skills/smithery.ai/context-engine

context-engine

SKILL.md

Context-Engine

Search and retrieve code context from any codebase using hybrid vector search (semantic + lexical) with neural reranking.

Client- or provider-specific wrapper files should stay thin and defer to this document for shared MCP tool-selection and search guidance.

Quickstart

  1. Start with search for most codebase questions.
  2. Use symbol_graph first for direct symbol relationships such as callers, definitions, importers, subclasses, and base classes.
  3. Use graph_query only if that tool is available and you need transitive impact, dependency, or cycle analysis; otherwise combine symbol_graph with targeted search.
  4. Prefer MCP tools for exploration. Narrow grep/file-open use is still fine for exact literal confirmation, exact file/path confirmation, or opening a file you already identified for editing.
  5. Use cross_repo_search for multi-repo questions. For public V1 context_search, treat include_memories=true as compatibility-only: it preserves response shape but keeps results code-only and may add memory_note.

Decision Tree: Choosing the Right Tool

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Mar 25, 2026