「across」の検索結果

Curated trending across GitHub repos and the Hugging Face Hub (models, datasets, spaces) - filtered, clustered, and labeled by momentum with a one-line why-notable per pick.

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Amazon sales volume estimator for sellers and product researchers. Estimate monthly sales and revenue from BSR (Best Seller Rank), ASIN, or keyword. Three modes: (A) BSR Calculator — input BSR + marketplace + price + category to get instant sales estimate, (B) ASIN Lookup — input ASIN to auto-fetch data and estimate sales, (C) Keyword Market Analysis — input keyword to analyze total market size and competition. Works on 12 Amazon marketplaces. No API key required. Use when: (1) estimating how many units a product sells per month, (2) sizing a market or niche opportunity, (3) analyzing competitor sales performance, (4) comparing sales across price points, (5) identifying top sellers vs long-tail distribution.

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。

Profitable niche discovery for Amazon sellers. Identifies underserved markets with high demand but low competition. Analyzes market gaps, emerging segments, and untapped opportunities across categories. Use when the user asks about finding niches, profitable markets, underserved segments, market gaps, blue ocean opportunities, niche research, or what markets to enter on Amazon.

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。

Evaluate and plan Amazon marketplace expansion across countries and regions. Use when a seller asks which Amazon marketplace to enter, how to compare international demand and economics, what tax, product-compliance, logistics, localization, account, or launch workstreams to investigate, or how to build a gated global-selling roadmap. Do not use as legal, tax, customs, or certification advice.

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Amazon listing builder and optimizer for sellers. Two modes: (A) Create — build keyword-optimized listings from scratch using keyword lists + product characteristics + AI copywriting, (B) Optimize — audit existing listings, find keyword gaps, score across 8 dimensions, and rewrite with missing keywords. Integrates with amazon-keyword-research for keyword input. Works on 12 Amazon marketplaces. No API key required. Use when: (1) creating a new Amazon listing from keywords, (2) auditing an existing listing for SEO and conversion, (3) checking keyword coverage in title/bullets/description, (4) generating listing copy with target keywords and tone, (5) comparing listings against competitors, (6) preparing a listing for launch or relaunch.

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。

Reusable approval-loop pattern for fanning out lead personalization across parallel Claude Code Task sub-agents. Shows the user 1 sample personalization, collects feedback, runs 10 more, approves, runs 10 more — stops when 2 consecutive rounds have zero edits, then scales to the full list. ALWAYS uses Claude Code Task tool sub-agents — never an external Anthropic/OpenAI API key. Use when any skill needs per-lead custom variables (situation lines, value lines, CTAs).

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。

Compare reply rates, bounce rates, and positive reply rates broken down by inbox type (SMTP / Gmail / Outlook) for a Smartlead account. Use when you want to know "which inbox type delivers best" or when debugging unexplained deliverability differences across a mixed fleet. Operates via Smartlead API only (no database required).

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 high-performing headline variations across different angles. Trigger on "headlines", "hooks", "ad copy", "email subject lines".

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 a comprehensive brand standards document — covering logo usage, color, typography, voice, messaging, and application rules. Use when the user says "brand guidelines", "brand standards", "brand book", "style guide", "brand guide", "brand manual", "brand rules", "brand documentation", "brand toolkit", "onboarding designers or copywriters", "need a document for the team", "brand consistency across teams", or wants to codify all brand decisions into a reusable reference document.

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Use when the user mentions Higgsfield Canvas, a node-based or node graph workspace, an infinite board/canvas, chaining generations into a pipeline, or wants to wire prompts → images → videos across models on one surface. Covers what Canvas is, the node categories, the seven models that run inside Canvas, the named canvas patterns (Simple Seedance, Extend Video, Image Edit, StoryBoard With Elements, Long Video fan-out), the build-free / generate-paid cost model, reusable templates, assets-as-nodes, and Shared Canvas live collaboration. Also trigger on 'Higgsfield ComfyUI alternative', 'node workflow', or 'connect nodes to build a scene/campaign'.

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。

Pre-production story-and-character development for Higgsfield projects — the upstream layer that decides WHAT to prompt before any model runs. Use when the user wants to build a character, design a world, develop a story or premise, create a character sheet / character bible / story bible, lock a visual style or 'visual DNA', plan a multi-shot narrative with consistent characters, or says things like 'help me design a character', 'build the world', 'I need a backstory', 'make this character consistent across shots', 'develop my film/series concept', or 'I keep getting generic AI characters'. Routes the locked outputs into higgsfield-prompt + the right model. Adapted from Higgsfield's official character-design framework by @vavavinca.

