「seed」の検索結果

Unity procedural generation design-to-code translation. Noise-based terrain/placement, tile & grid systems, dungeon/room generation, seed & reproducibility, content budget & constraint systems, runtime vs baked generation. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. Based on Unity 6.3 LTS.

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 fantasy character names in zh-TW with original spelling and etymology, across human, elf, dwarf, orc/beastfolk, and halfling naming traditions. Use when the user needs a name for a character, NPC, party member, villain, shopkeeper, or monster, asks to think of, suggest, or rename such a character, names entities for a MUD/TRPG/game world or worldbuilding document, or writes lore, quests, presets, or seed data that require in-world personal names.

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。

Product-led growth and customer-base growth for B2B SaaS. Use this skill for self-serve funnel work (activation, time-to-value, free trial vs freemium, PQL definition, in-product upgrade moments, sales-assist triggers), for the self-guided interactive product demo that runs in front of the login wall (demo portfolio and flow design, gated vs ungated policy, demo seed data and privacy, keeping a published demo in sync with the shipping product, step-level demo analytics), and for growing revenue from existing customers (adoption, expansion, churn-save, the self-serve cancel flow and failed-payment recovery, renewal marketing, net revenue retention, and champion tracking: watching the people who bought and used you at each customer, confirming a job change from evidence, and running both plays a move fires, the seat they left and the account they joined). Also triggers on: PLG, product-led growth, activation, aha moment, time to value, free trial, freemium, PQL, product qualified lead, onboarding, self-serve, customer marketing, expansion revenue, upsell, cross-sell, churn, retention, NRR, renewal, cancel flow, cancellation flow, save offer, exit survey, pause subscription, dunning, failed payment recovery, involuntary churn, people keep canceling, champion tracking, job change signals, job change alerts, our champion left, our champion changed jobs, customer alumni, former customers who moved to a new company, interactive demo, self-guided demo, product tour, click-through demo, demo automation, demo library, should our demo be gated, ungated demo, demo without a sales call, our demo is out of date, demo shows the old UI, put a demo on our homepage, demo completion rate, demo drop-off, try before you talk to sales.

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 a task needs the judgment of an Agricultural Equipment Operator — calibrating planter seed population and singulation, diagnosing combine header or separator loss, sequencing planting or harvest across fields under a weather-constrained window, sizing machinery capacity in acres/hour against a season's acreage, or evaluating PTO/grain-bin entrapment safety on a job site.

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 and edit images with diffusion models: prompting, seeds, CFG, img2img, inpainting, conditioning, and API integration. Use when adding AI image generation to apps or 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。

Guides AI agents in using Tree Ring Memory for durable recall, project decisions, user preferences, warnings, future seeds, privacy-safe memory capture, and lifecycle-aware forgetting.

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。

Prepare for fundraising due diligence — runs CTO, CFO, CPO, sales, and codebase health reviews to produce a consolidated investor brief with scorecard, red flags, and strengths. Use before Series A, seed round, acqui-hire evaluation, or board presentation.

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 codebase for product-market fit readiness -- evaluate startup PMF signals, core value loop tightness, feature scatter vs focus ratio, user activation funnel friction, retention hook infrastructure, pricing flexibility, analytics event coverage, CI/CD iteration speed, and growth-stage maturity for pre-seed through Series A products.

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 game level design systems and procedural generation -- BSP room subdivision, Wave Function Collapse tile placement, cellular automata cave generation, Perlin noise terrain, chunk stitching, seed determinism, difficulty scaling curves, pacing rhythm (tension/rest 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。

Judges whether a user's input suits the Vibe Creating style of video-prompt writing, and when it does, distills single-scene prompts, multi-shot descriptions, emotional imagery, or mixed input into prompts that are easier for a video model to generate from — while preserving any user-specified dialogue, voiceover, music, sound effects, and other hard constraints. Use when a user wants to turn an idea, story, feeling, or rough/over-specified prompt into a strong text-to-video prompt (Seedance, Sora, Kling, Veo, Runway, etc.), or asks to "rewrite", "improve", "clean up", or "vibe-ify" a video prompt. Do NOT use for long narrative films that need precise word-for-word dialogue sync, industrial shot lists meant to be executed verbatim, or functional/UI demos and step-by-step tutorials.

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 provides a plot summary, scene idea, character relationship, emotional beat, or short video concept and wants a cinematic AI video prompt. First diagnose the story, then rewrite it into a model-ready prompt for Kling, Seedance, Veo, Sora, Runway, Jimeng, or general AI video models.

