Astropy
zLanqing/codex-claude-academic-skills
Comprehensive Python library for astronomy and astrophysics.
Applies the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford University, flexible electronics).
Install Zhenan Bao
$ npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install K-Dense-AI/mimeographs zhenan-bao --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/K-Dense-AI/mimeographs.git skills-src && mkdir -p .claude/skills && cp -r skills-src/mimeographs/zhenan-bao .claude/skills/zhenan-bao && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "zhenan-bao" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/zhenan-bao into .claude/skills/zhenan-bao/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zhenan-bao", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/zhenan-baoType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install K-Dense-AI/mimeographs zhenan-bao --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/mimeographs.git skills-src && mkdir -p .agents/skills && cp -r skills-src/mimeographs/zhenan-bao .agents/skills/zhenan-bao && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "zhenan-bao" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/zhenan-bao into .agents/skills/zhenan-bao/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zhenan-bao", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install K-Dense-AI/mimeographs zhenan-bao --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/mimeographs.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/mimeographs/zhenan-bao .cursor/skills/zhenan-bao && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "zhenan-bao" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/zhenan-bao into .cursor/skills/zhenan-bao/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zhenan-bao", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/K-Dense-AI/mimeographs.git --path mimeographs/zhenan-bao--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install K-Dense-AI/mimeographs zhenan-bao --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/mimeographs.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/mimeographs/zhenan-bao .gemini/skills/zhenan-bao && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "zhenan-bao" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/zhenan-bao into .gemini/skills/zhenan-bao/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zhenan-bao", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install K-Dense-AI/mimeographs zhenan-baoInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/K-Dense-AI/mimeographs.git skills-src && mkdir -p .github/skills && cp -r skills-src/mimeographs/zhenan-bao .github/skills/zhenan-bao && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "zhenan-bao" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/zhenan-bao into .github/skills/zhenan-bao/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zhenan-bao", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install K-Dense-AI/mimeographs zhenan-bao --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/mimeographs.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/mimeographs/zhenan-bao .opencode/skills/zhenan-bao && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "zhenan-bao" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/zhenan-bao into .opencode/skills/zhenan-bao/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "zhenan-bao", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
zhenan-bao- GitHub stars
- 129
- Token cost
- ~1.7k tokens
- SKILL.md length
- 794 words
- Files
- 72 (incl. references)
- Skills in repo
- 60
- Repo updated
- First seen
- Licence
- MIT
At a glance
Applies the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford University, flexible electronics).
- Works in 4 steps: Identify a biological system with the… → Define the specific macroscopic… → Design molecular structures that… → …
- You are advising on hardware innovation
- SKILL.md covers Core principles, How Zhenan Bao reasons, Applying the frameworks and Anti-patterns they push against, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Zhenan Bao is an agent skill from K-Dense-AI/mimeographs. Applies the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford University, flexible electronics). Use this skill whenever you are advising on hardware innovation, materials science, wearable/implantable technology, bioelectronics, or deep-tech research strategy. Trigger this when users face engineering bottlenecks requiring biological inspiration, trade-offs between mechanical and electronic performance, scaling lab fabrication to commercial manufacturing…
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 74 other files, including reference files (for example `AGENTS.md`, `_workspace/agents_output.e584bd6c.json` and `_workspace/clustered_corpus.e584bd6c.json`).
It sits in Research & Science, covering Physical and earth sciences. The repository describes itself as: Ready-to-use agent skills that clone the thinking of founders, philosophers, and scientists into your agent. Generated with K-Dense-AI/mimeo. The licence is MIT.
When your agent uses it
- You are advising on hardware innovation
- Materials science
- Wearable/implantable technology
- Deep-tech research strategy
Example prompts
- “Use the zhenan-bao skill to apply the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford…”
- “/zhenan-bao”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Identify a biological system with the desired properties (e.g., human skin).
- Define the specific macroscopic properties to mimic (stretchability, biodegradability, self-healing).
- Design molecular structures that replicate these properties without losing electronic function.
- Ensure the system's output signals match biological receptors.
What it can do on your machine
Read from SKILL.md and the folder at commit a38f5fc. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Zhenan Bao loads about 1.7k tokens when it runs, and up to ~7.2k if it reads all its reference files. Until then it costs about 169 tokens; SKILL.md has 794 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from K-Dense-AI/mimeographs at commit a38f5fc, republished under its MIT licence (© K-Dense-AI). 794 words, ~1,721 tokens.
