'index' 검색 결과

SEO/GEO Agent Operations SOP v2 — Rebuilt from real-world operations (analook.com 0→launch, GSC incident, DataForSEO monitoring, gingiris.tools post-migration recovery). What's new in v2: • Step-by-step onboarding (Q1→Q6), multiple choice wherever possible — no big forms • Mandatory daily SEO log — first item is always GSC token status check • Data cross-validation rule: any external metric must come from ≥2 sources before use • Backlink progress tracking (6-week wait → check → alert if not indexed) • New vs. established site strategy matrix (new site <6mo: KD≤20; mature: KD up to 35+) Real incidents baked in: GSC token expired silently for 2 weeks (analook.com), P0 keywords dropped out of Top 100 after domain migration (gingiris.tools), traffic data off by 17× from single-source DataForSEO. Triggers: "SEO agent" | "SEO daily report" | "GSC monitoring" | "DataForSEO" | "GEO agent" | "backlink tracking" | "IndexNow" | "competitor comparison page" | "SEO SOP" | "autonomous SEO" | "GEO triple combo" 🇨🇳 SEO/GEO Agent 运营 SOP v2 — 基于真实运营经验重写（analook.com 从零建站 + GSC 断档 2 周 + DataForSEO 监控 + gingiris.tools 迁移权重恢复）。 对话式开局、强制日报（GSC token 是第一项）、数据交叉验证铁律、外链进度追踪、新老站区分策略。

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Semantic codebase search, code indexing, and prompt enhancement via standalone CLI. Use when: (1) Semantic code search with natural language queries, (2) Code indexing for remote codebase retrieval, (3) Prompt enhancement with codebase context, (4) Before grep/find/glob operations for better accuracy, (5) Complex requirements clarification, (6) Large codebase navigation. Triggers: "search context", "enhance prompt", "find code that", "index project", "clarify requirements". IMPORTANT: Always use ace-tool BEFORE grep/find/glob for semantic-level code location.

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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).

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Progressive Disclosure skill index — efficient skill loading in 3 layers. Layer 1 (index, ~100 tokens) always loaded. Layer 2 (summary, ~300 tokens) loaded on context need. Layer 3 (full SKILL.md) loaded on execution only.

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Indexes and searches API documentation from OpenAPI 3.0 specs using swagger-parser and lunr.js. Builds searchable indexes of endpoints, parameters, and response schemas for quick reference.

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Generate or update the centralized documentation index (docs/INDEX.md) with navigation map and cross-references.

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Find and fix broken internal links, dead external URLs, stale imports, missing cross-references, and orphaned files. Ensures all project references remain valid and up-to-date. Use when documentation contains broken internal links, external URLs return 404 errors, import statements reference moved or deleted modules, cross-references between files are out of sync, or files exist but are never referenced anywhere in the project. Also use in index mode for a directory of markdown notes with a designated index, such as an agent-memory store, where an orphan is a file the index does not link to.

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Organize, extract, prune, and verify Claude Code persistent memory files. Covers MEMORY.md as a concise index, topic extraction to dedicated files, staleness detection, accuracy verification against project state, the dual 200-line / 25KB load cap, and reachability of topic files from the index. Use when MEMORY.md is approaching either load cap, after a session produces durable insights worth preserving, when a topic section has grown beyond 10-15 lines and should be extracted, when project state has changed and memory entries may be stale, or before and after rewriting the index so that no topic file loses its only pointer.

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Parse all `# implements:` annotations in source code and emit `library/_code-index.md` as a shelf-index. Also extracts cross-module import edges and writes `library/_dependency-edges.md`. Idempotent — re-running produces byte-identical output if no annotations or imports changed.

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Work with the @upstash/search TypeScript/JavaScript SDK, a serverless full-text and semantic search database with built-in reranking. Use when adding search to an app or site, creating a search index, upserting documents with searchable content and filterable metadata, running keyword, semantic, or hybrid search queries, reranking results, filtering with SQL-like or structured filter syntax, paginating with range, fetching or deleting documents, resetting an index, or checking index info. Also use when the user asks for site search, product, document, or knowledge-base search, or a managed search service that needs no cluster to run.

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Work with the @upstash/vector TypeScript/JavaScript SDK, a serverless vector database for embeddings, similarity search, semantic search, and RAG (retrieval-augmented generation). Use when upserting, querying, fetching, ranging, or deleting vectors, upserting raw text against an index with a built-in embedding model, choosing dense, sparse, or hybrid indexes, filtering by metadata, organizing data with namespaces, running resumable queries, or connecting Upstash Vector to an AI or LLM application. Also use when the user asks for a vector store, vector search, nearest-neighbor or kNN search, embeddings storage, semantic cache, recommendations or similarity features, or a hosted vector index that needs no infrastructure.

