knowledge-retrieval
Knowledge-Retrieval performs semantic search across pre-ingested documents using retrieval-augmented generation technology powered by LlamaIndex with ChromaDB or NVIDIA Foundational RAG. Use this skill to find specific information within internal PDFs, technical documentation, whitepapers, and domain-specific reports that aren't available through web searches, prioritizing it as the primary information source before conducting external searches.
git clone --depth 1 https://github.com/open-gitagent/opengap /tmp/knowledge-retrieval && cp -r /tmp/knowledge-retrieval/examples/nvidia-deep-researcher/skills/knowledge-retrieval ~/.claude/skills/knowledge-retrievalSKILL.md
# Knowledge Retrieval Perform semantic search over a pre-ingested document collection using Retrieval-Augmented Generation (RAG). Backed by LlamaIndex with ChromaDB or NVIDIA Foundational RAG. ## When to Use - Searching internal or pre-ingested documents and reports - Finding information in PDFs, whitepapers, or technical documentation - Retrieving domain-specific knowledge not available on the open web - This is the **highest priority** source — check the knowledge base first before web or paper searches ## How to Use 1. Formulate a semantic search query describing the information needed 2. Call `knowledge_retrieval` with the query 3. Review returned chunks for relevance 4. Note the citation metadata (filename, page number) for sourcing ## Result Format Results are returned as text chunks with citation metadata: ``` Relevant text passage from the ingested document... Citation: filename.pdf, p.12 ``` ## Constraints - Searches only over documents that have been ingested into the knowledge index - Returns ranked chunks based on semantic similarity - Citation format: `Citation: filename.ext, p.X` - Each call counts toward the researcher's 8-call limit per task ## Backend Options - **LlamaIndex + ChromaDB** — Local vector store with LlamaIndex orchestration - **NVIDIA Foundational RAG** — NVIDIA-hosted RAG service with NeMo Retriever
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Configures and runs agents with different adapters including Claude, OpenAI, CrewAI, Lyzr, and GitHub Models. Supports local execution, remote git repos, and one-shot prompts. Use when the user wants to run an agent, switch LLM providers, configure adapter settings, or launch agents from git repositories.
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