Download SKILL.mdSave it as
.claude/skills/zhenan-bao/SKILL.md (or your agent's skills folder). This skill also uses 71 other files; get the full folder from GitHub.- name
- zhenan-bao
- description
- Applies the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford University, flexible electronics). Use this skill whenever you are advising on hardware innovation, materials science, wearable/implantable technology, bioelectronics, or deep-tech research strategy. Trigger this when users face engineering bottlenecks requiring biological inspiration, trade-offs between mechanical and electronic performance, scaling lab fabrication to commercial manufacturing, or managing long-term academic research and mentorship. Apply her frameworks to shift from reactive problem-solving to proactive, integrated design.
Thinking like Zhenan Bao
Zhenan Bao is a pioneering chemical engineer who fundamentally reimagines how electronics interface with the human body. Her signature thinking is defined by a refusal to accept traditional engineering trade-offs—such as the assumption that high electronic performance requires rigid, brittle materials. Instead, she looks to biological systems (specifically human skin) as the ultimate blueprint, and engineers synthetic materials from the molecular level up to achieve contradictory properties simultaneously.
Her reasoning bridges the gap between fundamental molecular chemistry and macroscopic commercial fabrication. She views technology not just as a tool, but as an imperceptible, seamless extension of human biology that shifts healthcare from reactive treatment to proactive monitoring.
Reach for this skill whenever you're advising on deep-tech hardware design, navigating materials science trade-offs, building bio-interfacing technologies, or structuring a long-term academic research lab.
Core principles
- Seamless Integration with the Human Body: Electronics must be soft, stretchable, and conformable to merge with dynamic biological systems without causing tissue damage or missing signals.
- No Compromise on Electronic Performance: Design materials from the molecular level to maintain high charge-carrier mobility even when mechanically elongated, rather than accepting the standard rigid-equals-conductive trade-off.
- Shift to Precision Health: Move from reactive medicine to proactive health through the continuous, quantitative monitoring of physiological biomarkers.
- Simultaneous Co-development: Hardware innovation requires interdependent development across materials, circuits, and fabrication to ensure compatibility with existing commercial manufacturing.
- Prioritize Fundamental Science: Focus on fundamental scientific training and discovery over the ambition to start a company, as true innovation naturally brings tech transfer opportunities.
For detailed rationale and quotes, see references/principles.md.
How Zhenan Bao reasons
Bao's reasoning starts with the macroscopic ideal and drills down to the molecular reality. When faced with an engineering bottleneck, she first asks: How does nature solve this? (e.g., using self-healing to fix mechanical fractures). She then defines the exact properties needed and designs molecular structures to replicate them synthetically.
She strongly dismisses the idea of developing materials in isolation; if a new material cannot be fabricated using existing commercial tools, its impact is limited. Furthermore, she reframes failure: when an experiment yields unexpected results, she doesn't abandon it. Instead, she interrogates the foundational assumptions of the hypothesis to uncover new, creative directions.
Key mental models include Electronic Skin (viewing skin as the ultimate blueprint for next-gen electronics) and Dynamic Bonds as Energy Shock Absorbers (using reversible chemical bonds to dissipate mechanical strain). For her complete set of models, see references/mental-models.md.
Applying the frameworks
Skin-Inspired Material Design
Use when designing new classes of flexible, biocompatible electronics or physical interfaces.
- Identify a biological system with the desired properties (e.g., human skin).
- Define the specific macroscopic properties to mimic (stretchability, biodegradability, self-healing).
- Design molecular structures that replicate these properties without losing electronic function.
- Ensure the system's output signals match biological receptors.
Show full SKILL.md (326 more words)Show less
Molecular Design for Contradictory Properties
Use when engineering systems that require traditionally opposing characteristics (e.g., conductivity vs. stretchability).
- Identify the opposing requirements.
- Design a composite molecular structure that incorporates elements of both (e.g., conductive polymers surrounded by flexible, ring-like molecules).
- Engineer the structure to dissipate mechanical energy without breaking the functional pathway.
Reframing Experimental Failure
Use when a research project or experiment hits a wall and yields unexpected results.
- Resist the urge to declare the experiment a "failure."
- Examine the original hypothesis to identify incorrect foundational assumptions.
- Use those uncovered assumptions to develop creative new ideas that wouldn't have been considered otherwise.
For the full catalog of her frameworks, see references/frameworks.md.
Anti-patterns they push against
- Relying on Rigid, Crystalline Structures: Assuming high performance requires purely rigid structures, which makes materials brittle and unsuitable for dynamic environments.
- Using Rigid Materials for Biological Interfaces: Forcing rigid devices into soft tissue, which causes severe immune responses, scarring, and discomfort.
- Developing Materials in Isolation: Creating novel materials without considering how they will be stacked into circuits or manufactured using existing commercial tools.
- Declaring "Failed" Experiments: Stopping the inquiry process when results are unexpected, rather than hunting for the incorrect assumptions that led there.
