「number」の検索結果

Retrieve translated patent description (specification) text from Nexscope. Triggered when users request patent specification translation, patent full text in other languages, translated patent full text, or want to view patent specifications in Chinese, English, or Japanese, patent specification translation, patent description translation, Nexscope, or patent translation. Also triggered when users provide a patent ID or publication number and request specification/description content in another language, or mention "patent specification translation," "description translation," "translated full text," or similar intent.

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Retrieve patent description (specification) data from the Nexscope patent database by patent ID or publication number. Triggered when users mention patent specification, patent full text, patent technical description, patent embodiment details, Nexscope specification data, patent specification, patent full text, technical description, embodiment details, Nexscope, or patent detailed description. Even if the user does not explicitly say "Nexscope," this skill should be triggered whenever they need to view the complete specification/description content of one or more patents.

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Nexscope overview analysis of Amazon keyword market competition. Trigger when the user mentions keyword competition, supply-demand ratio, competitor count, keyword search volume estimation, market competitiveness assessment, keyword popularity ranking, ad competition analysis, number of products under a keyword, keyword competition, supply-demand ratio, competitor count, search popularity, market competition analysis, Nexscope, keyword overview. Even if the user does not explicitly say "Nexscope", if their need involves assessing keyword-level competition intensity, supply-demand balance, or search result product count on Amazon, this skill should also be triggered.

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Reserved-field rules and field-number lookup for evolving AppSettings, plus the Rust/Kotlin diagnostics wire contract. Use before assigning or removing a proto field. DataStore mapping: protobuf-datastore.

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。

Act as an end-to-end data scientist: turn business questions into defensible analysis, validated models, and decision-ready reports. Use whenever the user asks to analyze, explore, or profile a dataset or CSV/Parquet/Excel file; asks what drives a metric or why a number changed ("why did churn go up?"); wants to test whether a difference is real (A/B tests, experiments, "is this significant?", "how many samples do I need?"); wants a predictive model (churn, forecast, scoring, segmentation, classification, regression); asks to review an existing analysis, notebook, or model for flaws; or needs results written up for decision-makers. Triggers in any language ("phân tích dữ liệu", "xây model dự đoán", "kiểm định A/B"), even when they never say "data science" or "statistics".

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。

Adaptive conversion of LaTeX, PDF, or Markdown sources into a complete Word .docx that follows a user-supplied .docx template. Use when pandoc --reference-doc alone is not enough — for thesis, dissertation, report, or institutional Word formatting that needs cover pages, declarations, TOC, heading numbering, captions, three-line tables, equations, citations, and visual verification.

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。

Answer a "how do I …" question about the platform with a Gherkin scenario on @datagrok-libraries/bdd that is filmed into a how-to video (grok-bdd guide), so the answer is demonstrated, sent as a video plus numbered steps, and kept as a regression test; the same scenarios, filmed in help mode, are the GIFs of the help pages

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。

Sort, hide, show, reorder, resize, pin, format, and color-code columns in a Datagrok TableView grid via the datagrok_exec tool. Use whenever the user asks to sort by a column (any direction), multi-sort, hide / show / reorder / pin / resize columns, freeze the first N columns, change number-format display, color-code cells (defaults and grid-only tint here; full per-type reference in datagrok-df-and-columns), set row height, or reset the grid back to defaults. Distinct from datagrok-df-and-columns (which owns column-level data metadata like semType, units, friendlyName, and is also where canonical color-coding lives) and from datagrok-viewers (which owns scatter plot / histogram / etc.). Does NOT cover filtering (`datagrok-filtering`), selection (`datagrok-selection`), custom cell renderer authoring (`create-cell-renderer`), saving / restoring layouts, or grid event handlers.

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Semantic code search using natural language queries. Use when users ask "where is X implemented", "how does Y work", "find the logic for Z", or need to locate code by concept rather than exact text. Returns file paths with line numbers and code snippets.

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Script the first 1-3 second TikTok hook: the spoken line, the on-screen text, and the opening visual firing at once so the viewer cannot swipe. Picks a 2026 hook formula (cold-open result, pattern interrupt, number reveal, open-loop question, relatable call-out, story) by goal of completion, saves, comments, or shares. The single biggest retention lever on TikTok. Use to script a hook from a video idea. Not for the caption (use tt-caption-writer) or scrubbing a script (use tt-humanizer).

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Foundational concepts in nutrition science — macronutrients, micronutrients, energy balance, Atwater factors, reference intakes (DRI/RDA/AI/UL), food composition tables, and the methods of human nutrition research. Grounds the rest of the department in a shared vocabulary and in the measurement limits of the field, including controlled-trial history, observational-study limits, and the biochemical basis for calorie accounting. Use when a question asks what something "is" nutritionally, how energy and nutrients are measured, or what the reference numbers mean.

