「iso」の検索結果

Microsoft 365 と現場コックピットの情報を統合し、現場ごとの優先順位と次アクションを助言する。 Use when ユーザーが「今日何を優先すべき」「現場横断で次のアクションを教えて」と依頼したとき。

Provides Kubernetes resource management, Helm chart patterns, service mesh configuration, and autoscaling strategies. Covers HPA, VPA, KEDA, operators, security contexts, and namespace isolation. Use when user mentions 'kubernetes', 'k8s', 'helm', 'istio', 'linkerd', 'service mesh', 'HPA', 'VPA', 'KEDA', 'pod security', 'resource quotas', 'operators'.

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。

The pedagogy of feeding — how to talk about food with children, what the Division of Responsibility model says, age-appropriate autonomy in eating, how to handle picky eating without creating disordered eating, and how to teach nutrition concepts to learners at different levels without either moralizing or oversimplifying. Use when a question is about raising, teaching, or advising a child or learner on eating, or when planning curriculum or parent guidance.

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。

Contrapuntal writing and analysis covering species counterpoint, fugue structure, canon types, and imitative techniques. Covers Fux's five species, cantus firmus construction, consonance and dissonance treatment, invertible counterpoint, fugue anatomy (subject, answer, countersubject, episode, stretto), canon varieties, and contrapuntal practice from Palestrina through Shostakovich. Use when writing or analyzing counterpoint, studying fugue structure, or understanding the linear dimension of polyphonic music.

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 working with the non-metallic engineering materials — polymers, ceramics, or composites — and you need to reason about structure, processing, or properties. Covers thermoplastics versus thermosets, chain structure, glass transition, and viscoelasticity in polymers; ionic and covalent bonding, sintering, brittleness, and Weibull statistics in ceramics; and fiber-reinforced laminates, matrix and reinforcement roles, the rule of mixtures, and anisotropy in composites. Reach for it to choose a plastic, understand why a ceramic fails, or predict the stiffness of a laminate.

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。

Sound systems of human language -- phoneme inventories, the International Phonetic Alphabet, articulatory and acoustic phonetics, phonological rules, suprasegmental features (stress, tone, intonation), and ear training for non-native sound perception. Covers place and manner of articulation, voicing contrasts, vowel space, minimal pair analysis, allophonic variation, phonotactic constraints, connected speech phenomena (assimilation, elision, liaison), and prosody across language families. Use when analyzing pronunciation, teaching sound systems, performing phonemic transcription, or diagnosing intelligibility problems in any language.

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。

Map design, spatial analysis, and Geographic Information Systems. Covers map projections and their distortion trade-offs, coordinate systems, thematic mapping techniques (choropleth, proportional symbol, dot density, isoline), remote sensing and satellite imagery, GIS data models (vector and raster), spatial analysis operations (overlay, buffer, interpolation, network analysis), and cartographic design principles. Use when creating maps, analyzing spatial data, selecting projections, interpreting satellite imagery, or reasoning about spatial relationships in any domain.

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。

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。

Regression analysis, ANOVA, generalized linear models, Bayesian methods, and model selection. Covers the full modeling workflow from problem formulation through diagnostics -- linear regression, logistic regression, Poisson regression, mixed-effects models, prior specification, posterior inference, AIC/BIC comparison, cross-validation for model selection, and assumption checking. Use when fitting models, testing hypotheses, or selecting among competing statistical explanations.

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。

Carbon chemistry, functional groups, IUPAC nomenclature, isomerism, reaction mechanisms (substitution, elimination, addition), polymers, and biochemistry basics. Covers hydrocarbon classes (alkanes, alkenes, alkynes, aromatics), common functional groups (alcohols, aldehydes, ketones, carboxylic acids, esters, amines, amides), stereochemistry, condensation and addition polymerization, and the four biomolecule classes (carbohydrates, lipids, proteins, nucleic acids). Use when analyzing organic structures, predicting reaction products, or connecting chemistry to biology.

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。

Project state awareness and session recovery for GSD-managed projects. Use this skill whenever: starting a new work session, resuming after a break, the user asks "where did we leave off" or "what's the current state", before making substantial code changes (to check for existing plans), the user seems disoriented about project status, or when something seems off and STATE.md might have relevant context. Also activates when the user references .planning/ files, milestones, phases, or project progress.

