「discovering」の検索結果

Discover trending new products across 16 TikTok Shop regional markets via Nexscope new product ranking data. Trigger when users mention TikTok new product rankings, TikTok hot-selling products, TikTok Shop bestsellers, short-video e-commerce product selection, TikTok new product discovery, cross-border TikTok product selection, TikTok new product rankings, TikTok bestsellers, short-video product selection, TikTok viral products, new product ranking, TikTok product trends. Even if the user does not explicitly mention "Nexscope" or "new product ranking", trigger this skill whenever their need involves discovering hot-selling new products or emerging product trends on TikTok Shop.

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 Nexscope market list capability to filter Amazon niche markets by category dimensions, supporting market size, competition, top concentration, seller structure, new product share, price/rating/margin ranges, and many other criteria for discovering viable markets and evaluating product selection directions. Trigger when the user mentions Amazon market research, niche category research, market opportunity screening, market concentration analysis, new product opportunities, market selection, Nexscope market research, category market research. Even if the user does not explicitly mention "Nexscope", if the need is to screen and evaluate Amazon markets by category dimensions, this skill should also be triggered.

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。

Nexscope Product Database multi-condition filtering. Filter Amazon products by category, price, sales volume, revenue, reviews, rating, weight, BSR rank, LQS, seller type, and more across 10 marketplaces. Trigger when users mention Amazon product selection, product database filtering, BSR rank filtering, category-based product discovery, high-rating low-competition products, FBA product search, Amazon product discovery, or similar terms. Even if the user does not explicitly mention "Nexscope" or "product database," trigger this skill whenever the request involves filtering Amazon products by multiple criteria or discovering potential 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。

Use Nexscope data to find and analyze competitors on Amazon, covering 12 marketplaces, with product metrics including sales, BSR, pricing, ratings, and growth trends. Trigger when the user mentions competitor lookup, competitor analysis, ASIN reverse lookup, competitive product research, finding similar products, market competitor discovery, product benchmarking, competitor sales estimation, analyzing competitor listings, competitor analysis, ASIN reverse lookup, competitor sales, competitor research, Nexscope, market competitor discovery, competitor trends. Even if the user does not explicitly mention "Nexscope" or "competitor lookup", if their need involves discovering and analyzing Amazon competitors by ASIN, keyword, seller name, brand, or category, this skill should also be triggered.

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 1688 product bestseller billboard data for sourcing discovery and wholesale product research. Trigger when the user mentions 1688 product rankings, 1688 bestseller lists, wholesale hot products, domestic sourcing rankings, dropshipping product selection, 1688 trending products, bulk purchase popular items, supplier product rankings, 1688 billboard, 1688 bestsellers, sourcing rankings, wholesale hot products, trending product rankings, supplier rankings, 1688 trends. Even if the user does not explicitly mention "1688 billboard", if their need involves discovering hot-selling wholesale products or sourcing opportunities on the 1688 platform, this skill should also be triggered.

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 Amazon same-niche competitors by ASIN, with multi-dimensional filtering by click conversion rate, composite conversion rate, click volume, sales volume, reviews, ratings, price, and gross margin to identify potential competitors. Triggered when users mention same-niche competitors, ASIN competitor mining, niche competitor analysis, similar product benchmarking, ASIN benchmarking, niche market competitor list, high-conversion competitor screening, Nexscope product mining, niche competitor by ASIN, ASIN competitor analysis, same niche products, similar products discovery, conversion rate comparison, potential competitor screening, Nexscope ASIN mining. Even if users do not explicitly mention "niche" or "same niche", this skill should be triggered whenever the task involves discovering competitor lists or screening potential competitors based on a specific ASIN within the same market segment.

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。

Conjecture generation, sequence analysis, and experimental mathematics for mathematical discovery. Covers sequence analysis (OEIS lookups, recurrence relations, generating functions), pattern detection methods (finite differences, ratio analysis, modular patterns), conjecture generation workflow, classical integer sequences (Fibonacci, Catalan, partition numbers, Bernoulli numbers), combinatorial identities, the probabilistic method (Erdos, expected value arguments, Lovasz Local Lemma), AI-assisted discovery (FunSearch, Ramanujan Machine), and confidence calibration with cautionary tales (Mertens conjecture, Polya conjecture). Use when discovering patterns, analyzing sequences, generating conjectures, or working with combinatorial identities.

