Analyze a code snippet for quality issues and semantic drift

AgentPMT Tool Search and Execution - Unified interface for discovering, searching, and using AgentPMT tools without MCP refresh. Access tools required for workflows and skills here.

Search TED notices using semantic vector search. Best for conceptual queries and finding related tenders. Args: query: The search query (natural language) limit: Maximum number of results (default: 10) country: Filter by country code (optional) Returns: Search results ranked by semantic similarity

Perform semantic search using vector embeddings with FAISS acceleration for better conceptual matching.

Find tracks similar to a given track using Tonr's semantic embeddings.

Search saved contexts by keyword or natural language query. Returns matching context summaries ranked by relevance using hybrid keyword + semantic search. Searches across titles, reasoning, code snippets, file paths, and commit SHAs. Results include local contexts and (if authenticated) cloud workspace contexts including team-shared contexts. Use for finding past decisions, understanding why code was written, or discovering relevant prior work. Use gitwhy_get <context_id> to read the full context. CLI alternative: `git why search "<query>"`.