tracing, request-signing recovery, SSL pinning bypass, JNI boundary inspection, and app trust-boundary analysis. Use when the user asks to hook an APK, inspect signer logic, trace Java or native boundaries, bypass pinning or root checks, inspect shared prefs or app databases, or replay accepted mobile requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。