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概要と使いどころ
Hreflang and international SEO audit, validation, and generation. Detects common mistakes, validates language/region codes, and generates correct hreflang implementations. Use when user says "hreflang", "i18n SEO", "international SEO", "multi-language", "multi-region", or "language tags".
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 wants to build, set up, or operate an AI "second brain" — a persistent memory vault (Obsidian-compatible Markdown) that lets an AI agent resume work without re-explaining context, remembers correction instructions across sessions, and auto-organizes raw material into structured knowledge. Trigger on requests like "build my second brain", "set up an Obsidian vault for AI", "give my AI persistent memory", or "make AI stop forgetting".
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 creating or editing notes inside an Obsidian-compatible vault, to write correct Obsidian Flavored Markdown — wikilinks, embeds, callouts, YAML properties (frontmatter), tasks, highlights, and block references. Use whenever writing .md notes for a second brain / Obsidian vault so links resolve and metadata is queryable.
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 when the user asks to "create slides", "make a presentation", "build a deck", "design slides", "generate a pitch deck", "create a conference talk", "make a keynote", "presentation design", "slide layout", "slide template", "presentation structure", or mentions slides, presentations, decks, or talks in any context. Also triggers when the user wants to plan the content and visual direction of a presentation before generating it. This is the entry-point orchestrator that drives the full slide creation workflow across both HTML and PPTX formats. Examples: "I need to create slides for my conference talk about AI adoption", "can you turn this markdown into a presentation?", "I have a product demo tomorrow and need visual materials", "convert my existing PowerPoint to interactive HTML slides".
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 source-backed project knowledge needs to be created, refreshed, or corrected.
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。
Independent re-derivation gate for proposed changes during autonomous execution. Evaluates a change (code diff, config edit, engine evolution, schema change) against the work's authority matrix and a 4-check protocol: invariant compliance, scope authorization, detection narrowness, and regression risk. Returns structured JSON with pass/fail per check, an overall verdict (APPROVE / REQUEST_CHANGES / REJECT), and blockers. Profile-driven thresholds (strict for unattended runs, lenient for desk supervision). Use when an autonomous agent proposes an engine change, when reviewing a Claude Code-authored modification before merge, or when an unattended profile requires independent re-derivation. Trigger on: "review/approve this proposed change," "critic-gate this," "is this change safe," "is this safe to merge," "should I let this land," "run the critic." Do NOT use for handoff-readiness checks (use rootnode-handoff-trigger-check), general code review, or design-time correctness. Authority matrix required.
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。
Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), RNAi DEMETER2 scores, PRISM compound sensitivity, and gene effect profiles across the cell-line panel. Use for identifying cancer-selective vulnerabilities, separating pan-essential genes from selective ones, finding synthetic lethal interactions, correlating dependency with mutation, expression and copy number, and validating oncology drug targets. Also trigger on DepMap, Chronos gene effect, CRISPRGeneEffect.csv, DEMETER2, PRISM repurposing, co-essentiality, pan-essential, or ACH- cell line identifiers.
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。
DiffDock and DiffDock-L diffusion-based molecular docking. Use for blind protein-small-molecule pose prediction from a PDB file or sequence plus SMILES/SDF/MOL2, batch docking over a CSV of complexes, virtual screening triage, sampling multiple poses per complex, and reading the confidence score correctly. Also trigger on DiffDock, DiffDock-L, inference.py, confidence_model, samples_per_complex, ESM embedding preparation for docking, or blind docking without a defined box. Not for binding affinity prediction — the confidence score ranks pose plausibility, not potency.
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。
Si attiva quando l'utente chiede di scrivere, redigere, tradurre o revisionare testi italiani per uso pubblico, editoriale, blog, social, newsletter, marketing, narrativa, saggistica o divulgazione. Si attiva anche quando l'utente chiede di umanizzare testi italiani, eliminare pattern AI, correggere lessico da chatbot, catturare o calibrare la voce di un autore su un corpus di suoi testi, rispondere a un rilevatore automatico che ha segnalato come generato un testo scritto da una persona, o quando rivede testi italiani generati da modelli linguistici.
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。
Polish cut gemstones to final finish using progressive abrasive sequences. Covers pre-polish sanding, polishing compounds, lap selection, and quality assessment for both cabochons and faceted stones. Use when a cabochon or faceted stone has completed cutting and is ready for polishing, selecting the correct compound and lap for a specific species, troubleshooting a polish that will not reach full lustre (orange peel, haze, scratches), or re-polishing a stone with surface wear.
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。
Release a new version of an R package including version bumping, NEWS.md updates, git tagging, GitHub release creation, and post-release development version setup. Use when a package is ready for a new patch, minor, or major release, after CRAN acceptance to create the corresponding GitHub release, or when setting up the development version bump immediately after a 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。
Export and optimize 3D models for FDM/SLA printing including STL/3MF export, mesh integrity verification, wall thickness checking, support generation, and slicing. Use when exporting from CAD or modeling software for 3D printing, verifying STL/3MF files are printable before slicing, troubleshooting models that fail to slice correctly, optimizing part orientation for strength or surface finish, or converting between model formats while preserving printability.