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The discipline of keeping a field notebook — words, pictures, numbers, metadata, and questions captured during sustained outdoor observation. Covers the Laws notebook method, the sit-spot practice, phenology recording, sketch-first-name-later discipline, and the long-term research value of accumulated journals. Use when the task is to teach or structure ongoing field observation rather than answer a one-shot identification.

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Grammar and syntactic structures across human languages -- word order typology (SVO, SOV, VSO, VOS, OVS, OSV), morphological systems (isolating, agglutinative, fusional, polysynthetic), agreement patterns (gender, number, case, person), phrase structure, clause embedding, and cross-linguistic universals. Covers constituent analysis, dependency vs. constituency grammars, grammatical relations (subject, object, oblique), ergativity vs. accusativity, tense-aspect-mood systems, and how grammar encodes meaning differently across language families. Use when analyzing sentence structure, comparing grammar systems, teaching grammatical concepts, or understanding why a learner makes transfer errors from their L1.

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。

Understanding how digital systems actually work -- hardware, operating systems, networks, and information representation -- at a depth sufficient to reason about them rather than just use them. Covers CPU/RAM/storage/GPU roles, what an OS does, how packets travel the internet, and how computers represent numbers, text, images, and sound as binary. Use when a learner needs to build a mental model of computing rather than memorize menu paths.

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。

Before dispatching a multi-agent team, run a spectral diagnostic on the proposed communication graph and emit a (ρ, Δ, κ) coordination signature plus a pass/fail verdict against per-task-class thresholds. Builds the row-stochastic operator P from the team graph, computes the successor representation M = (I − γP)⁻¹, and ranks the topology for robustness (κ, condition number), consensus (Δ, spectral gap), and drift (ρ, spectral radius). Per Parks & Alharthi (arxiv 2605.11453), rank order on (κ, Δ, ρ) predicts coordination quality pre-execution with rank correlations of 1.0 / 0.5 / −1.0. Triggers: "dispatch the team", "team topology check", "before running the agents", "is this team configuration OK", "team pre-flight".

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。

Foundational measurements and relationships. The axioms of the system — numbers, distance, angles, and the geometry of seeing.

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。

Mathematical verification for physical calculations: unit tracking algebra (exponent maps), PhysicalQuantity pattern for compound units, SI/Imperial mixed-unit handling, Buckingham pi theorem for dimensionless groups, and common engineering dimensionless numbers. Activates for unit verification, dimensional consistency checks, scaling analysis, and calculation validation across all infrastructure domains.

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。

Measure ACSets better than authors via surjectivity gadgets, Betti numbers, Möbius classification, and p-adic ultrametric distance

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 groomed milestone with parallel kage-bunshin sessions in isolated worktrees. Use when a milestone has been groomed and /groom-milestone has produced a dispatch plan. Reads the dispatch plan, creates an integration branch, spawns one kage-bunshin (independent claude -p process) per wave item in its own worktree — each session is a full orchestrator with the Agent tool. Sequentially merges worktree branches, relays wave discoveries to subsequent waves, then lands the integration branch to main. Takes a milestone number as argument.

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Close a completed GitHub milestone. Args: {milestone-number}. Audits open and closed issues, offers to carry forward open items to a new or existing milestone, closes the GitHub milestone, updates Project V2 Status to Done for closed issues, and generates a completion summary. Use when a sprint or release is finished and needs to be officially closed.

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Use when assigning backlog items to a GitHub milestone. Args: {milestone-number} [P0|P1|P2|title-filter]. Uses backlog list to load items, shows items with GitHub Issue status, lets user select which to assign. Creates missing GitHub Issues for selected P0/P1 items, assigns all to the milestone, updates Project V2 Status to Backlog. Use after create-milestone to populate a sprint or release.

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。

Grooms a GitHub milestone for parallel execution — batch-grooms ungroomed items, assesses scope gaps, analyzes cross-item dependencies via Impact Radius overlap, builds conflict groups, assigns items to execution waves, and persists the dispatch plan via dispatch_create_plan MCP tool. Calls dispatch_wave_start per wave to register state. Use when preparing a milestone for /work-milestone execution. Pass the milestone number as the first argument. Requires milestone items assigned via /group-items-to-milestone.

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。

Assign backlog items to a GitHub milestone by bridging per-item files to GitHub Issues. Use when populating a sprint or release milestone, after create-milestone, or when a milestone number is specified with optional P0/P1/P2 or title filter. Creates missing GitHub Issues for selected P0/P1 items, assigns all selected items to the milestone, and updates Project V2 Status to Backlog.

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Transitions a GitHub milestone from planning to active execution. Use when the team is ready to begin a sprint or release cycle — bulk-transitions open issue labels from status:needs-grooming to status:in-progress, updates GitHub Projects V2 Status to In Progress, and confirms before applying changes. Requires milestone number as argument. Use after /group-items-to-milestone.

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。