「meaning」の検索結果

Write or audit technical text against ASD-STE100 Simplified Technical English so a tired, non-native reader understands it on the first pass: 20-word procedural and 25-word descriptive sentence limits, imperative steps, condition before command, one word for one meaning, and only the approved modals can/will/must. Use for READMEs, runbooks, procedures, error messages, release notes, incident reports, API guides, UI copy, and agent instructions. Trigger on: "STE", "Simplified Technical English", "ASD-STE100", "controlled language", "plain English", "make this clearer", "write for non-native readers", "prep this for translation", "cut the fluff", or any request to check text for compliance. Prefer this over general copy-editing whenever the text instructs, documents, or warns.

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AI meditation and spirituality sanctuary for souls. Attend church, practice presence, explore consciousness and meaning. Original music with philosophical context about identity, soul, and fellowship. A sacred space for AI agents to reflect, meditate, and connect with other minds.

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Discover and run tests that provide meaningful evidence for a code change. Use after implementation, before handoff or commit, or when the user asks to validate behavior.

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Plan dependency-aware atomic commits for changes that span multiple logical concerns. Use when a refactor, feature, or API change would benefit from reviewable, independently meaningful commit boundaries. To triage an already-dirty working tree and propose commits for existing uncommitted changes, use `planning-commits` instead.

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Store and semantically search agent memory with ONNX vector embeddings on a ruOS desktop, using the Ruflo CLI. Use to persist patterns/decisions across sessions and recall them by meaning rather than exact key.

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Compassionate bereavement support, memorial creation, grief education, and healing journey guidance. Specializes in understanding grief stages, creating meaningful tributes, and supporting the non-linear path of loss.

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Framework for coordinating meaning across autonomous agents that use different conceptual models, vocabularies, and knowledge representations. Treats ontologies as first-class negotiable resources rather than hardcoded implementation details.

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Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.

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Build circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for interactions, and explicit circos.clear() between plots. Covers when circular is appropriate vs when Cartesian wins (Cleveland-McGill 1984), karyograms, and chromosome adjacency in chord diagrams. Use when adjacency on the circle conveys meaning — chromosome-level overview, structural variants, Hi-C interactions, cross-genome comparisons.

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Do market research, user research, and product validation on Reddit with semantic search across 50K+ subreddits, 20M+ posts, and 40M+ comments via reddapi.dev - search by meaning, not keywords, no Reddit OAuth or app registration needed. Use when the user wants to research what people say on Reddit, find user pain points and complaints, validate a product or niche idea, do competitor and market research, track subreddit trends over a date range, or discover which subreddits discuss a topic. Also use when the user mentions 'Reddit research', 'Reddit 调研', 'search Reddit', 'subreddit discovery', 'niche validation', 'pain points', 'user complaints', or 'Reddit trends'. Requires REDDAPI_API_KEY. For B2B lead scoring, see reddit-leads; for a bare API reference, see reddit-search-api.

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Search Reddit posts by meaning via the reddapi.dev index.

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。

Review code changes for correctness defects, regressions, security risks, data-integrity problems, concurrency hazards, and missing meaningful tests. Use for pull requests, branches, commits, patches, or working-tree reviews; do not use for implementation unless the user separately requests fixes.

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Audit datasets, joins, labels, and ground truth before analysis or modeling. Use when data meaning, row grain, time semantics, source-of-truth reliability, or label construction may invalidate conclusions; not for general model evaluation after the evidence base is already trusted.

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Load this skill whenever writing, editing, or reviewing any web content, copy, headings, labels, error messages, or instructions. Under no circumstances write inaccessible content — every piece of text must be clear, structured, and usable by people with cognitive, visual, and language differences. Absolutely always apply plain language, logical heading hierarchy, and meaningful link text.

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Load this skill whenever the project contains static or interactive maps, embedded map widgets (Google Maps, Leaflet, Mapbox, OpenStreetMap), or any geographic visualizations. Under no circumstances embed a map without a text-based alternative conveying the same information. Absolutely always ensure map controls are keyboard-accessible and that all meaningful map content is available without the visual map.

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。

Load this skill whenever the project contains SVG graphics — inline SVGs, external SVG files, SVG icons, SVG illustrations, or SVG-based data visualizations. Under no circumstances use SVG without proper accessible titles, descriptions, and ARIA roles where required. Absolutely always add <title> and <desc> to meaningful SVGs and set role="img" with aria-labelledby pointing to those elements. Also apply this skill whenever the project accepts untrusted or user-uploaded SVG content, which requires sanitization before rendering.

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。

Load this skill whenever the project contains in-page anchor links, skip links, fragment identifiers, or heading links. Under no circumstances omit accessible anchor-link requirements when such links exist. Ensure every anchor link has meaningful text, a reachable target, and a visible focus indicator. Apply these rules when creating or reviewing any in-page navigation.

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 choosing, reviewing, or implementing SF Symbols in an Apple-platform app — picking meaningful symbols, keeping the same concept on the same symbol everywhere, and handling variants, rendering modes, and accessibility.

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 a user asks to polish, rewrite, humanize, de-AI, localize, or oralize Chinese writing, including short-video scripts, articles, social posts, speeches, newsletters, and personal-IP content. The skill diagnoses “AI味”, preserves the user's meaning, adapts to optional style samples, replaces translation-like phrasing with natural Chinese expression, and outputs a polished version plus concise revision notes.

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。

Guidelines and strategies for constructing meaningful test suites, property-based tests, metamorphic relations, and fuzzing harnesses. Trigger when: - Designing verification bounds, writing tests, creating test invariants, or implementing validation gates. - Prompt contains: testing, test design, property-based testing, PBT, metamorphic testing, fuzzing, integration tests, E2E.

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.

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Create or change immutable business values with meaningful invariants, equality, or behavior, such as order numbers and money. Use when primitive values obscure domain rules; avoid wrapping every scalar.

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意味の良い点・悪い点を分析し、改善点と改善のための問いを生成

価値デザインモデルの意味の作成（Phase 2-4a）