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srsubramanian

knowledge-base-search

by srsubramanian

0🍴 0📅 Jan 25, 2026

SKILL.md


id: knowledge_base name: Knowledge Base Search version: 1.0.0 category: knowledge description: Search and retrieve information from the vector knowledge base (RAG)

tool_configs:

  • name: kb_search description: Search the knowledge base for relevant information method: search args:

    • name: query type: string required: true description: The search query to find relevant documents
    • name: top_k type: integer required: false description: Number of results to return (default 5)
    • name: collection type: string required: false description: Filter by collection name requires_skill_loaded: true
  • name: kb_list_documents description: List documents in the knowledge base method: list_documents args:

    • name: collection type: string required: false description: Filter by collection name requires_skill_loaded: true
  • name: kb_list_collections description: List all collections in the knowledge base method: list_collections args: [] requires_skill_loaded: true

  • name: kb_get_stats description: Get knowledge base statistics method: get_stats args: [] requires_skill_loaded: false

resource_configs:

  • name: search_tips description: Tips for effective knowledge base searches content: |

    Search Tips

    • Use specific keywords related to your topic
    • Try different phrasings if initial search doesn't return good results
    • Use collection filters to narrow down results
    • Higher top_k values give more context but may include less relevant results

Knowledge Base Skill

You have access to a vector knowledge base that stores documents and enables semantic search. This knowledge base uses embeddings to find contextually relevant information.

Capabilities

  1. Semantic Search: Search for documents using natural language queries. The search uses vector similarity to find contextually relevant content, not just keyword matching.

  2. Collection Management: Documents can be organized into collections. Use collection filters to narrow your search to specific domains or topics.

  3. Context Retrieval: Retrieve relevant context from documents to help answer user questions. Multiple document chunks may be combined to provide comprehensive information.

When to Use This Skill

Use the knowledge base when:

  • The user asks about specific topics that may be in uploaded documents
  • You need factual information from the user's document collection
  • Looking for specific details, quotes, or data from stored documents
  • The user references documents they've previously uploaded

Search Guidelines

  1. Be Specific: Use clear, focused queries. Instead of "tell me about the project", try "project requirements and timeline".

  2. Iterate: If initial results aren't helpful, rephrase your query or try different keywords.

  3. Use Context: Combine multiple search results to build a comprehensive answer.

  4. Cite Sources: When using information from search results, mention the source document.

Example Workflows

Finding Specific Information

  1. Call kb_search with a targeted query
  2. Review the returned chunks for relevant information
  3. If needed, search again with refined query
  4. Synthesize information from multiple results

Exploring Available Documents

  1. Call kb_list_collections to see what's available
  2. Call kb_list_documents to see specific files
  3. Search within relevant collections for specific content

Checking System Status

  1. Call kb_get_stats to verify the knowledge base is available
  2. Check document and chunk counts to understand the knowledge base size

Score

Total Score

50/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

0/10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

0/15
最近の活動

3ヶ月以内に更新がある

0/10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

0/5

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