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Build an evidence-based competitive pricing strategy for ecommerce products. Use when a seller asks how to position a price against competitors, set regular and promotional prices, protect contribution margin, design bundles or price tiers, respond to competitor moves, or coordinate prices across Amazon, Shopify, TikTok Shop, Walmart, eBay, or other channels. Do not use for automated repricing implementation or claims of a mathematically proven optimal price without sufficient 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。

Identify underserved market gaps and unmet customer needs in e-commerce. Analyzes competitor blind spots, review pain points, search demand without adequate supply, and emerging customer segments.

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 a controlled dynamic-pricing or repricing system for ecommerce products. Use when a seller asks for demand-based, inventory-based, competitor-responsive, or time-based price rules; SKU eligibility; price floors and ceilings; automation approvals; simulations; monitoring; or rollback plans across Amazon, Shopify, TikTok Shop, Walmart, eBay, or other channels. Do not use for a one-time optimal-price calculation or to change live prices without explicit authorization.

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。

Practical IT troubleshooting playbooks for small teams without dedicated IT staff.

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 eBPF for deep kernel-level observability — trace syscalls, network flows, and application behavior without code changes using Cilium, Tetragon, and bpftrace.

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。

Rename a page safely: update the file, fix every inbound wikilink, add the old name as an alias, and log it. Use this skill whenever a page needs a different canonical title, the user says "rename X to Y", asks to fix an inconsistent title, or after a lint run flags naming problems. Do NOT use for merging two pages, for moving a page between folders without a name change, or for renaming files outside the wiki.

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。

Codify a successful workflow from the current conversation into a permanent project-local skill. After you discover (e.g.) a cold-email sequence that converts, an ad-creative format that beats baseline, or a content-pipeline cadence that compounds — /money-skillify writes it as a SKILL.md under the project's local skills directory so future sessions can re-invoke it without re-discovery. Use when the user says: 'this worked, save it', 'codify this', 'turn this into a skill', '把这个固化下来', '存成 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。

Bulk-localize subscription, subscription-group, and in-app purchase display names across App Store locales using asc, including API 4.4.1 version-scoped v2 resources. Use when filling or updating subscription/IAP names and descriptions without App Store Connect UI work.

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。

Capture or triage small Neva repository and engineering-harness frictions without derailing feature work.

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-line summary of key Agent Monitor metrics — active sessions, total cost from the pricing engine, events today from daily_events, top tool from tool_usage, and current model from the most recent session. Use for a fast at-a-glance check without leaving the terminal.

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。

MANDATORY for every coding agent and contributor touching localized content — keep all five localization surfaces (dashboard UI keys, wiki page, full mirrored guides, locale-aware formatting, language switchers) in parity across every supported language. Use automatically (without being asked) whenever you add or change user-visible UI copy, add an i18n key, edit README-EN.md or a localized guide, edit wiki/index.html, or add a language surface.

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 YouTube data is needed without Google API quotas or OAuth setup: transcripts, video metadata, channel info, search results, playlists. Triggers on pasted YouTube links, creator names, @handles, topic research, video summaries, channel browsing, or any request where YouTube content would help — even if not mentioned explicitly. Not for uploads, account management, or written-source-only research.

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 structured YouTube data is needed: pasted video/channel/playlist links, transcripts for analysis, video metadata, channel upload history, search results, or playlist contents — without Google API quotas or OAuth. Triggers on YouTube URLs, creator names, topic research, or any request needing YouTube content, even if not mentioned explicitly. Not for uploads, account management, or written-source-only research.

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 video content needs to be extracted as text: pasted YouTube links or IDs, requests to transcribe, summarize, quote, translate, convert video to text, or extract information from video content. Also use when a user shares a video URL without explanation and wants to know what it says. Not for uploads or account management.

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。

Draft submission-ready mathematical-modeling paper sections from the approved solution package, frozen numbers, human decision ledger, and verified figures without searching scattered exploratory outputs or inventing interpretation.

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。

Collect and analyze relevant papers, reports, and reference methods to inform method selection without fabricating references or copying models blindly.

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。

Build and risk-screen a compact role-based method shortlist for a mathematical-modeling subquestion. Use after problem framing and data profiling, before model code generation, to propose a main candidate, a usable baseline, and at most one conditional fallback without padding the pool.

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 scoped or final cross-media consistency checks for mathematical-modeling artifacts, comparing canonical numbers, symbols, parameters, decisions, files, and paper claims without performing full-workspace audits for low-risk 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。

Classify each parsed mathematical-modeling subquestion by required output and structure, surface ambiguous framing trade-offs for human choice, and record primary/secondary task types without selecting algorithms.

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。

Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace.

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 whether the semantic evidence required by the active lean or submission profile exists and is current, without requiring one verbose artifact per skill or an arbitrary number of pass bullets.

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。

Summarize modeling experiment evidence, compare the approved main method with a usable baseline, surface fallback triggers, and produce a decision-point or final report without creating routine per-round prose.

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。

Inspect a mathematical-modeling workspace, evaluate lean or submission gates per subquestion, update machine-readable manifests, classify change impact, and route one next action without duplicating downstream work.

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-based 3D design tool with visual editor, animation, and web export. Use this skill when creating 3D scenes without code, designing interactive web experiences, prototyping 3D UI, exporting to React/web, or building designer-friendly 3D content. Triggers on tasks involving Spline, no-code 3D, visual 3D editor, 3D animation, state-based interactions, React Spline integration, or scene export. Alternative to Three.js for designers who prefer visual tools over 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。