{"repo":"Anjos2/recursive-research","free":true,"listed":false,"github":"https://github.com/Anjos2/recursive-research","clone":"git clone https://github.com/Anjos2/recursive-research.git","description":"Claude Code skill for recursive research up to PhD level across any domain. Source tiering, WDM + Munger inversion for autonomous decisions, and disk checkpointing to survive context compaction.","language":null,"stars":39,"topics":["ai-agent","claude-code","claude-code-skill","knowledge-management","mental-models","research-tool","recursive-research","weighted-decision-matrix"],"license":"MIT","category":"ai-agents","readme_excerpt":"recursive-research Claude Code plugin & skill for recursive research up to PhD level on any topic — science, tech, business, arts, humanities. Source tiering, loop auto-regulation, disk checkpointing, and WDM + Munger inversion for autonomous decisions. Version: 2.2.0 · License: MIT · Author: Joseph Huayhualla (@Anjos2) --- What it does You give it a research seed (a topic) and the skill: 1. Asks for mode ( web / local / mixed ), local paths if applicable, priority/excluded sources, and a cycle cap. 2. Identifies 3-5 seed threads applying WDM (Weighted Decision Matrix) + Munger Inversion. 3. Detects available MCPs (Firecrawl, Context7, WebFetch, WebSearch) and prioritizes by speed and quality. 4. Iterates in auto-regulated cycles — each cycle picks the least-covered thread, selects sources, investigates, consolidates. 5. Tiers every source into Tier 1 / 2 / 3 / Rejected with transparent criteria. 6. Saves disk checkpoints every cycle — survives context compaction. 7. Closes when the 5-criteria PhD fitness function is met, or upon hitting the cycle cap. 8. Asks if you want to keep going. Research can be infinite. --- Why it's different Feature How it solves it --- --- Works across any domain Generic source tiering (papers, academic books, official archives, raw data), not code-only Rejects garbage sources automatically Explicit criteria: no author, data-less marketing, SEO spam, unsupervised AI content Survives context limits Per-cycle disk checkpoint + --resume mode for new s","default_branch":null,"files":null,"tree":[],"storefront":"/r/Anjos2","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Anjos2/recursive-research/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}