AI Research Skills

The catalog, installation, and visual layer for a Vertical AI Research Reference Harness. Move from research orientation to release through 17 portable skills, an eight-stage lifecycle, evidence-aware handoffs, and explicit human gates.

Built for graduate students, PhDs, postdocs, research support staff, and agent/harness builders who need inspectable research workflows rather than a black box. The portable skills live in this repository; research-hub supplies the executable runtime, while the optional agent-collab-harness adds policy/checkpoint governance.

Languages: English | 繁中 · Pipeline · Examples · Runtime contract · Glossary · For Agent/Harness Builders

📚 Part of the agentic AI learning roadmap — featured in §13–14 (research workflows).

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Start here — Why, what, and how

See the whole research lifecycle first

The 17-skill core is organized around durable handoffs: each stage produces the next stage's input, while cross-cutting tools preserve context, verification, and delegation boundaries.

Your first question	Short answer	Go deeper
Why use these skills?	Keep research context durable, verify evidence before claims move downstream, and pause automation at meaningful human decisions.	Problems this catalog solves
What is included?	17 portable skills, 8 lifecycle stages, 5 installable plugins, an executable research runtime, and an optional policy/checkpoint harness.	Skill outputs
How do I use it?	Install the 12-skill research workspace, then ask for a concrete research outcome in natural language. Add writing, Zotero, or delegation plugins only when needed.	30-second install · Usage patterns

17 core skills	8 research stages	5 optional-by-need plugins	3 truth-store integrations
Portable SKILL.md contracts	Orientation → release	Start with 1; grow to 5	Zotero · Obsidian · NotebookLM

Try the smallest useful path

claude plugin marketplace add WenyuChiou/ai-research-skills
claude plugin install research-workspace@ai-research-skills

Then ask, for example:

Build a literature triage matrix for human-in-the-loop research agents. Verify identifiers, preserve contradictions, and show me the evidence gaps before recommending next steps.

Need an executable, resumable workflow instead of prompt-only skills? Continue with pip install research-hub-pipeline, then run research-hub setup and research-hub doctor. The full path is in Install.

Understand the two control layers

Harness architecture — deterministic control around semantic work

research-hub owns the research-domain runtime and recoverable state. Role agents do semantic work; deterministic validators, evidence contracts, and the optional agent-collab-harness policy/checkpoint layer control what may proceed.

Human-in-the-loop — where automation must pause