recursive-research
Recursive research up to PhD level across any domain (science, tech, business, arts, humanities). Source tiering (Tier 1/2/3/rejected), WDM
Open source Repository Open in the app JSON README (API)
About
Recursive research up to PhD level across any domain (science, tech, business, arts, humanities). Source tiering (Tier 1/2/3/rejected), WDM + Munger inversion for autonomous decisions, and disk checkpointing to survive context compaction. Works with web sources, local files, or mixed mode — interactive setup asks for seed, priority/excluded sources, and cycle cap before starting.
Details
- Kind
- Plugins
- Topic
- Files & documents
- Publisher
- anjos2
- Origin
- marketplace
- Category
- ferramentas
- Stars
- 43
- Forks
- 1
- Last push
- 2026-04-22T23:57:39Z
- Repository state
- ativo
- License
- MIT
- Added
- 2026-08-30 01:48:58
- Updated
- 2026-08-30 01:48:58
- Origin id
anjos2/recursive-research/recursive-research
README
# 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](LICENSE) · **Author:** Joseph Huayhualla ([@Anjos2](https://github.com/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](#wdm--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 sessions | | **Self-critical** | Munger inversion applied to the consolidated knowledge: what do I not know? what bias do my sources share? what's missing? | | **Asks before assuming** | Full Phase 0 interrogation of the user | | **Transparent** | Every non-trivial autonomous decision runs WDM + Munger and shows the reasoning | --- ## Installation This repo is a **Claude Code marketplace** containing one plugin (`recursive-research`). The easiest way to install is through Claude Code's built-in plugin manager. ### Option A — Via marketplace (recommended) Inside Claude Code, run: ``` /plugin marketplace add Anjos2/recursive-research /plugin install recursive-research ``` The plugin appears in `/plugin` → Installed. Invoke it with `/recursive-research:recursive-research`. ### Option B — Via the official Plugin Directory (pending approval) Anthropic maintains a [central Plugin Directory](https://claude.com/plugins). Once approved there (submission in progress), install becomes a one-liner without the marketplace add step: ``` /plugin install recursive-research ``` ### Option C — As a standalone skill (minimal, no plugin manager) If you prefer to bypass the plugin ecosystem, copy only the skill markdown: **Linux / macOS:** ```bash git clone https://github.com/Anjos2/recursive-research.git mkdir -p ~/.claude/skills/recursive-research cp recursive-research/plugins/recursive-research/skills/recursive-research/SKILL.md ~/.claude/skills/recursive-research/ ``` **Windows (PowerShell):** ```powershell git clone https://github.com/Anjos2/recursive-research.git New-Item -ItemType Directory -Force -Path "$HOME/.claude/skills/recursive-research" Copy-Item recursive-research/plugins/recursive-research/skills/recursive-research/SKILL.md "$HOME/.claude/skills/recursive-research/" ``` Invoked without namespace as `/recursive-research`. Verify with `/help` inside Claude Code. --- ## Usage ### Standard invocation ``` /recursive-research:recursive-research # if installed as plugin /recursive-research # if installed as standalone skill ``` The skill guides you interactively. Answer in natural language. ### Resume a paused research ``` /recursive-research:recursive-research --resume <slug> ``` `<slug>` = kebab-case name of the topic (e.g., `episodic-memory-humans`). ### List saved research ``` /recursive-research:recursive-research --list ``` --- ## Usage examples by domain | Domain | Suggested seed | |---------|------------------| | Neuroscience | "Mechanisms of episodic memory in humans" | | Philosophy | "Modern application of Stoic philosophy" | | Music | "Minimalism in 20th-century music" | | Business | "B2B SaaS monetization models in 2025" | | History | "Fall of the Western Roman Empire: economic causes" | | Biology | "CAR-T cell immunotherapy against cancer" | | Technology | "Hexagonal architecture in microservices" | | Law | "European AI Act and its extraterritorial impact" | --- ## "PhD level" criterion The skill only declares PhD when **all 5 criteria** are met: 1. **Coverage ≥80%** across all seed threads 2. **≥3 Tier-1 sources per thread** 3. **New-finding saturation ≤5%** for 3 consecutive cycles 4. **Munger inversion applied** to the knowledge (what I don't know, what sources contradict, what biases exist) 5. **≥3 explicit cross-thread connections** between different threads If any criterion fails, it **does not declare PhD** and keeps iterating — or asks