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)
You give it a research seed (a topic) and the skill:
- Asks for mode (
web/local/mixed), local paths if applicable, priority/excluded sources, and a cycle cap. - Identifies 3-5 seed threads applying WDM (Weighted Decision Matrix) + Munger Inversion.
- Detects available MCPs (Firecrawl, Context7, WebFetch, WebSearch) and prioritizes by speed and quality.
- Iterates in auto-regulated cycles — each cycle picks the least-covered thread, selects sources, investigates, consolidates.
- Tiers every source into Tier 1 / 2 / 3 / Rejected with transparent criteria.
- Saves disk checkpoints every cycle — survives context compaction.
- Closes when the 5-criteria PhD fitness function is met, or upon hitting the cycle cap.
- Asks if you want to keep going. Research can be infinite.
| 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 |
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.
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.
Anthropic maintains a central Plugin Directory. Once approved there (submission in progress), install becomes a one-liner without the marketplace add step:
/plugin install recursive-research
If you prefer to bypass the plugin ecosystem, copy only the skill markdown:
Linux / macOS:
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):
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.
/recursive-research:recursive-research # if installed as plugin
/recursive-research # if installed as standalone skill
The skill guides you interactively. Answer in natural language.
/recursive-research:recursive-research --resume <slug>
<slug> = kebab-case name of the topic (e.g., episodic-memory-humans).
/recursive-research:recursive-research --list
| 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" |
The skill only declares PhD when all 5 criteria are met:
- Coverage ≥80% across all seed threads
- ≥3 Tier-1 sources per thread
- New-finding saturation ≤5% for 3 consecutive cycles
- Munger inversion applied to the knowledge (what I don't know, what sources contradict, what biases exist)
- ≥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).
| 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.
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.
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.
The skill detects what you have and uses them in this order:
- Firecrawl MCP (highly recommended) — AI-optimized scraping
- Context7 MCP — official library docs
- WebSearch + WebFetch (built-in Claude Code) — universal fallback
- Chrome DevTools MCP — only when content requires real JS execution; generally too slow for large-scale research
In memoria/investigaciones/<slug>/ of the active project:
estado.md·hilos.md·hallazgos.mdfuentes-tier-1.md·fuentes-tier-2.md·fuentes-tier-3.md·fuentes-rechazadas.mdciclo-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.
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
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.
- 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
claude-code · claude-code-skill · claude-code-plugin · ai-agent · research-tool · recursive-research · knowledge-management · weighted-decision-matrix · mental-models
recursive-research does not collect any user data. Everything runs locally on your machine. See PRIVACY.md for the full policy.
MIT — use, modify, distribute freely. Just keep the copyright notice.
- 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 ⭐.