Iteratively search, evaluate, and refine file retrieval for subagent context.
npx skills add https://github.com/flatrick/mdt --skill iterative-retrieval-flatrick
Please help me install this Agent Skill. Skill: iterative-retrieval Source: https://github.com/flatrick/mdt/tree/main/skills/iterative-retrieval Command: npx skills add https://github.com/flatrick/mdt --skill iterative-retrieval-flatrick
This Skill addresses the challenge where subagents lack the precise context needed to perform their tasks, preventing them from knowing which files or information are relevant upfront.
Use the iterative-retrieval skill to find files related to 'user authentication' in the codebase.
High-intent search queries and answers about installing and using this skill.
Improving context retrieval for subagents requires an iterative process that dynamically searches, evaluates, and refines files based on task relevance. This approach progressively builds optimal context without upfront knowledge of relevant code.
Iterative retrieval in RAG pipelines is a pattern that progressively refines context by searching and evaluating files to identify gaps. It optimizes token usage by focusing exclusively on high-relevance code for the specific task.
To avoid overwhelming an agent during complex debugging, implement an iterative retrieval pattern that intelligently discovers and retrieves only the most relevant files. It dynamically filters information based on identified task relevance and context gaps.
Yes, progressive context refinement is specifically designed for unpredictable agentic workflows. It handles evolving context requirements by dynamically searching and evaluating file retrieval during execution to supply precise information.
Yes, iterative file retrieval works precisely because it solves the problem of not knowing relevant files upfront. It dynamically evaluates and refines context retrieval based on task relevance and identified information gaps.
lvlup-swCreate isolated git worktrees in gitignored directories for parallel tasks.
andrew-starosciakRefine subagent context through a four-stage iterative retrieval loop.
robertbr123Build and manage vector databases for RAG and semantic search with Qdrant.
Ced3-hanAutomate iterative context retrieval for multi-agent workflows.
