Diogenes plugin marketplace for the deterministic AI research methodology.
npx claudepluginhub diogenes-project/diogenesDiogenes — deterministic AI research methodology combining ICD 203, GRADE, PRISMA, Cochrane, and five other frameworks into an evidence-based process. Anti-sycophantic by design.
A unified research methodology for AI agents combining nine intelligence and scientific frameworks into an 11-step evidence-based process. Available as a Claude Code plugin or as a standalone prompt for any AI interface (Claude, ChatGPT, Gemini, or any capable LLM).
A structured research methodology that makes AI agents produce defensible, auditable, evidence-based research. It combines frameworks from intelligence analysis (ICD 203), clinical medicine (GRADE, Cochrane, CONSORT), climate science (IPCC), systematic review methodology (PRISMA, ROBIS), institutional standards (NAS), and the philosophy of science (Chamberlin/Platt).
The methodology was developed to solve a specific problem: AI agents, when asked to "research this," default to building a case rather than conducting an investigation. They confirm what you expect, minimize contradictions, and present uncertain conclusions as settled. This methodology constrains that behavior through enforcement language — telling the AI not just what to do, but what it is prohibited from doing and why.
The detailed background behind this methodology — the framework evaluation, the design decisions, and the evidence for every feature — is discussed in a pair of articles:
All three can be combined in a single research run using /research run.
Research produces complete evidence archives: source scorecards, search logs, hypothesis evaluations, collection-level synthesis, gap identification, and a five-domain self-audit.
From within a Claude Code session, run these two commands:
# Add the marketplace (one-time setup)
/plugin marketplace add wphillipmoore/ai-research-methodology
# Install the plugin
/plugin install ai-research-methodology@ai-research-methodology
The first command registers the marketplace. The second installs the plugin.
After installation, the /research skill is available in all sessions.
Verify the install: run /plugin, go to the Installed tab, and
confirm ai-research-methodology appears with the expected version.
Documentation: Discover and install plugins, Plugin marketplaces
From within a Claude Code session:
# Refresh the marketplace to pick up new versions
/plugin marketplace update ai-research-methodology
# Then update the plugin
# Option A: use the interactive UI
/plugin
# Go to Installed tab → select the plugin → Update
# Option B: from the shell (outside a session)
claude plugin update ai-research-methodology@ai-research-methodology
After updating, run /reload-plugins to activate the new version in your
current session.
Documentation: Configure auto-updates, CLI commands
Note: Auto-updates are disabled by default for third-party marketplaces.
To enable them, go to /plugin → Marketplaces tab and configure
auto-update for this marketplace.
Copy the contents of
ai-research-methodology/standalone/research.md
and paste it into any AI conversation — Claude, ChatGPT, Gemini, or any
capable LLM. Then provide your claims, queries, and/or axioms. The prompt
includes both the research methodology and the output format. It was
developed and tested with Claude but uses no Claude-specific features.
# Run research from a file (claims, queries, axioms, or any combination)
/research run file=claims.md output=research/ai-trust
# Run research interactively
/research run
# Re-run previous research (isolation enforced — no access to prior results)
/research rerun research/ai-trust
RuFlo Marketplace: Claude Code native agents, swarms, workers, and MCP tools for continuous software engineering
No description available.
Code intelligence powered by a knowledge graph — execution flows, blast radius, and semantic search