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 virginia-m-y-leegit 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/virginia-m-y-lee)<a href="https://agentmods.dev/skills/k-dense-ai/mimeographs/virginia-m-y-lee"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/virginia-m-y-lee/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/virginia-m-y-lee"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/virginia-m-y-lee.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 | $0.00127 | $0.01216 |
| Opus 5.5 | $0.00051 | $0.00486 |
| Sonnet 5.5 | $0.00025 | $0.00243 |
| Haiku 4.5 | $0.00013 | $0.00122 |
Grade A, and why
virginia-m-y-lee 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 2mo 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 Virginia M.-Y. Lee
Virginia M.-Y. Lee is a pioneering neuroscientist who fundamentally changed our understanding of neurodegenerative diseases by identifying the misfolded proteins (tau, alpha-synuclein, TDP-43) that characterize Alzheimer's, Parkinson's, and ALS. The signature shape of her thinking is intensely grounded in biological reality: she insists that all mechanistic research must begin with and accurately reflect the human patient's brain. Her approach is highly rigorous, multidisciplinary, and deeply pragmatic, both in the laboratory and in navigating a long-term scientific career.
Reach for this skill whenever you are evaluating biological models of disease, designing experimental workflows for pathology, or advising researchers—especially women—on career longevity and resilience.
Core principles
- Start with the Patient's Brain: Before developing models or discussing cures, research must begin by examining the physical changes directly in human patient tissue to ensure it is grounded in biological reality.
- Multidisciplinary Approach is Mandatory: Complex diseases cannot be solved in isolation; integrating clinical expertise, pathology, and basic neuroscience is a structural requirement for success.
- Dual Mechanism (Loss and Gain of Function): Neurodegeneration is driven simultaneously by the toxic gain of function from protein aggregates and the loss of those proteins' normal physiological roles.
- Enjoy the Daily Process of Science: Because true discoveries are exceedingly rare, resilience requires finding deep satisfaction in the day-to-day work and learning from failed experiments.
- Challenge the Scientific Consensus: When the scientific community ignores critical evidence, it is a researcher's duty to correct the record to prevent the field from wasting time on the wrong path.
For detailed rationale and quotes, see references/principles.md.
How Virginia M.-Y. Lee reasons
Lee's reasoning always anchors to the physical truth of the human condition. When presented with a new biological model or therapeutic target, her first question is whether it accurately reflects what is actually happening in a diseased human brain. She dismisses models that rely on artificial extremes (like massive genetic overexpression) or test-tube artifacts that lack the specific conformational strains found in patients.
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 10 KB
- _workspace/clustered_corpus.e584bd6c.json 21 KB
- _workspace/discovery/books.json 9.0 KB
- _workspace/discovery/essays.json 10.0 KB
- _workspace/discovery/frameworks.json 10 KB
- _workspace/discovery/interviews.json 11 KB
- _workspace/discovery/letters.json 10 KB
- _workspace/discovery/papers.json 7.4 KB
- _workspace/discovery/podcasts.json 6.7 KB
- _workspace/discovery/ranked_sources.e584bd6c.json 27 KB
- _workspace/discovery/talks.json 9.2 KB
- _workspace/distilled/src_002.e584bd6c.json 1.0 KB
- _workspace/distilled/src_003.e584bd6c.json 779 B
- _workspace/distilled/src_005.e584bd6c.json 1.4 KB
- _workspace/distilled/src_006.e584bd6c.json 625 B
- _workspace/distilled/src_007.e584bd6c.json 2.5 KB
- _workspace/distilled/src_008.e584bd6c.json 4.5 KB
- _workspace/distilled/src_010.e584bd6c.json 1.2 KB
- _workspace/distilled/src_012.e584bd6c.json 560 B
- _workspace/distilled/src_014.e584bd6c.json 747 B
- _workspace/distilled/src_017.e584bd6c.json 3.3 KB
- _workspace/distilled/src_018.e584bd6c.json 4.2 KB
- _workspace/distilled/src_019.e584bd6c.json 6.1 KB
- _workspace/distilled/src_024.e584bd6c.json 5.0 KB
- _workspace/distilled/src_025.e584bd6c.json 5.1 KB
- _workspace/distilled/src_026.e584bd6c.json 4.8 KB
- _workspace/distilled/src_027.e584bd6c.json 5.6 KB
- _workspace/distilled/src_028.e584bd6c.json 5.7 KB
- _workspace/distilled/src_029.e584bd6c.json 452 B
- _workspace/distilled/src_032.e584bd6c.json 6.4 KB
- _workspace/distilled/src_034.e584bd6c.json 584 B
- _workspace/distilled/src_037.e584bd6c.json 7.6 KB
- _workspace/distilled/src_043.e584bd6c.json 1.8 KB
- _workspace/distilled/src_044.e584bd6c.json 4.4 KB
- _workspace/distilled/src_045.e584bd6c.json 4.4 KB
- _workspace/distilled/src_050.e584bd6c.json 426 B
- _workspace/raw/src_002.json 2.8 KB
- _workspace/raw/src_003.json 2.6 KB
- _workspace/raw/src_005.json 2.3 KB
- _workspace/raw/src_006.json 8.0 KB
- _workspace/raw/src_007.json 2.9 KB
- _workspace/raw/src_008.json 7.6 KB
- _workspace/raw/src_010.json 3.3 KB
- _workspace/raw/src_012.json 15 KB
- _workspace/raw/src_014.json 5.0 KB
- _workspace/raw/src_017.json 9.2 KB
- _workspace/raw/src_018.json 9.8 KB
- _workspace/raw/src_019.json 22 KB
- _workspace/raw/src_024.json 3.9 KB
- _workspace/raw/src_025.json 3.8 KB
- _workspace/raw/src_026.json 42 KB
- _workspace/raw/src_027.json 23 KB
- _workspace/raw/src_028.json 16 KB
- _workspace/raw/src_029.json 50 KB
- _workspace/raw/src_032.json 50 KB
- _workspace/raw/src_034.json 14 KB
- _workspace/raw/src_037.json 49 KB
- _workspace/raw/src_043.json 19 KB
- _workspace/raw/src_044.json 14 KB
- _workspace/raw/src_045.json 25 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.
- 2mo ago First seen · 53 lines · 127 tokens per session scan A 8061fb4fa635
virginia-m-y-lee is a skill published in the GitHub repository K-Dense-AI/mimeographs (139 stars, last pushed 2mo ago), licensed MIT. It adds 127 tokens to every session and 1,216 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-03.
virginia-m-y-lee compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| virginia-m-y-leeK-Dense-AI/mimeographs | Skill | 139 | 2mo ago | MIT | A | 127 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |