「consumer」の検索結果

Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.

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。

Pick a product archetype from a curated catalog before any UI gets built — the single biggest lever for not looking vibecoded. Routes the request to one of B2B-productivity, enterprise-trust, premium-consumer, playful-consumer, editorial, brutalist-distinctive, dev-tool, or marketing-landing, and returns a complete design philosophy: typography pair, color logic, motion curve, density, icon stance, reference sites, and a "feels like X" claim. Load when the user asks to pick an aesthetic, choose a design direction, decide what a UI should feel like, classify a product visually, says "what should this look like", "make this feel like [Linear/Stripe/Apple/Duolingo/...]", "give me a design direction", "what's the right aesthetic for this", or when frontend-design routes here during archetype selection. Sub-skill of frontend-design.

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。

Deprecate APIs, features, or systems safely — announce, migrate consumers, sunset on a timeline, and document alternatives. Load when removing an old API, migrating users between implementations, sunsetting a feature, or the user asks about deprecation policy, migration guides, or breaking changes. Not for deleting dead code with zero consumers (use code-simplification). Distinct from meta `deprecate-skill` (skill library retirement).

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 strategy analysis for any consumer product. Competitive analysis, market sizing (TAM/SAM/SOM), pricing strategy, launch readiness assessment, and positioning. Built from 20 years of PM experience across consumer electronics, gaming, and mobile.

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。

Detect WMI event subscription persistence by analyzing Sysmon Event IDs 19, 20, and 21 for malicious EventFilter, EventConsumer, and FilterToConsumerBinding creation.

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。

Implements API contract testing to ensure provider-consumer compatibility using Pact or similar tools. Prevents breaking changes with contract specifications and bi-directional verification. Use for "contract testing", "API contracts", "Pact", or "consumer-driven contracts".

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。

Inventory and govern a project's test assets. Connect requirements, business rules, risks, bugs, and cross-boundary contracts to stable TEST-IDs and executable evidence in the repository's existing test registry or TESTS.md. Use for test inventory, test gap analysis, unit/integration/contract/E2E/smoke classification, bug-to-test regression protection, consumer/provider contract testing, test-necessity review, and pre-delivery evidence review.

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。

Govern cross-module regression in large repositories with a REGRESSION.md ledger that records each module's downstream consumers and executable acceptance command. After a change, run the changed module and every affected downstream command, and use observed exit codes as regression evidence under the project's delivery policy. Use for module regression, regression ledgers, impact audits, downstream verification, and changes where modifying A may break B.

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。

Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.

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。

Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.

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 requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade analytical report. This skill operates in two phases — (1) generating a structured analysis framework with chapter skeleton, data query requirements, and analysis logic, and (2) after data collection by other skills, producing the final consulting-grade report with structured narratives, embedded charts, and strategic insights.

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。

Consumer-side wiring for ADR-097 Phase 3 federation_spend events — per-peer rolling windows + suspension-threshold check

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 and wire Remotion Studio config options as either startup-fixed or reloadable while preventing mixed lifecycle behavior across consumers. Use when adding, changing, or reviewing a Config setter or CLI option consumed by Studio, its preview server, compiler, HTML bootstrap, public-folder watcher, or render queue.

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。

When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' 'consumer behavior,' 'anchoring,' 'social proof,' 'scarcity,' 'loss aversion,' 'framing,' or 'nudge.' Use this whenever someone wants to understand or leverage how people think and make decisions in a marketing context. For applying psychology to specific pages, see cro; for pricing tactics, see pricing; for copy framing, see copywriting.

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, refine, test, validate, or list CLI-Anything harnesses for GUI applications in Cursor. Prefer slash commands /cli-anything, /cli-anything-refine, /cli-anything-test, /cli-anything-validate, and /cli-anything-list when available. This skill supports natural-language discovery of the generator; it does not replace those commands. Discovering already-published CLIs from CLI-Hub is a separate consumer skill (cli-hub-meta-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。

Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for CI/CD, registry, dependency drift, artifact provenance, image build, release pipeline, and runtime consumer challenges. Use when the user asks to trace dependency drift, registry pulls, malicious packages, build or release tampering, CI execution, artifact signing, or which shipped artifact the runtime actually consumes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Track, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management. Use this skill when defining a metrics framework, calculating CAC/LTV/burn multiple, benchmarking business health, or preparing metrics dashboards for investors or board reporting.

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。

Runs Inspector UI work on the standalone Threads state lab so the agent can see the overlay. Use when a CopilotKit employee asks an agent to fix, polish, add, or debug Inspector UI, chrome, panes, overlay actions, launcher, Home, Threads, Playground, Memory, or any visual behavior in @copilotkit/web-inspector. Don't use for docs-only Callout updates (load inspector-docs), runtime or core changes with no Inspector UI, showcase cell work, or reading Inspector as a consumer inside an app.

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 has written (or wants to write) a `ModularPipelineBlocks` subclass in a local Python file and needs to package it into a Hub-uploadable directory. Covers the workflow from a single `block.py` file to a published custom-block repo that consumers can load via `ModularPipeline.from_pretrained(<repo>, trust_remote_code=True)`.

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。

When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.

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。

GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.

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。

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.

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。

Publish the user's own gbrain over MCP so other devices, desktop apps and cloud agents can reach it. `gbrain mcp expose` installs and signs in Tailscale, publishes the running `gbrain serve --http` on the tailnet (HTTPS, tailnet-only by default; Funnel only when a client lives in a vendor cloud), keeps the server alive as a user service, and hands back the MCP URL. Then register one least-privilege client per consumer, choose native OAuth/PKCE or a private machine handoff for that client, and verify the connection inside the intended harness.

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。