「how」の検索結果

Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.

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 planning or restructuring what pages a site has and how they connect: hierarchy, navigation, URL patterns, breadcrumbs, and internal linking. Not for XML sitemaps, which are in seo-audit.

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。

This skill should be used when user asks to "upload my model to Ultralytics Platform", "push this run to the platform", "upload a dataset to platform", "download a dataset from platform", "search platform datasets", "start cloud training", "train on platform GPUs", "export a model on platform", "deploy a model endpoint", "run Moondream on Platform", "auto-annotate a Platform dataset", "run hosted AI inference", "why is my run not showing on platform", or mentions platform.ultralytics.com, ul:// URIs, ultralytics-platform, or ULTRALYTICS_API_KEY.

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。

Looks up current LiveKit facts (API signatures, CLI flags, config options, model and provider support, SDK changelogs, pricing) from the docs instead of answering from memory. Use whenever a question touches LiveKit specifics: "does LiveKit support X", "what changed in agents 1.8", "what are the arguments to Y", "how much does LiveKit cost", "find an example of Z in the LiveKit repos", or before writing any LiveKit code. Other LiveKit skills load this one first. Covers the LiveKit Docs MCP server and the `lk docs` CLI.

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。

This skill should be used when the user asks "how to setup GitHub CLI", "configure gh", "gh auth not working", "GitHub CLI connection failed", "gh CLI error", or needs help with GitHub authentication.

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。

Drives a multi-turn conversation with a LiveKit agent running locally to see what it does. Use when the user says "test my agent", "try my agent", "does this work", "why did it call that tool", "it says the wrong thing when I ask X", "test this change", or whenever you have edited an agent and need to check how it behaves. Wraps `lk agent debugger`: start the agent in text mode, send turns, read the tool calls, handoffs, errors and logs behind each reply, and restart after an edit. It runs without audio or a LiveKit room at one LLM call per turn, so it is the preferred way for a coding agent to live-test during development, and the default when the user says "test" without naming unit tests or simulations.

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。

Trigger when: (1) User mentions "manimgl" or "ManimGL" or "3b1b manim", (2) Code contains `from manimlib import *`, (3) User runs `manimgl` CLI commands, (4) Working with InteractiveScene, self.frame, self.embed(), ShowCreation(), or ManimGL-specific patterns. Best practices for ManimGL (Grant Sanderson's 3Blue1Brown version) - OpenGL-based animation engine with interactive development. Covers InteractiveScene, Tex with t2c, camera frame control, interactive mode (-se flag), 3D rendering, and checkpoint_paste() workflow. NOT for Manim Community Edition (which uses `manim` imports and `manim` CLI).

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。

Select and use Audio Toolbox acoustic, psychoacoustic, and speech quality metrics. Use when computing loudness, sharpness, roughness, fluctuation strength, noise criteria (NC/RNC/RC), speech transmission index (STI), speech intelligibility index (SII), speech quality (ViSQOL, STOI), SPL, reverberation time (RT60), tone-to-noise ratio, or prominence ratio. Also use when asked about PESQ, POLQA, calibration factor, EBU R 128, LUFS, HVAC noise, background noise evaluation, or how to measure audio quality or noise compliance. Covers calibration, standard selection, signal alignment, and the complete function inventory including what does NOT exist.

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。

Discover MATLAB Parallel Computing Toolbox clusters on the network and in the cloud, and manage their profiles — list, inspect, import, export, set default, validate, and delete. Use whenever the user asks what parallel computing resources, clusters, or cluster profiles they have or can use — e.g. "what parallel resources do I have", "show my cluster profiles", "list clusters", "what clusters can I run on", "where can I submit jobs" — and for any work with parcluster, parallel.listProfiles, parallel.defaultProfile, MJS / Generic / HPC Server / MJSComputeCloud clusters, .mlsettings files, or profile validation. Does NOT cover job submission, parpool, or parfor.

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。

Show all installed MATLAB products and support packages for a given MATLAB installation folder. Use when listing, checking, or verifying what products or support packages are in a MATLAB installation.

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。

Speed up local parfor, parfeval, or spmd by switching to a thread-based parallel pool. Trigger when a user describes slow or disappointing local parallel performance, even if they don't mention threads. Symptoms: parfor on a laptop/workstation is slower than expected or "only slightly faster than for"; parfor scales poorly with the number of workers; ticBytes/tocBytes, the Parallel Pool dashboard, mpiprofile, or system tools show large per-worker data transfer; large broadcast variables or sliced inputs make iterations slow; opening a process pool dominates a short workload; user mentions serialisation or data transfer overhead. Also trigger on any question about whether code or a function works on a thread pool. For non-pool MATLAB performance work (vectorisation, preallocation, profiling), defer to matlab-optimize-performance.

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。

Display 3-D image volumes, medical image volumes, surface meshes, and annotations for 3-D image processing. Use when displaying 3-D images or isosurfaces with volshow, creating volume viewers with viewer3d, adding Regions of Interest (ROI) or annotations, overlaying masks or segmentations, streaming volumetric data, or building apps with volume display.

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。

Display images and annotations for image processing, computer vision, and visual inspection. Use when displaying images with imageshow, creating image viewers with viewer2d, adding Regions of Interest (ROI) or annotations, overlaying masks or segmentations, streaming video frames, or building apps with image display.

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。

TikTok Shop content creation strategy and planning. Trending formats, viral hooks, product showcasing, hashtag strategy, and content calendar development. Use when the user asks about TikTok content strategy, viral content creation, TikTok marketing, or content planning.

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。

Complete TikTok Shop selling guide. Setup, listing optimization, content strategy, live selling, creator affiliates, and scaling strategies. Use when the user asks about TikTok Shop setup, how to sell on TikTok, TikTok Shop guide, or getting started with 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。

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。

Use when publishing harness improvements to the remote kit repo. Diffs managed files, shows what changed, bumps version, and pushes. Counterpart to vc-update (pull).

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。

Pull latest agent harness improvements from the remote kit repository. Shows a dry-run diff summary, waits for confirmation, then applies updates.

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。

CloudBase PostgreSQL access-pattern and slow-query quality guidance. Use when designing how tables are read and written, eliminating per-row database calls, adding indexes for filters or joins, reviewing high-traffic data access, or explaining a slow SQL query. Not for first-time PG SDK setup, login UI, or NoSQL 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 contributing to Tel-Agent - picking an issue to work on, setting up the repository for the first time, starting or finishing a task, opening a pull request, or asking "what can I work on" / "how do I start" / "is my change ready to submit". Covers the full path from a fresh clone to a merged pull request.

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, rewriting, or improving technical docs (quickstarts, how-tos, tutorials, concept pages, or API references).

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 a new docs section or product area, editing llms.ts / the llms.txt or llms/[...slug] / llms-full.txt routes / get-llm-text / skill.md / .well-known endpoints, or working on the "agent score", "llms.txt", or anything "agent-ready" in the docs and site apps. Explains the invariants the Mintlify agent-readiness audit measures and how to hold 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。

Trace where the user's recorded position on something has shifted: superseded claims, contradictions between sources of different dates, and what evidence moved them. Use this skill when the user asks what they have changed their mind about, how their thinking on a topic developed, what they used to believe, or wants a quarterly look back at their own positions. Do NOT use for finding contradictions between sources with no time dimension, or for a current-state answer.

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。

Scaffold a first eval suite for an agent: mine real failures into cases, write behavioural checks over traces, and generate the runner. Use when the user wants evals, regression tests for an agent, a golden set, or asks how to know a prompt/model change did not break things. Do NOT use for a single task's done-check (goal-test) or for auditing context (context-audit).

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。