「models」の検索結果

Use when reviewing Python changes - Django, Flask and FastAPI handlers, subprocess, SQL, Jinja2, format strings, and data/ML code that loads pickles, models, notebooks or remote model 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。

Use when adding, importing, moving or loading textures, models, audio or scenes - per-platform compression, atlases, LODs, async loading per engine, engine metadata files (.meta, .import, .uid, .uasset), Git LFS, and asset validation tests.

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 writing or changing PyTorch code — model, Dataset/DataLoader, training and evaluation loops, determinism, mixed precision, torch.compile, checkpoints with safetensors, Hugging Face models, ONNX export, and tests that run 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。

Use when writing or changing analytical SQL or a dbt model — CTE structure, window functions, grain and join correctness, dbt data tests, unit tests, contracts and incremental models, and how to run them

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 native iOS with SwiftUI - small composable views, observable state models, atomic components, Swift 6.2+ concurrency, and system styling over hardcoded values

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 150+ AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok

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 security audits on codebases — full scans, diff reviews, threat models, vulnerability triage, remediation guidance, and finding tracking. Activate when the user says "security scan", "audit this repo", "review this PR for security", "threat model", "triage vulnerabilities", "fix this vuln", or "track findings".

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 pitch decks, one-pagers, memos, financial models, and fundraising materials. Use when the user needs investor-facing 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。

Create and render OpenSCAD 3D models. Generate preview images from multiple angles, extract customizable parameters, validate syntax, and export STL files for 3D printing.

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 writing or debugging prompts for ByteDance Seedance video models (Seedance 2.5, 2.0, 2.0 Mini, 1.5 Pro, 1.0) on Dreamina, Jimeng AI, Doubao, BytePlus ModelArk or ComfyUI, when a generated video drifts off the reference face, grows unwanted subtitles or watermarks, duplicates a character, jumps at an extension seam, or when planning multi-shot or multi-reference video briefs.

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。

Used to invoke the PXMeter tool for rigorous quality assessment of biomolecular structure prediction models (e.g., proteins, nucleic acids, small molecules). This skill covers single-sample CIF evaluations and large-scale dataset benchmarks, providing rich result parsing support. Trigger this skill when the user asks to "run PXMeter", "compare PDB/CIF evaluation results of different tools", "check benchmark scores", or asks "how accurate is the structure generated by the model".

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 Kaggle skill. Use when the user explicitly mentions Kaggle, kaggle.com, a Kaggle URL, Kaggle competitions, Kaggle datasets/models/notebooks, Kaggle forums/discussions/writeups, Kaggle benchmarks, hackathons hosted on Kaggle, Kaggle badges, or Kaggle account setup. Do not use for generic ML, GPU/TPU, notebook, dataset, benchmark, or data-science tasks unless the user clearly ties them to Kaggle.

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 writing-style contract for agent outputs (reports, ARCH docs, verdicts, threat models). Forces direct prose with concrete evidence, no marketing voice, no hedge words. The single most-referenced skill across the pipeline — used by 28 agents.

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。

Structured idea generation + multi-LLM debate for the product-owner stage. Diverge (generate genuinely different bets), debate (a 4-persona panel on 4 models argues over 2 rounds), converge (synthesize a recommendation). Used by product-owner before architect; available to architect for design-space exploration.

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 supported images, videos, audio, and 3D models via RunningHub API and run RunningHub AI Applications by webappId.

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 or edit digital 3D assets with Meshy: models, textures, rigging, animation, and reference images. For physical printing, use meshy-3d-printing.

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 or prepare models for physical 3D printing, including white or multicolor prints, Creative Lab products, sizing, and slicer handoff.

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。

Threat-models and hardens an application, API, data flow, dependency, or deployment against authentication and authorization flaws, injection, secrets exposure, unsafe deserialization, SSRF, abuse, privacy loss, and supply-chain risk. Use for security review, threat modeling, hardening, or sensitive changes. Not for generic code style review or an unexplained bug without a security hypothesis.

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。

Designs and runs reproducible evaluations for AI agents, prompts, tools, skills, and model-backed workflows using realistic datasets, isolated baselines, objective assertions, rubric grading, trajectory analysis, cost/latency tracking, and regression comparison. Use when measuring agent quality, optimizing skill triggering, comparing prompts or models, or gating an AI feature release. Not for ordinary deterministic unit tests.

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。

Designs or reviews relational, document, key-value, graph, or search data models with ownership, invariants, access paths, migrations, consistency, retention, privacy, and recovery behavior. Use for schema changes, new data stores, indexes, migrations, persistence boundaries, or query-driven design. Not for a query-only bug without a model change or for API contract 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。

Designs database schemas, migrations, and data models for PostgreSQL, MySQL, MongoDB, and Redis. Use when planning tables, relationships, indexes, or ORM-backed schema 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。

Design local AI engines for iOS. Use when wiring Apple Foundation Models, local classifiers, extraction, summarization, grounded answers, and cloud fallbacks.

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。

Formulates LP, MILP, CP-SAT models; diagnoses infeasibility and gaps. Use when a MILP is infeasible, shifts need scheduling under capacity, or choosing a solver.

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。

Designs team Git workflows for branching, PRs, and releases. Use when choosing branching models, stacked PRs, merge queues, worktree isolation for agents, or collaboration rules.

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。