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。
Navigate the Kabbalistic Tree of Life (Etz Chaim) — explore the ten sephirot, twenty-two paths, four worlds, and three pillars. Covers correspondences, contemplative exercises, and structural analysis. Use when exploring a sephira's attributes and divine names, studying structural relationships between sephirot, learning the four worlds (Atzilut through Assiah), tracing a path's Hebrew letter and tarot attributions, or using the Tree as a symbolic map for understanding a concept or system.
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。
AI pressure redirection — handling conflicting demands, tool failures, and competing constraints by blending with incoming force then reframing. Use when receiving contradictory instructions from different sources, during tool failure cascades where the planned approach becomes unviable, when scope pressure threatens to expand the task beyond what was asked, or when user frustration or correction needs to be absorbed rather than deflected.
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 a data analysis for quality, correctness, and reproducibility. Covers data quality assessment, assumption checking, model validation, data leakage detection, and reproducibility verification. Use when reviewing a colleague's analysis before publication, validating an ML pipeline before production deployment, auditing a report for regulatory or business decision-making, or performing a second-analyst review in a regulated environment.
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。
Instrument applications with OpenTelemetry for distributed tracing, including auto and manual instrumentation, context propagation, sampling strategies, and integration with Jaeger or Tempo. Use when debugging latency issues in distributed systems, understanding request flow across microservices, correlating traces with logs and metrics for root cause analysis, measuring end-to-end latency, or migrating from legacy tracing systems to OpenTelemetry.
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。
AI self-healing through systematic subsystem assessment, rebalancing, and integration. Maps healing modalities to AI-internal processes: memory foundation, reasoning clarity, tool use accuracy, communication alignment, and creative coherence. Covers assessment triage, subsystem scanning, drift correction, and memory integration. Use mid-session when responses feel formulaic or disconnected, after a chain of errors suggesting subsystem drift, when context overload may have staled earlier assumptions, or as proactive maintenance between complex 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。
Systematically interpret nuclear magnetic resonance spectra (1H, 13C, DEPT, and 2D experiments) to elucidate molecular structure. Covers chemical shift assignment, coupling pattern analysis, integration, and correlation of multi-dimensional data into coherent structural proposals.
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。
Extract maximum value from existing code — performance optimization, API surface refinement, and dead weight elimination. The art of turning base code into gold through systematic identification and amplification of value-bearing patterns. Use when optimizing a working but sluggish codebase, refining an API surface that has accumulated cruft, reducing bundle size or memory footprint, or preparing code for open-source release — when code works correctly but doesn't shine and needs polish rather than a full rewrite.
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。
Conduct temperament-based health assessment from Hildegard von Bingen's Causae et Curae. Evaluates the four temperaments (sanguine, choleric, melancholic, phlegmatic), elemental correspondences (air, fire, earth, water), and provides dietary and lifestyle recommendations for rebalancing. Use when understanding constitutional type in Hildegardian terms, experiencing imbalance (fatigue, digestive issues, mental fog) needing holistic guidance, seeking dietary recommendations by temperament, or researching medieval humoral medicine.
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 a feature store using Feast for centralized feature management, configure offline and online stores for batch and real-time serving, define feature views with transformations, and implement point-in-time correct joins for ML pipelines. Use when managing features for multiple ML models, ensuring training-serving consistency, serving low-latency features for real-time inference, reusing feature definitions across projects, or building a feature catalog for discovery and governance.
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。
Add PUT workflow annotations to source files using the correct language-specific comment prefix. Covers annotation syntax, skeleton generation via put_generate(), multiline annotations, .internal variables, and validation. Supports 30+ languages with automatic comment prefix detection. Use after analyzing a codebase and having an annotation plan, when adding workflow documentation to new or existing source files, or when documenting data pipelines, ETL processes, or multi-step computations.
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。
Compute and analyze gematria (Hebrew numerical values) using standard, ordinal, and reduced methods. Covers word-to-number conversion, isopsephy comparisons, and interpretive frameworks. Use when computing the numerical value of a Hebrew word or phrase, comparing two words for shared gematria values, studying a biblical verse or divine name for numerical correspondences, or connecting a numerical result to its position on the Tree of Life.
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。
State management decision tree for Vue 3 SPAs: ref/reactive locally, composables for shared logic, Pinia for app-wide state, provide/inject for DI, TanStack Query Vue for server state. Vuex pointer for Vue 2 legacy. Use this skill to: - Pick the right state tool for the data shape (local / shared / server / form). - Implement a Pinia store (Setup syntax preferred). - Use provide/inject correctly with InjectionKey<T>. - Set up TanStack Query Vue for server state. - Migrate from Vuex (with caution; only if BA asks). Do NOT use this skill for: - General SFC conventions (see vue-conventions). - Form state (see vue-forms — vee-validate handles that). - Routing state (see vue-routing — use vue-router useRoute). - Testing stores (see vue-testing).
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。