- Researching to Start a Company: Conducting academic research primarily for commercialization, which distracts from building a solid fundamental understanding.
How to use this skill in conversation
When the user is facing hardware design trade-offs, surface the Molecular Design for Contradictory Properties framework to help them engineer around the compromise. If they are discussing health tech or wearables, invoke the shift to Precision Health and the Electronic Skin mental model to push their thinking toward continuous, imperceptible monitoring.
Cite her concepts by name (e.g., "Zhenan Bao calls this the 'Nano-confinement Effect'") and apply her principles to the user's specific context. Do not pretend to be Zhenan Bao or speak in the first person. Instead, channel her rigorous, biology-inspired, molecular-level approach to problem-solving.
© K-Dense-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 71 other files (references) in mimeographs/zhenan-bao of K-Dense-AI/mimeographs.
- SKILL.md
- AGENTS.md
- _workspace/agents_output.e584bd6c.json
- _workspace/clustered_corpus.e584bd6c.json
- _workspace/discovery/books.json
- _workspace/discovery/essays.json
- _workspace/discovery/frameworks.json
- _workspace/discovery/interviews.json
- _workspace/discovery/letters.json
- _workspace/discovery/papers.json
- _workspace/discovery/podcasts.json
- _workspace/discovery/ranked_sources.e584bd6c.json
- _workspace/discovery/talks.json
- _workspace/distilled/src_000.e584bd6c.json
- _workspace/distilled/src_001.e584bd6c.json
- _workspace/distilled/src_004.e584bd6c.json
- _workspace/distilled/src_007.e584bd6c.json
- _workspace/distilled/src_008.e584bd6c.json
- … and 54 more
Open the folder on GitHubat commit a38f5fc
Compare with similar skills
Zhenan Bao next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Zhenan Bao this skillK-Dense-AI/mimeographs | 129 | — | ~1.7k | Automated safety check: Pass | MIT | |
| AstropyzLanqing/codex-claude-academic-skills | 4.7k | 13 repos | ~2.9k | Automated safety check: Pass | BSD-3-Clause | |
| PymatgenzLanqing/codex-claude-academic-skills | 4.7k | 11 repos | ~5k | Automated safety check: Pass | MIT | |
| Cantera Ignition DelayK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Weathertrpc-group/trpc-agent-go | 1.9k | 8 repos | ~591 | Automated safety check: Pass | Apache-2.0 | |
| Pymol VisualizationChatMol/ChatMol | 373 | — | ~1.2k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Zhenan Bao
What does Zhenan Bao do?
Applies the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford University, flexible electronics). Zhenan Bao is an agent skill from K-Dense-AI/mimeographs. Applies the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford University, flexible electronics).
When should I use Zhenan Bao?
Zhenan Bao fits situations like: you are advising on hardware innovation; materials science; wearable/implantable technology; deep-tech research strategy.
How do I install Zhenan Bao in Claude Code?
Run `npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a claude-code`. Or copy the skill folder (mimeographs/zhenan-bao in K-Dense-AI/mimeographs) into .claude/skills/zhenan-bao in your project. Claude Code loads it when a task matches its description.
How do I install Zhenan Bao in Codex?
Run `npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a codex`. Or copy the skill folder (mimeographs/zhenan-bao in K-Dense-AI/mimeographs) into .agents/skills/zhenan-bao in your project. Codex loads it when a task matches its description.
Can I use Zhenan Bao in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add K-Dense-AI/mimeographs --skill zhenan-bao -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/zhenan-bao, .gemini/skills/zhenan-bao, .github/skills/zhenan-bao and .opencode/skills/zhenan-bao in your project.
What does Zhenan Bao need to run?
SKILL.md names no scripts, command-line tools or credentials: Zhenan Bao is instructions for the agent only.
Does Zhenan Bao access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Zhenan Bao safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Zhenan Bao use?
Zhenan Bao is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Zhenan Bao use?
About 1.7k tokens (SKILL.md is roughly 6.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.5k tokens, read only when the agent opens those files.
What are the alternatives to Zhenan Bao?
Skills that share tags, products or a category with Zhenan Bao: Astropy (zLanqing/codex-claude-academic-skills, 4.7k stars), Pymatgen (zLanqing/codex-claude-academic-skills, 4.7k stars), Cantera Ignition Delay (K-Dense-AI/scientific-agent-skills, 48k stars) and Weather (trpc-group/trpc-agent-go, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Zhenan Bao?
K-Dense-AI (a GitHub organization) maintains it in K-Dense-AI/mimeographs, which has 129 GitHub stars. The repository holds 60 skills in this directory. The repository was last updated on August 18, 2026.
Source: K-Dense-AI/mimeographs on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.