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"Optimize SQL query performance using EXPLAIN analysis, indexing strategies, and common anti-pattern fixes. Use this skill when the user needs to speed up slow queries, design indexes, fix N+1 problems, or optimize database performance — even if they say 'this query is slow', 'optimize our database', 'which indexes do we need', or 'our dashboard takes 30 seconds to load'.".

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LlamaIndex.TS data framework for RAG, indexing, retrieval, query engines, chat engines, and agentic workflows in TypeScript

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Use when building RAG or LLM applications with LlamaIndex - data loaders, node parsing, vector stores, retrievers and rerankers, query engines, agents and workflows, streaming, or evaluation

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Analyze existing XML sitemaps or generate new ones with GSC indexing cross-reference. Validates format, URLs, and structure against actual indexing status. Use when user says "sitemap", "generate sitemap", "sitemap issues", "XML sitemap", or "sitemap indexing".

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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".

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Schema design, normalization decisions, indexing strategies, and migration safety for relational databases. Use when designing tables, choosing between normalize vs denormalize, selecting index types, planning zero-downtime migrations, or setting up connection pooling. Activate on "schema design", "normalization", "denormalization", "foreign key", "index strategy", "migration", "connection pooling", "composite key", "surrogate key", "soft delete", "polymorphic association". NOT for PostgreSQL-specific query tuning or EXPLAIN analysis (use postgresql-optimization), NoSQL or document database design, or cloud database provisioning.

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Design and safely evolve data models, database schemas, migrations, queries, indexes, and ORM data-access boundaries. Use for data-model, migration, query, index, ORM schema, or datastore-selection tasks. Discover the existing engine and migration source before proposing syntax.

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Generates or updates an index.md to reference all docs in the folder. Use if user requests to create or update an index of all files in a specific folder

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Framework de dados para construir aplicações LLM com RAG. Especializado em ingestão de documentos (300+ conectores), indexação e consultas. Inclui índices vetoriais, mecanismos de consulta, agentes e suporte multimodal. Use para perguntas sobre documentos, chatbots, recuperação de conhecimento ou construção de pipelines RAG. Ideal para aplicações LLM centradas em dados.

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Audit Bing search visibility, Webmaster Tools evidence, and IndexNow readiness when authorized tools are available. Use for Bing indexing, link, crawl, or Microsoft search visibility work; not for Google indexing assumptions.

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Discover and recommend public skills from external registries, and own public-index refresh and scrub requests. Use when creating or importing a skill, finding similar public skills, refreshing the index, or scrubbing it. Maintains PUBLIC_SKILL_REGISTRY.urls and PUBLIC_SKILL_INDEX.yaml; returns up to 5 similar matches with rich summaries and clear next actions.

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Search the Unique AI Platform knowledge base using the unique-cli search command, with automatic per-turn citation tracking so cited facts render as clickable reference chips and `<sup>N</sup>` footnotes on the Unique platform. Use whenever the user asks to find, search, or query documents or content on Unique, including filtering by folder or metadata. Also covers `unique-cli read <cont_id>` for reading the full indexed text of a document when its content ID is already known. NOTE: This search uses combined vector + full-text indexing. Excel (.xlsx/.xls), CSV (.csv), and image files are NOT full-text indexed, so they will not appear in search results. To locate these file types, use the unique-cli-file-management skill instead (browse folders with `unique-cli ls` to find them by name).

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Full SEO audit: Google Search Console data + URL Inspection API + PageSpeed Insights API + technical crawl + keyword research + metadata audit + schema markup audit + search intent analysis + Core Web Vitals monitoring. Feeds real GSC data and PageSpeed metrics into AI to surface quick wins, diagnose traffic drops, find content gaps, identify metadata mismatches, detect schema gaps, monitor page performance, and produce an actionable 30-day plan. Use this skill whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, traffic drops, content gaps, search visibility, technical SEO, meta tags, schema markup, structured data, URL indexing, keyword research, indexing issues, page speed, performance, Core Web Vitals, LCP, INP, CLS, or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "crawl errors", "content strategy", "keyword cannibalization", "search intent", "schema markup", "structured data", "URL inspection", "page speed", "performance score", "core web vitals", "lighthouse", or any organic search question. If in doubt, trigger. This skill handles everything from quick GSC checks to deep technical audits with performance monitoring.

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