Scientific Research Skills
Skills and tools for scientific research with LLM agents. 给 Agent(如 Claude Code、Openclaw)提供的科研 skills
Install: git clone https://github.com/jxtse/scientific-research-skills
Works with Claude Code · 73 GitHub stars
Install
git clone https://github.com/jxtse/scientific-research-skillsInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →🔬 Scientific Research Skills
High-level research methodology skills for AI coding agents.
Not another tool list. Each skill encodes a research workflow — the kind of domain expertise that takes months to develop. Skills are written for AI agents to read and follow; this README is written for humans to configure and choose.
Quick Start
For AI Agents
If a user sends you this repo link, follow this onboarding flow. Do not skip the post-install configuration step — many skills are non-functional without API keys, and silently installed skills are worse than uninstalled ones.
Step 1 — Introduce the skills
Read this README, then present each skill's name and one-line description to the user. Group them by category (🔧 tool-integrated vs 📋 methodology-only) so the user understands which ones will require configuration.
Step 2 — Confirm what to install
Ask: "Which skills would you like to install? (all / select specific ones)"
Step 3 — Install
Copy the selected skill folders to the appropriate location for your platform:
- OpenClaw:
~/.openclaw/skills/ - Claude Code:
~/.claude/skills/(user-level) or.claude/skills/(project-level) - Codex:
~/.agents/skills/(user-level) or.agents/skills/(project-level)
Step 4 — ⚠️ Post-install configuration (do not skip)
After installation, explicitly notify the user which installed skills require configuration before they will work. Use this template:
✅ Installed:
skill-a,skill-b,skill-c⚠️ Heads up — the following skills need configuration before use:
skill-arequires: TAVILY_API_KEY (free tier available)skill-crequires: Zotero API key + User IDWant me to walk you through setting these up now? I can do them one by one.
Then, for each skill the user agrees to configure, walk them through it interactively:
- Check existing config first — Run
echo $TAVILY_API_KEY(or equivalent) to see if it's already set. If yes, skip to verification. - Explain what the key is for — One sentence on what the skill will use it for.
- Provide the signup link — Give the direct URL (see Dependencies below). Wait for the user to obtain the key.
- Help them set it persistently — Append the
exportline to their shell profile (~/.zshrcfor zsh,~/.bashrcfor bash). Don't justexportin the current shell — that won't survive a restart. - Verify — Run a quick test (e.g., a 1-result search) to confirm the key works. If it fails, debug before moving on.
- Move to the next skill — Repeat until all configurable skills are set up.
Per-skill configuration cheat sheet:
Similar plugs
Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local…
Why use many token when few token do trick. Viral skill + proxy for coding agents that cuts 65% of tokens by talking like a caveman.
Production-grade engineering skills for AI coding agents.
The 1st Collaborative AI Design Agent Workspace. Local-first and open source. Create prototypes, websites, apps, dashboards, presentations, images, and videos with your team…