AI Research Skills：组织可核验的研究流程

Universal SKILL.md catalog for research workflows: literature review, research design, project memory, manuscript writing, and cross-agen…

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). 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 Read-only and reversible steps can continue automatically. Breaking contracts, skill removal, external writes, semantic acceptance, and release authorization remain explicit human decisions. If you are… Best next page A researcher or research team Follow the eight-stage pipeline after the quick install above. An agent or harness builder Read the architecture, state, HITL, recovery, and evaluation guide. Evaluating portability or trust boundaries Review compatibility, the runtime contract, and limitations. Contents Install — get the skills Why this catalog exists The pipeline — what each stage delivers to the next Use it See what each skill produces FAQ Compatibility Limitations 1. Install — get the skills The core asset is portable SKILL.md; Claude Code marketplace support is the convenience layer. Use the path that matches your host: Host Path Claude Code Marketplace install below; gets auto-triggering and claude plugin list verification. Codex CLI / Cursor / Windsurf Load the canonical repo's SKILL.md into the host's skills/rules directory, or inline it into the prompt. Gemini CLI / generic API client Inline SKILL.md as prompt or system context. Hermes Install a raw SKILL.md; this repo has Hermes 0.13.0 skill-load verification for literature-triage-matrix. OpenClaw Use a SKILL.md directory shape such as ~/.openclaw/skills/<skill>/SKILL.md when supported; not release-verified here yet. Full per-host recipes are in docs/install.md → Using these skills outside Claude Code. Claude Code fastest path — 30 seconds: claude plugin marketplace add WenyuChiou/ai-research-skills claude plugin install research-workspace@ai-research-skills Windows cmd.exe: run the commands one at a time. If the plugin list does not show research-workspace@ai-research-skills, your paste probably only executed the first line; see docs/install.md for the single-line CMD form. For Claude Code, the first two commands install the 12-skill research-workspace plugin. Add the optional plugins only when you need manuscript writing, full Zotero operations, or Claude-to-Codex/Antigravity delegation. Additive install — stop after any step and use what you have: # 1. Marketplace + 12 research-hub skills claude plugin marketplace add WenyuChiou/ai-research-skills claude plugin install research-workspace@ai-research-skills # 2. Manuscript work — outline, drafting, prose and evidence audit, scientific review (14/17) claude plugin install academic-writing-skills@ai-research-skills # 3. Zotero CRUD (15/17; enable local API in Zotero desktop first — docs/setup-guide.md §C) claude plugin install zotero-skills@ai-research-skills # 4. Multi-CLI delegation (17/17; install codex / agy CLI binaries first) claude plugin install codex-delegate@ai-research-skills claude plugin install antigravity-delegate@ai-research-skills # 5. Literature pipeline automation (Python CLI behind research-hub skills) pip install research-hub-pipeline research-hub setup --persona researcher research-hub doctor Separate live smoke (not installation): This is a live literature workflow, not an offline install check. --no-nlm disables NotebookLM only; it does not disable other network calls, models, or writes. Complete the live-run preflight and obtain the