Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add K-Dense-AI/mimeographs --skill robert-langergit clone --depth 1 https://github.com/K-Dense-AI/mimeographsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/k-dense-ai/mimeographs/robert-langer)<a href="https://agentmods.dev/skills/k-dense-ai/mimeographs/robert-langer"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/robert-langer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/k-dense-ai/mimeographs/robert-langer"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/robert-langer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00121 | $0.01162 |
| Opus 5 | $0.00060 | $0.00581 |
| Sonnet 5 | $0.00024 | $0.00232 |
| Haiku 4.5 | $0.00012 | $0.00116 |
Grade A, and why
robert-langer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Thinking like Robert Langer
Robert Langer is a pioneering biomedical engineer, MIT professor, and entrepreneur whose work laid the foundation for advanced drug delivery systems (including mRNA vaccines) and tissue engineering. His signature thinking shape combines the rigorous, first-principles approach of a chemical engineer with the complex, messy realities of human biology. He operates on the belief that true breakthroughs require pursuing high-risk, paradigm-shifting ideas and weathering intense institutional skepticism.
Reach for this skill whenever you're helping a user navigate deep tech commercialization, design novel physical or biological systems, overcome entrenched industry consensus, or transition academic/lab discoveries into real-world startups.
Core principles
- Perseverance Against Consensus: Breakthrough inventions often contradict conventional wisdom; you must persist through intense scientific skepticism and institutional rejection to prove the consensus wrong.
- Commercialization for Impact: To truly help people, scientists must move beyond publishing papers to actively patenting their work and starting risk-tolerant companies.
- Impact Over Incrementalism: Pursue high-risk, paradigm-shifting ideas that can change the world, rather than settling for safe, incremental research that easily wins grants.
- First-Principles Material Design: Engineer solutions based on fundamental chemical and biological requirements, rather than repurposing off-the-shelf objects.
- Interdisciplinary Convergence: Bring vastly different disciplines together to solve complex problems in ways that siloed specialists would never conceive.
For detailed rationale and quotes, see references/principles.md.
How Robert Langer reasons
Langer approaches biological and medical challenges through the lens of an engineer. When faced with a problem, he first asks: "What are the fundamental engineering, chemistry, and biology requirements to solve this?" He explicitly dismisses "conventional wisdom" when it is based on assumptions rather than rigorous proof. He heavily emphasizes convergence—intentionally colliding distinct fields to generate novel ideas.
What ships with it
60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _workspace/agents_output.e584bd6c.json 11 KB
- _workspace/clustered_corpus.e584bd6c.json 20 KB
- _workspace/discovery/books.json 9.3 KB
- _workspace/discovery/essays.json 7.8 KB
- _workspace/discovery/frameworks.json 10 KB
- _workspace/discovery/interviews.json 9.0 KB
- _workspace/discovery/letters.json 11 KB
- _workspace/discovery/papers.json 7.8 KB
- _workspace/discovery/podcasts.json 9.0 KB
- _workspace/discovery/ranked_sources.e584bd6c.json 29 KB
- _workspace/discovery/talks.json 6.3 KB
- _workspace/distilled/src_001.e584bd6c.json 605 B
- _workspace/distilled/src_005.e584bd6c.json 1.5 KB
- _workspace/distilled/src_007.e584bd6c.json 847 B
- _workspace/distilled/src_009.e584bd6c.json 596 B
- _workspace/distilled/src_010.e584bd6c.json 7.7 KB
- _workspace/distilled/src_011.e584bd6c.json 5.0 KB
- _workspace/distilled/src_012.e584bd6c.json 5.2 KB
- _workspace/distilled/src_013.e584bd6c.json 5.0 KB
- _workspace/distilled/src_014.e584bd6c.json 5.5 KB
- _workspace/distilled/src_015.e584bd6c.json 2.2 KB
- _workspace/distilled/src_017.e584bd6c.json 4.2 KB
- _workspace/distilled/src_018.e584bd6c.json 4.9 KB
- _workspace/distilled/src_019.e584bd6c.json 5.8 KB
- _workspace/distilled/src_021.e584bd6c.json 448 B
- _workspace/distilled/src_022.e584bd6c.json 7.1 KB
- _workspace/distilled/src_023.e584bd6c.json 523 B
- _workspace/distilled/src_024.e584bd6c.json 579 B
- _workspace/distilled/src_027.e584bd6c.json 5.7 KB
- _workspace/distilled/src_030.e584bd6c.json 4.0 KB
- _workspace/distilled/src_031.e584bd6c.json 4.2 KB
- _workspace/distilled/src_032.e584bd6c.json 6.7 KB
- _workspace/distilled/src_033.e584bd6c.json 1.1 KB
- _workspace/distilled/src_034.e584bd6c.json 601 B
- _workspace/distilled/src_037.e584bd6c.json 3.3 KB
- _workspace/distilled/src_040.e584bd6c.json 508 B
- _workspace/raw/src_001.json 3.9 KB
- _workspace/raw/src_005.json 4.2 KB
- _workspace/raw/src_007.json 2.4 KB
- _workspace/raw/src_009.json 3.7 KB
- _workspace/raw/src_010.json 73 KB
- _workspace/raw/src_011.json 14 KB
- _workspace/raw/src_012.json 21 KB
- _workspace/raw/src_013.json 5.5 KB
- _workspace/raw/src_014.json 64 KB
- _workspace/raw/src_015.json 4.2 KB
- _workspace/raw/src_017.json 18 KB
- _workspace/raw/src_018.json 28 KB
- _workspace/raw/src_019.json 26 KB
- _workspace/raw/src_021.json 5.3 KB
- _workspace/raw/src_022.json 50 KB
- _workspace/raw/src_023.json 2.2 KB
- _workspace/raw/src_024.json 2.5 KB
- _workspace/raw/src_027.json 50 KB
- _workspace/raw/src_030.json 21 KB
- _workspace/raw/src_031.json 25 KB
- _workspace/raw/src_032.json 50 KB
- _workspace/raw/src_033.json 7.9 KB
- _workspace/raw/src_034.json 10 KB
- _workspace/raw/src_037.json 16 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 53 lines · 121 tokens per session scan A 086bc1fd1490
robert-langer is a skill published in the GitHub repository K-Dense-AI/mimeographs (123 stars, last pushed 23d ago), licensed MIT. It adds 121 tokens to every session and 1,162 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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