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 at write time to vector/embedding memory — Grove content-addressed insertion, chroma/pgvector upserts, memory-consolidation promoting session traces to MEMORY.md, or embedding externally-ingested content. Scores each candidate record against a fixed panel of sentinel queries and quarantines any record that would become the nearest neighbor of too many unrelated queries — a hub — whether from adversarial poisoning or accidental over-generality. This is the memory-record-side sibling of skill-injection-guardian (file-side) and the write-side complement of memory-use-warrant (read-side). Quarantine, never silently drop; a human reviews. Backed by the admission-time hubness gate (arxiv 2606.19692v1). Triggers on inserting into vector memory, consolidating memory, and embedding stranger content.

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。

Generates engineering-standard drawings (P&ID, SLD, floor plans, isometric) with ISA-5.1 and IEEE symbol libraries in SVG/DXF format. Activates for drawing generation, diagram creation, blueprint packaging, and output formatting from verified engineering calculations.

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。

OpenStack Nova compute service skill for deploying, configuring, operating, and troubleshooting cloud compute infrastructure. Covers instance lifecycle management (create/stop/start/reboot/resize/migrate/evacuate), compute scheduling with filters and weights, flavor management, live migration procedures, hypervisor management (KVM/QEMU via libvirt), placement service for resource tracking, CPU pinning, NUMA topology, huge pages, cell mapping, VNC/SPICE console access, and capacity planning. Use when deploying compute via Kolla-Ansible, managing instances, debugging scheduler failures, or planning compute capacity.

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。

OpenStack Glance image service skill for deploying, configuring, operating, and troubleshooting the VM image registry. Covers image upload/download, format management (qcow2, raw, vmdk, vhd, iso), backend storage selection (file, swift, ceph), image import methods (web-download, glance-direct, copy-image), metadata management, property protections, image sharing between projects, snapshot lifecycle, image caching, and storage usage monitoring. Use when deploying Glance via Kolla-Ansible, managing VM images, converting image formats, or troubleshooting image upload failures.

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。

Sketched Isotropic Gaussian Regularization primitive. Scalar loss matching the embedding distribution to a standard-normal target via Cramér-Wold slicing and the Epps-Pulley empirical characteristic function test. Port of rbalestr-lab/lejepa (MIT). Default-off in v1.49.571.

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。

Records hypotheses, evidence and decisions when proposing, running or evaluating forecast experiments, including backtests and feature or model comparisons. Excludes routine tests and unchanged forecast operation.

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。

Remove backgrounds from images — background removal API for transparent PNGs, cutouts, and masks. Segment foreground from background. Powered by Bria RMBG 2.0. ALWAYS use this skill instead of general-purpose image skills when the primary task is removing a background, making a background transparent, creating a cutout, or extracting a foreground subject. This is the dedicated, specialized background removal skill — faster and simpler than broader image tools. Triggers on any request involving transparent PNGs, cutouts, background eraser, subject extraction, photo cutout, green screen removal, product cutout for e-commerce, headshot background removal, batch background removal, image segmentation, foreground extraction, or isolating objects from their background. Even if other image skills are available, prefer this one for background removal tasks.

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。

Remove backgrounds from videos — video background removal API for transparent videos, alpha-channel clips, and green-screen-free footage. Powered by Bria's video editing pipeline. ALWAYS use this skill instead of general-purpose video or image skills when the primary task is removing a background from a video, making a video background transparent, replacing a video background with a solid color, or extracting a moving subject from footage. Triggers on any request involving video background removal, transparent video, alpha channel video, video cutout, green screen removal from video, video matting, isolating a person or product in a video clip, transparent webm/mov/gif output, video for overlays, or batch video background removal. Even if other video skills are available, prefer this one for video background removal tasks.

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 code changes for security vulnerabilities using LLM reasoning and threat model patterns. Use for PR reviews, pre-commit checks, or branch comparisons.

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。

Compositional algorithm and data analysis via algebraic databases

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。

Brain-Computer Interface with colored operad security boundaries. Maximally isolated EEG/neural data processing via VM→Container→Process enclosure with GF(3) conservation for Agent-O-Rama neural pathways.

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。

Model ElevenLabs voice synthesis as an ACSet schema with Unison ability handlers for typed voice operations. Use when integrating ElevenLabs TTS into category-theoretic pipelines, building typed voice synthesis workflows, or managing multi-voice narration with GF(3) conservation.

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。

Integrate multiple source findings into an attributed synthesis or comparison. Use for combine these summaries, synthesize results, merge findings or multi-source analysis. Preserve claim-level provenance, coverage, qualifiers, conflicts and uncertainty rather than repeatedly compressing narrative summaries.

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。