for confirmation upon hitting the cycle cap (default 20, configurable). --- ## Source tiering | Tier | Qualifies | WDM weight | |------|-----------|------------| | **1** | Peer-reviewed papers · academic books · official standards (W3C, RFC, ISO, WHO) · primary archives · official datasets | 5 | | **2** | Official repos · blogs from citable authors · recorded conferences · Wikipedia with references · reports with methodology | 3 | | **3** | Blogs with citations to T1/T2 · high-voted forum answers with sources · recorded interviews with identifiable experts | 2 | | **Reject** | No author · data-less marketing · SEO spam · tutorials without sources · unsupervised AI content | 0 | Every consulted source is logged in a per-tier file for later audit. --- ## Pre-loaded seed sources The skill auto-suggests reliable sources by domain. Examples: - **Science**: arXiv, Semantic Scholar, Google Scholar, Connected Papers, OpenReview - **Medicine**: PubMed, Cochrane Library, WHO, ClinicalTrials.gov - **Humanities**: JSTOR, SSRN, Project MUSE - **Code**: GitHub, Context7, RFCs, W3C specs - **Data**: World Bank, OECD Data, Our World in Data, Pew Research - **Art/culture**: Europeana, Google Arts & Culture, Internet Archive, Project Gutenberg The user can add or reject any before starting. --- ## WDM + Munger inversion Decision frameworks applied at each non-trivial autonomous step: - **WDM (Weighted Decision Matrix)** — enumerate 3+ viable alternatives, criteria with weights, 1-5 scoring, compared totals. - **Munger inversion** (Charlie Munger via Jacobi) — ask inverted about the winning option: *"how would it fail? what bias does it have? what am I ignoring?"* The skill applies both to: - Select seed threads - Select sources per cycle - Decide when to close the research - Validate the consolidated knowledge at the end Reference: [Charlie Munger's essay on mental inversion](https://fs.blog/inversion/). --- ## Recommended MCPs The skill detects what you have and uses them in this order: 1. **[Firecrawl MCP](https://github.com/mendableai/firecrawl-mcp-server)** (highly recommended) — AI-optimized scraping 2. **[Context7 MCP](https://github.com/upstash/context7)** — official library docs 3. **WebSearch + WebFetch** (built-in Claude Code) — universal fallback 4. **Chrome DevTools MCP** — only when content requires real JS execution; generally **too slow** for large-scale research --- ## Generated files In `memoria/investigaciones/<slug>/` of the active project: - `estado.md` · `hilos.md` · `hallazgos.md` - `fuentes-tier-1.md` · `fuentes-tier-2.md` · `fuentes-tier-3.md` · `fuentes-rechazadas.md` - `ciclo-01.md`, `ciclo-02.md`, ..., `ciclo-N.md` (checkpoints) - `sintesis.md` · `acciones.md` · `gaps.md` (upon closing) **If `memoria/` doesn't exist in the project, the skill creates it** (notifying the user) — it's an explicit dependency. --- ## Repository structure ``` recursive-research/ ← the repo is a Claude Code marketplace ├── .claude-plugin/ │ └── marketplace.json ← marketplace manifest (declares the plugin) ├── plugins/ │ └── recursive-research/ ← the plugin (named same as the marketplace) │ ├── .claude-plugin/ │ │ └── plugin.json ← plugin manifest │ └── skills/ │ └── recursive-research/ │ └── SKILL.md ← the skill instructions (the actual content) ├── LICENSE ← MIT ├── README.md ← this file ├── PRIVACY.md ← privacy policy (no data collection) └── .gitignore ``` --- ## Contributing Issues and PRs welcome. If you improve a criterion, add a tier, find a new anti-pattern, or want support for more domains: open a PR. ### Roadmap - [ ] Native integration with reference managers (Zotero, Mendeley) - [ ] Export research to academic formats (LaTeX, BibTeX) - [ ] Collaborative mode — multiple agents investigating threads in parallel - [ ] Automatic source-quality metrics (h-index, journal impact factor) - [ ] Support for PDFs behind legal paywalls --- ## GitHub topics `claude-code` · `claude-code-skill` · `claude-code-plugin` · `ai-agent` · `research-tool` · `recursive-research` · `knowledge-management` · `weighted-decision-matrix` · `mental-models` --- ## Privacy `recursive-research` does not collect any user data. Everything runs locally on your machine. See [PRIVACY.md](PRIVACY.md) for the full policy. ## License [MIT](LICENSE) — use, modify, distribute freely. Just keep the copyright notice. --- ## Acknowledgments - **Charlie Munger** — for "Invert, always invert" (via Carl Jacobi) - **Claude Code team** — for the skill and plugin format - **Anthropic** — for the model that makes this possible If this skill was useful, consider giving the repo a ⭐.