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。

End-to-end pipeline for producing Vox-style explainer videos from a single topic prompt. One topic in, finished film out — script, keyframes (Seedream 5.0 Pro), animation (Gemini Omni Flash), voiceover (xAI TTS), music (MiniMax Music 2.6), all assembled locally with ffmpeg via the Atlas Cloud API. Use this skill whenever the user asks for an explainer video, a Vox-style video, a documentary short, an educational video essay, a "one prompt to video" pipeline, or wants to turn a topic/article/report into a narrated video with subtitles and music. Also trigger when the user mentions Atlas Cloud video pipelines, keyframe-to-animation workflows, or automated video essays — even if they don't say "Vox."

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 designing or reviewing Salesforce sandbox topology, refresh cadence, masking, and environment purpose. Triggers: 'Developer sandbox', 'Developer Pro', 'Partial Copy', 'Full sandbox', 'sandbox refresh', 'data masking', 'test environment', 'Gov Cloud sandbox'. NOT for how many environments a program needs and how they map to branches - use devops/environment-strategy. NOT for re-seeding reference data after a refresh - use data/sandbox-refresh-data-strategies. Also covers: SandboxPostCopy Apex class, SandboxInfo and SandboxProcess Tooling API, SandboxSettings metadata, sandbox topology table, refresh calendar.

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。

Automating post-sandbox-refresh cleanup via the `SandboxPostCopy` interface — the Apex class that runs ONCE after a sandbox refresh or clone completes, before users can log in. Used to mask emails, deactivate users, scrub integration endpoints, disable scheduled jobs, and reapply per-environment configuration the metadata copy doesn't carry. Covers the interface contract (`runApexClass` setting, `SandboxContext` parameter, single-execution semantics), the email-masking pattern that stops sandbox tests emailing production addresses, and the refresh runbook checklist. NOT for choosing sandbox type or refresh cadence — use admin/sandbox-strategy. NOT for re-seeding reference data after a refresh — use data/sandbox-refresh-data-strategies. Trigger keywords: SandboxPostCopy, runApexClass, SandboxContext, Test.testSandboxPostCopyScript, RunAsAutoProcUser, Automated Process user, CronTrigger, System.abortJob, sandbox email masking, post-refresh runbook.

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 the engagement model for an Experience Cloud community: reputation levels, ideation, and content contribution strategy. Triggers: 'community engagement strategy', 'gamification Experience Cloud', 'reputation levels setup', 'ideation community portal', 'member recognition program'. NOT for blocking, flagging or approving what members post — use admin/experience-cloud-moderation. NOT for measuring logins, page views or engagement after launch — use data/community-analytics-data. Also covers: the Network reputation elements that carry the ladder (enableReputation, reputationLevels/level/label/lowerThreshold, reputationPointsRules/pointsRule/eventType/points), the 16 documented reputation eventType values and their default points, ManagedTopics / ManagedTopic (Navigational vs Featured, position 0-24), NetworkMember.ReputationPoints seeding, and why FeedItem cannot carry the engagement dashboard.

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。

Database Architect skill. Use this when you need to modify the database schema, add tables, or seed data. This project uses RAW SQL SCRIPTS orchestrated by .NET Aspire, NOT Entity Framework Migrations.

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。

Startup Founder Playbook — idea validation, MVP, fundraising (seed→Series A), team building, pitch deck, metrics, investor relations

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。

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

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。

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

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。

Find question-based Google Autocomplete suggestions for any topic. Prepends question modifiers (what, how, why) to a seed topic and returns real autocomplete suggestions — useful for AEO prompt research, content ideation, and understanding what people ask about a topic. Use when the user wants to discover questions people search for, find content angles, or do keyword/prompt research for a topic.

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。

Train an ML model in the QuantConnect ML-Training-Pipeline with thermal-safe GPU usage and rigorous validation. Arguments: <architecture|script> [--dry-run] [--seeds 0,1,7,42,99] [--folds 5] [--bg]

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 database migration, model update, and seed 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。

Drafts a Delaware Amended and Restated Certificate of Incorporation implementing VC term sheet economics and governance into DGCL-compliant charter provisions. Use when drafting or revising a Delaware A&R certificate, preferred stock charter terms, Series Seed/A/B financing charter, blank check preferred authority, or implementing cap structure from a term sheet or SPA.

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。

Fetch external sources (web / arXiv / GitHub) and turn them into scanner-gated wiki CANDIDATES — never canonical pages. Every fetched byte is DATA; url-guarded, size-capped, redirect-re-validated, injection-scanned, and secret-scrubbed before a candidate is even created. Requires network. NOT for capturing local knowledge (see mk:wiki); NOT for one-shot page-to-markdown (see mk:web-to-markdown).

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。