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概要と使いどころ
Für Indexierung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: agb-indexierung.
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。
Google SEO APIs: Search Console (Search Analytics, URL Inspection, Sitemaps), PageSpeed Insights v5, CrUX field data with 25-week history, Indexing API v3, and GA4 organic traffic. Provides real Google field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use when user says "search console", "GSC", "PageSpeed", "CrUX", "field data", "indexing API", "GA4 organic", "URL inspection", "google api setup", "real CWV data", "impressions", "clicks", "CTR", "position data", "LCP", "INP", "CLS", "FCP", "TTFB", or "Lighthouse scores".
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。
Google SEO APIs: Search Console (Search Analytics, URL Inspection, Sitemaps), PageSpeed Insights v5, CrUX field data with 25-week history, Indexing API v3, and GA4 organic traffic. Provides real Google field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use when user says "search console", "GSC", "PageSpeed", "CrUX", "field data", "indexing API", "GA4 organic", "URL inspection", or "real CWV 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。
Create and maintain AGENTS.md / CLAUDE.md snippet indexes that route tasks to the correct dotnet-skills skills and agents (including compressed Vercel-style indexes).
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 journal indexing/inclusion status on CNKI - check which databases include a journal (北大核心, CSSCI, CSCD, SCI, EI, etc.), get impact factors and evaluation data. Use when user asks about a journal's level, indexing, or ranking.
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。
Sync every enabled repo in the curated skill index and open a confirmation-gated PR. Use when refreshing already-indexed sources. Don't use for adding new repos, improving a single skill, or installing skills locally.
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。
Technical SEO auditing covering crawlability, indexation, Core Web Vitals, on-page optimization, and competitive gaps, with an 85-point checklist and remediation plans. Use when auditing technical SEO or diagnosing indexation issues.
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。
Google SEO APIs: Search Console (Search Analytics, URL Inspection, Sitemaps), PageSpeed Insights v5, CrUX field data with 25-week history, Indexing API v3, and GA4 organic traffic. Provides real Google field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use when user says "search console", "GSC", "PageSpeed", "CrUX", "field data", "indexing API", "GA4 organic", "URL inspection", "google api setup", "real CWV data", "impressions", "clicks", "CTR", "position data", "LCP", "INP", "CLS", "FCP", "TTFB", or "Lighthouse scores".
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 Core Spotlight indexing infrastructure for making app content searchable via system Spotlight with rich attributes and deep link integration. Use when user wants to index content for Spotlight search, Siri suggestions, or system-wide searchability.
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。
Weekly, browser heavy. Unions every sitemap each property declares without a browser, builds the candidate set from URLs not already in the indexing ledger, then drives the member's own search performance console to inspect each candidate and request indexing inside an account wide allowance. Spends what is left on sitemap health, which is unmetered. It inspects, requests, and views or submits sitemaps inside that console and does nothing else there, ever, and it never removes a sitemap.
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 only when the user explicitly asks to use `$ralph-specum-index`, or explicitly asks Ralph Specum in Codex to generate or refresh index artifacts.
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。
Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental 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。
Curate the web-capture index. Use when the capture backlog grows, captures sit unprocessed at seedling/pending, or to surface stored research during work.
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。
Search, query, and maintain the qmd-indexed wiki - semantic search, keyword search, re-index after adding pages, check index status.
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。
Fix SQLite "database disk image is malformed" errors caused by corrupted FTS5 indexes. Use when: (1) UPDATE/INSERT fails with "stepping, database disk image is malformed" but PRAGMA integrity_check returns "ok", (2) Only specific records fail to update while others succeed, (3) Records contain dirty text with tabs, newlines, or unusual characters that were inserted into FTS5-indexed columns. The misleading error message suggests disk corruption, but the actual issue is FTS5 index corruption from malformed text 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。
Fix psycopg2 "IndexError: tuple index out of range" when using LIKE with parameterized queries. Use when: (1) cursor.execute() fails with IndexError on a query containing LIKE '%pattern%', (2) SQL LIKE wildcards conflict with psycopg2 %s parameter placeholders, (3) Query works in psql but fails in Python. The % character has dual meaning: SQL LIKE wildcard AND psycopg2's parameter substitution marker.
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。
Fix "content disappears after publishing" bugs caused by REST API indexing lag. Use when: (1) User publishes content but it doesn't appear in their feed/profile, (2) REST API returns stale data immediately after write operations, (3) Async indexing backends (ClickHouse, Elasticsearch, etc.) haven't processed new events, (4) Content shows briefly then vanishes on refresh. Applies to any system with separate write path (WebSocket/direct DB) and read path (REST API with async indexing).
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 from the user's own indexed documents with Guaardvark's local RAG, browse and read indexed files section by section, remember facts across sessions, and process or fetch new material. Use when the user asks what their documents say, wants a source-cited answer from their files, says "remember this", or asks to index a PDF, DOCX, spreadsheet, image or URL.
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。
Convert structured project-note JSON manuscripts into validated EPUB and optional Kindle-clickable PDF files. Use when the user asks to turn project notes, book-system JSON, FIRE-indexed notes, Luhmann/Zettelkasten numbered chunks, table-of-contents cards, index cards, cross-linked project notes, or manuscript JSON into an EPUB/PDF with chapter directories, keyword index cards, weighted links, bidirectional backlinks, versioned filenames, chapter-splitting plans, and full link 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。
Plan, implement, or review vector index tuning work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests vector index tuning work.
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。
Database design specialist for schema modeling, query optimization, indexing strategies, and data integrityUse when "database design, schema, indexes, query optimization, migrations, normalization, database scaling, foreign keys, data modeling, database, sql, postgres, mysql, mongodb, schema, indexes, migrations, normalization, optimization" mentioned.
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。
Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuningUse when "adding search to, algolia, instantsearch, search api, search functionality, typeahead, autocomplete search, faceted search, search index, search as you type, algolia, search, instantsearch, indexing, relevance, faceted-search, autocomplete" mentioned.
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。
DEPRECATED - Use building-github-index instead. Superseded per-file GitHub API implementation of progressive disclosure repository indexes.
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。
Builds a portable, embedding-free knowledgebase from a set of files and delivers it as a self-contained `.skill` bundle (BM25 index + bundled searcher + query protocol). Use when a user wants to turn uploaded files, a folder, or a corpus into a searchable knowledgebase they can hand to any agent — phrased as "make a knowledgebase", "build a KB skill", "package these docs for retrieval", "create a searchable bundle", or references to a `.skill` KB. The output runs anywhere with Node or Python — no model, no install, no network. Distinct from `bm25` (ephemeral in-session search) and `building-github-index` (markdown project-knowledge 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。