「find」の検索結果

Bevy ECS skill for navigation. Keywords: Bevy, navigation, pathfinding, ECS.

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 starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

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 the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified", "is this actually done", "maker checker", "second pair of eyes on this change". Not for prose, docs or typo 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。

Full-history Godot version migration hub. Use when upgrading any Godot project toward the library target (currently 4.7)—from 1.x/2.x legacy eras through 3→4 and hop-by-hop 4.x minors—or finding Domain Skill-scoped migration notes. Trigger keywords: upgrade Godot, migrate Godot version, Godot 3 to 4, Godot 2 to 3, upgrading_to_godot, version migration, breaking changes, convert-3to4, TileMapLayer, AnimationMixer, engine.cfg, project.godot.

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 blueprint for tower defense games (Bloons TD, Kingdom Rush, Fieldrunners) covering wave management, tower targeting logic, path algorithms, economy balance, and mazing mechanics. Use when building TD, lane defense, or tower placement strategy games. Keywords tower defense, wave spawner, pathfinding, targeting priority, mazing, NavigationServer baking.

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。

Bevy ECS skill for navigation. Keywords: Bevy, navigation, pathfinding, ECS.

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。

Discover and evaluate potential A-share investment opportunities for China-focused private equity and investment strategies. Adapted from the original deal-sourcing skill for Chinese market structure, data sources, and business practices. Triggers on "A股项目挖掘", "投资项目发现", "deal sourcing China", "find A-share deals", "sourcing opportunities China", or "discover investment 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。

Query A-share and Chinese financial market data via multiple data sources. Tier-1 paid source is iFind (同花顺, covers stocks/funds/macro/bonds/HK-US/ESG/index-sectors). Tier-2 free source is AkShare (行情/财报/行业/指数). Use whenever the agent needs Chinese financial data — compatible with 沪深 A 股, 科创板, 创业板, 北交所, and 港股通 stocks.

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。

Systematic stock screening and investment idea sourcing for A-share markets. Combines quantitative screens, thematic research, and pattern recognition to surface new long and short ideas. Adapted from the original idea-generation skill for Chinese market conventions and data sources. Triggers on "A股选股", "股票筛选", "寻找机会", "stock screen China", "A-share ideas", "find ideas for Chinese stocks", or "screen for A-share opportunities".

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。

Create new China-specific financial skills following the established patterns and conventions. Use this meta-skill to scaffold new china-* skills that integrate with iFind MCP (Tier-1) and AkShare MCP (Tier-2 fallback), follow CAS accounting standards, and adapt workflows for the Chinese market. Triggers on "创建中国skill", "新建A股skill", "create china skill", "new china-skill", "制作skill", or when creating any new china-* skill.

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。

Generic PowerPoint authoring skill for A-share investment analysis and pitch decks. Creates professional 路演PPT / 投资分析PPT for any A-share company using live data from iFind MCP (Tier-1) and AkShare MCP (Tier-2 fallback) tools. All company-specific values are parameterized — never hardcoded. Triggers on "A股PPT制作", "投资PPT", "制作PPT", "路演PPT", "pitch deck", "PowerPoint [company/ticker]", or any request to create slides for a Chinese stock. When invoked, use the `generate_a_share_ppt` script with --company and --ticker args.

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。

Bootstrap skill — establishes how to find and use GodotPrompter skills, with platform-specific tool 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。

Finds the price buyers will actually pay. Reads the consumer panel's four price answers per buyer into a Van Westendorp price-sensitivity range (too cheap, a bargain, getting expensive, too expensive), sets it against what competitors really charge and against the CFO's margin, and recommends a price, a price ladder (good / better / best) and an opening offer to test. Use when the user says "how much should I charge", "price this", "is $X too expensive", "pricing strategy", "what price", or after the consumer panel.

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。

Your CFO. Builds the unit economics of a business before money is spent: what one unit earns after its direct costs, the real profit margin at the planned volume, the break-even point in units a day, year 1 month by month, the cash needed before it pays for itself, how long the startup spend takes to earn back, and what happens if the price drops, sales come in low or costs rise. Every number traces to an input the user can check. Use when the user says "find the profit margins", "do the numbers", "is this profitable", "break-even", "unit economics", "how much do I need to start", or "run the CFO".

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。

Discover Civitai models with the BUILT-IN download_model action:"search_civitai" and install/generate them locally. Find a checkpoint/LoRA/embedding on Civitai, download it into ComfyUI, and use its trigger words. Optionally pair the official Civitai MCP for community features (images browsing, posting, collections).

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-site crawling, scraping, and site mapping via Firecrawl MCP. Use when user says "crawl site", "map site", "full crawl", "find all pages", "broken links", "site structure", "discover pages", "JS rendering", or needs site-wide 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。

Full website SEO audit with parallel subagent delegation. Crawls up to 500 pages, detects business type, delegates to up to 15 specialists (8 always + 7 conditional), generates health score. Use when user says audit, full SEO check, SEO best-practice review, analyze my site, website health check, or find SEO issues.

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。

Brainstorm and rank iOS/macOS app ideas tailored to developer skills. Use when user says "what should I build", "give me app ideas", "I don't know what to build", "brainstorm app ideas", or "help me find an app idea".

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。

Get press coverage and media attention for your indie app. Covers press kit preparation, finding journalists/bloggers/YouTubers, pitch timing, embargo strategy, and story angles that get coverage. Use when user wants press coverage, is preparing for a launch, or wants to build a media kit.

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。

Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.

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 analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across

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。

treekoR is a novel framework that aims to utilise the hierarchical nature of single cell cytometry data to find robust and interpretable associations between cell subsets and patient clinical end points. These associations are aimed to recapitulate the nested proportions prevalent in workflows inovlving manual gating, which are often overlooked in workflows using automatic clustering to identify cell populations. We developed treekoR to: Derive a hierarchical tree structure of cell clusters; qua

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。

SpatialDE is a method to find spatially variable genes (SVG) from spatial transcriptomics data. This package provides wrappers to use the Python SpatialDE library in R, using reticulate and basilisk.

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 package implements a metabolic network analysis pipeline to identify an active metabolic module based on high throughput data. The pipeline takes as input transcriptional and/or metabolic data and finds a metabolic subnetwork (module) most regulated between the two conditions of interest. The package further provides functions for module post-processing, annotation and 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。