348 件 ・ 関連度順
概要と使いどころ
Analyze Trigger.dev tasks, schedules, and runs for cost optimization opportunities. Use when asked to reduce spend, optimize costs, audit usage, right-size machines, or review task efficiency. Combines static source analysis with live run analysis via the Trigger.dev MCP tools (list_runs, get_run_details, get_current_worker).
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。
Valuation criteria for developed market value general insurance stocks. P/B 0.7-1.5x, Combined Ratio <100%, investment yield benchmarks, and dividend sustainability 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。
Valuation criteria for developed market growth general insurance stocks. Combined Ratio improvement trajectory, premium growth 7-10% YoY, expense ratio decline, and retention rate targets.
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。
Valuation criteria for emerging market insurance stocks. P/B 0.5-1.0x with 30-50% EM discount, combined ratio targets, and China vs India market comparisons.
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。
The logical structure of mathematical proof -- how first-order logic, natural deduction, and semantic reasoning combine to produce rigorous mathematical arguments. Covers the logical skeleton of direct proof, contraposition, contradiction, cases, and induction; the role of definitions, lemmas, and theorems; how informal mathematical prose maps to formal deductive structure; and the difference between proof-as-object and proof-as-activity. Use when the question is "why is this a valid proof?" rather than "what proof technique applies?"
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。
BDD-Driven Mathematical Content Verification Skill Combines Behavior-Driven Development with mathematical formula extraction, verification, and transformation using: - Cucumber/Gherkin for specification - RSpec for implementation verification - mathpix-gem for LaTeX/mathematical content extraction - Pattern matching on syntax trees for formula validation Enables iterative discovery and verification of mathematical properties through executable specifications.
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。
Combines AMP thread export with GF(3)-classified continuation for skill orchestration. Export threads as markdown, classify continuation choices as {-1:reductive, 0:neutral, +1:generative}, and fork parallel execution paths.
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。
Runs several language models as independent coders on one labeling or discovery task and treats disagreement as data. Covers diverse panel assembly, independent voting, consensus rules, Cohen’s and Fleiss kappa, Krippendorff’s alpha, correlated-error limits on validity claims, human validation, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, how to combine model labels, or what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.
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 several language models as independent coders on the same labeling or discovery task and reads their disagreement as data — panel assembly for model diversity, keeping votes independent, consensus rules, agreement statistics (Cohen's and Fleiss kappa, Krippendorff's alpha), the correlated-errors caveat that stops agreement being mistaken for validity, human validation beyond the panel, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, asks how to combine several models' labels, or asks what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.
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 this skill for ANY financial market, investment, or macro-economic analysis. ALWAYS trigger this skill — do not skip it — when the user asks about: BTC, bitcoin, crypto, gold, silver, oil, stocks, forex, bonds, interest rates, Fed policy, inflation, deflation, stagflation, market structure, trading setups, portfolio allocation, asset allocation, investment strategy, price analysis, market outlook, geopolitics affecting markets, or any question involving "should I buy/sell/hold [any asset]", "what will [asset] do", or "analyze [market/asset]". Apply Genesis Protocol (First Principle + System Thinking) combined with SMC Layer analysis to produce structured insights with explicit scenarios, entry/exit zones, and uncertainty. For non-market strategic thinking, use genesis-mind-strategic-intelligence instead.
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 this skill for ANY financial market, investment, or macro-economic analysis. ALWAYS trigger this skill — do not skip it — when the user asks about: BTC, bitcoin, crypto, gold, silver, oil, stocks, forex, bonds, interest rates, Fed policy, inflation, deflation, stagflation, market structure, trading setups, portfolio allocation, asset allocation, investment strategy, price analysis, market outlook, geopolitics affecting markets, or any question involving "should I buy/sell/hold [any asset]", "what will [asset] do", or "analyze [market/asset]". Apply Genesis Protocol (First Principle + System Thinking) combined with SMC Layer analysis to produce structured insights with explicit scenarios, entry/exit zones, and uncertainty. For non-market strategic thinking, use genesis-mind-strategic-intelligence instead.
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-stack video production from script to rendered video. Combines script generation (optimized for TikTok/YouTube/Reels) with AI-powered video rendering using Remotion, AI voiceovers (Qwen3-TTS/ElevenLabs), music generation (ACE-Step), and browser-based demo recording. Multi-session project tracking with automatic intent reconciliation. Use when "create video", "produce video", "demo video", "product video", or any request to generate AND render video content.
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。
Browser Use is an open source browser automation framework for AI agents that turns websites into controllable interfaces for multi-step tasks. It combines a Python SDK, browser orchestration, and model integrations so agents can navigate, extract data, and complete workflows in real browsers.
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。
Apify SDK is the official JavaScript SDK for building Actors, crawlers, and data extraction workflows on Apify. It gives agents a structured way to run scraping jobs, store outputs, manage inputs, and combine crawler logic with browser automation when needed.
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。
ApostropheCMS is a full-stack Node.js CMS that combines in-context editing for content teams with headless flexibility for developers. It is a strong fit when teams want live-page editing, MongoDB-backed content models, and a documented REST API for custom frontends.
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。
AFFiNE is an open source workspace that combines docs, whiteboards, and lightweight databases in one product. This skill is useful when an agent needs to structure notes, maintain linked knowledge, or automate content workflows around AFFiNE workspaces and self-hosted deployments.
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。
AIChat is a comprehensive LLM command-line tool written in Rust that combines chat-REPL, shell command generation, RAG, AI tools, and multi-provider support into a single binary. It connects to 20+ LLM providers including OpenAI, Claude, Gemini, and Ollama.
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 on Day 1 of an AIS-OS install, when someone says "set me up", "onboard me", "let's get started", "fill in my AIOS", or has just cloned the kit. Combined wizard — runs the 7-question intake AND scaffolds the Day-1 file set at the end. Idempotent — re-run any time after editing aios-intake.md.
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。
One command from "plugin installed" to "running brief on your idea." Combines /mycelium:setup (project-state initialization) and /mycelium:interview (10-minute discovery brief) into a single flow. Run this immediately after installing the Mycelium plugin — it's the recommended entry point for first-time users.
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 Biome in .NET repositories that ship Node-based frontend assets and want a fast combined formatter-linter-import organizer for JavaScript, TypeScript, CSS, JSON, GraphQL, or HTML. Use when a repo prefers a modern all-in-one CLI over a larger ESLint plus Prettier style stack.
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。
Evaluates stapled secondary structures combining primary commitment with secondary purchase in coordinated transactions. Use when analyzing stapled deals, structuring combined primary/secondary, or evaluating staple economics.
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。
Two-step self-review at every task lifecycle phase. Step 1 (this skill) runs in-context to gather session signals — files read vs grepped, user pushback, build evidence, degradation signs. Step 2 launches a forked subagent for unbiased code/plan review with fresh eyes. Combined report classifies findings as hard blocks or soft warnings.
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。