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Found 253 Skills
How to work in an OKF starter project (the `okf` starter pack): a knowledge base that is conformant with Google's Open Knowledge Format (OKF) from commit one — `concepts/`, `references/`, `notes/`, a reserved `index.md` navigation hub, and a reserved `log.md` change history. Read when the project has these folders plus reserved files, OR when asked whether a document is OKF-conformant, or to add a document to an OKF knowledge base. Carries the OKF conventions (non-empty `type` on every non-reserved doc; reserved files carry no frontmatter) as guidance, not enforcement. Complements the platform `open-knowledge` skill; does not replace it.
Knowledge Base RAG implements the complete Retrieval-Augmented Generation pipeline: document ingestion, intelligent chunking, embedding generation, vector store indexing, semantic retrieval, and grounded response generation.
Dify dataset retrieve API for knowledge base chunk search/testing. Use when integrating or debugging Dify knowledge base retrieval requests, retrieval_model options, or response shaping.
Create or update docs/knowledge-base/ chapters in mdbook format for human-first technical documentation.
Shared foundation for Oracle & Corrector agents. Establishes the source hierarchy for resolving conflicts between documentation, code, and specs. Load this skill first when investigating how the system works.
AI-first knowledge base and startup OS with file-based storage, AI agents, scheduled jobs, and embedded apps
FAQ identification from support tickets, step-by-step tutorial creation, screenshot/video script guidance, search optimization, and self-service deflection tracking.
AI-native open knowledge base about Taiwan built with Astro v5, featuring bilingual content (zh-TW/en), D3.js knowledge graph, and structured Markdown SSOT architecture.
Use this skill when designing help center architecture, writing support articles, or optimizing search and self-service. Triggers on knowledge base, help center, support articles, self-service, article templates, search optimization, content taxonomy, and any task requiring help documentation design or management.
Build a knowledge base from web content with Firecrawl. Use for local reference docs, RAG-ready chunks, fine-tuning datasets, documentation mirrors, topic corpora, or LLM-ready markdown organized from web sources.
Amazon Bedrock Knowledge Bases for RAG (Retrieval-Augmented Generation). Create knowledge bases with vector stores, ingest data from S3/web/Confluence/SharePoint, configure chunking strategies, query with retrieve and generate APIs, manage sessions. Use when building RAG applications, implementing semantic search, creating document Q&A systems, integrating knowledge bases with agents, optimizing chunking for accuracy, or querying enterprise knowledge.
How to work in a Knowledge Base project (the `knowledge-base` starter pack). Read when the project has the three-layer source-grounded layout — `external-sources/` → `research/` → `articles/` — or when asked how this project is organized. Carries the layer model, per-folder rules, status flows, and log discipline so this guidance does NOT live inside template bodies or log.md. The three procedures live elsewhere: ingest in the platform `open-knowledge` skill, research and consolidate as their own sibling skills in this pack. Complements the platform `open-knowledge` skill; does not replace it.