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。

GitHub interactome explorer for bmorphism/plurigrid ecosystem. Maps collaborations across AlgebraicJulia, Topos Institute, Anthropic, and MCP servers. Use for discovering cobordisms between research communities.

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。

Python fuzzing with Atheris for discovering vulnerabilities in Python code.

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。

Executes a four-phase feature addition workflow (Discovery, Planning, TDD Implementation, Verification) for Python projects. Use when adding a new feature end-to-end — discovering project structure and integration points, drafting a feature spec with MoSCoW-prioritized requirements and BDD acceptance criteria, implementing via test-first TDD cycles, then verifying with ruff lint, ty type checks, and behavior-focused regression and contract coverage.

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 skill lifecycle by tracing call chains, detecting circular dependencies, finding instruction contradictions, identifying duplicated datasets, analyzing bidirectional coherence, discovering scriptable sequences, and learning patterns. Use when checking skill coherence, validating skill workflow, finding semantic gaps in plugin structure, or auditing plugin before marketplace submission. Generates audit reports to .plugin-creator/audits/ with findings by dimension.

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 InstallAnywhere .iap_xml installer definitions — use when querying action sequences, discovering variables, resolving platform conditions, navigating panels, or comparing installer variants. Files are 2.5+ MB, 65,000+ lines — too large for context reads, requires structural dasel queries.

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 discovering niche signals, auditing ICP or won/lost evidence, rescoring accounts, or building account and lead scoring Plays. Triggers on fit scoring, engagement scoring, external proxies, and scoring leakage. Skip pure outreach copy or contributor skill installation tasks.

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。

Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.

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 when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'. Also use proactively when discovering valuable findings worth preserving.

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。

Read-only runbook for how the VNX fabric actually works — state resolution, the single-entry dispatch door, gate invocation, the horizon planning layer, the plan-gate panel, and the hard gotchas that repeatedly bite (PATH-break, dual-CLI, codex-cert, classifier-protected actions). Use when you need to look up a fabric operation instead of rediscovering it, or when a fabric command behaves unexpectedly. Companion to the t0-orchestrator skill (judgment) and vnx-manager (infra maintenance); this one is pure reference.

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。

Generates and validates Ansible playbooks from infrastructure requirements. Uses ansible-lint for validation and queries Ansible Galaxy API for discovering certified roles and 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。

Use when analyzing vault structure, finding orphan notes, discovering missing connections, identifying bridge concepts, or checking vault health from a graph perspective. Triggers on "vault graph", "map vault", "find orphans", "missing links", "vault structure", "knowledge graph".

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 searching for academic papers related to a topic, finding papers similar to one already in the vault, or discovering research gaps. Triggers on "find papers", "related papers", "paper search", "literature", "what papers should I read about X".

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。

Plan a multi-stop tour route with waypoint optimization, drive/walk time estimation, and POI discovery along the route using OSM data. Covers geocoding, nearest-neighbor and TSP-based ordering, time/distance matrix calculation, and itinerary generation with points of interest. Use when planning a road trip or walking tour with multiple destinations, optimizing visit order to minimize travel time, discovering sites along a route, or comparing driving versus walking versus public transport options.

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。

Configure reverse proxy patterns across multiple tools including Nginx, Traefik, and ShinyProxy. Covers WebSocket proxying, path-based and host-based routing, SSL termination, and Docker label auto-discovery. Use when routing multiple services behind a single entry point, proxying WebSocket connections (Shiny, Socket.IO), auto-discovering Docker services with Traefik labels, or adding SSL termination to services that don't handle TLS natively.

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 human-curated dbt model index must guide BigQuery SQL for a warehouse question. Not for discovering undocumented models or executing warehouse changes.

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。

A zero-risk first Cowork experience for discovering what Cowork does differently. Use when onboarding to Cowork, for getting started safely, during first-time exploration, when starting fresh with a new AI tool, or when the user says "I am new to Cowork", "first task", "show me what Cowork does", "what can you do that Chat cannot", "help me get started", or "safe first task".

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。