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Writes the character-performance layer of a video prompt as behavior under pressure, not displayed emotion — objective, obstacle, tactics, beats, subtext, listening, body/status/proxemics, and mandatory eye life. Produces a reusable 150–220-word acting master profile per character plus a per-scene rewrite of it, and a locked voice prompt. Use whenever a prompt needs acting, performance, or emotion direction; whenever characters read wooden, dead-eyed, or 'AI'; whenever a character must stay themselves across many shots; or when the user asks for character behavior, mannerisms, tics, a gait, or how someone reacts. Pairs with higgsfield-facs (muscle-level AU codes) and higgsfield-seedance (the prompt the paragraph goes into).

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Turns a brief, script, scene breakdown, treatment, or story idea into ONE connected director's shotlist for Seedance 2.0 — a single editable HTML artifact with a global Style Prefix, an @-asset glossary, and named per-scene prompts (1a, 1b, 2a…) each in Style → Characters → Scene → CUT 1..N form. Use whenever the user says 'make a shotlist', 'break this script into prompts', 'generate Seedance prompts for this ad/film', 'turn this brief into a shot list', 'director's shotlist', or wants many connected scene prompts rather than one. Also use to revise an existing shotlist (edit-once-propagates: 'change the style prefix everywhere', 'rewrite scene 4', 'split prompt 6'). Each prompt targets 15s; longer scenes split across 1a/1b/1c under one scene number.

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。

Applies the StoryBrand SB7 Framework from Building a StoryBrand by Donald Miller. Use when writing website copy, crafting brand messaging, creating marketing materials, building sales funnels, or designing email campaigns. The SB7 Framework positions the customer as the hero and the brand as the guide across 7 story elements. Triggers include 'how should we write our website', 'our messaging is confusing', 'customers don't understand what we do', 'how do I write a tagline', 'what should our homepage say', 'nobody reads our emails', 'how do I create a lead generator', 'our marketing isn't working but our product is good'. NOT for growth channel selection (use Traction), not for product positioning against competitors (use Obviously Awesome), not for pricing (use Monetizing Innovation).

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Split the Plan/Act/Verify loop across three model tiers — frontier planner, cheap executor, frontier judge — via env vars read by run.sh.

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。

Before picking new work, smoke-test the last "completed" feature. If it's broken, revert and re-open it before touching anything else. Kills the "looks shipped, isn't shipped" bug across sessions.

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Cache the parts of the prompt that don't change so a long-running loop stops paying full price on every turn. Use when the system prompt, tool defs, or reference docs are stable across many turns.

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。

Parallelize independent sub-jobs across fresh-context subagents instead of one bloated context. Use when a goal branches into many independent pieces.

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。

Clean Code principles (DRY, KISS, YAGNI), naming, function design and readability. Use when code is hard to read, with long methods, unclear names, duplication or deep nesting. For how responsibilities are split across classes and which way dependencies point, use solid-principles instead.

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Onboard a new user into a Symbiotic AI setup by interviewing them one sharp question at a time and writing their own context files (SOUL.md, USER.md, NOW.md, and AGENTS.md) as plain Markdown they keep. Use this whenever someone is setting up a personal AI agent, wants their assistant to remember or understand them across sessions, mentions Symbiotic AI / SOUL.md / USER.md / NOW.md, is staring at blank template files full of [bracketed placeholders], or asks how to give an AI persistent context they own and can move between models. Trigger even if they do not say the word "onboard".

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Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.

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Use when the user asks for a visual or UI quality review of frontend code that already shipped, or passes a phase number. Produces {phase_num}-UI-REVIEW.md with a graded 1-4 assessment across six pillars.

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Use when a bug, failing test, or unexpected behaviour needs investigation, especially across sessions or context resets. Isolates it in a debugger subagent with persistent .planning/debug state, unlike skills/systematic-debugging.

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Use when the user asks what UAT or verification items are still outstanding across phases, or wants a prioritized manual test plan. Scans every phase for pending, skipped, blocked and human_needed items and flags stale docs.

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。