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 ronald-c-kesslergit 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/ronald-c-kessler)<a href="https://agentmods.dev/skills/k-dense-ai/mimeographs/ronald-c-kessler"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/ronald-c-kessler/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/ronald-c-kessler"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/ronald-c-kessler.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 | $0.00133 | $0.01204 |
| Opus 5 | $0.00067 | $0.00602 |
| Sonnet 5 | $0.00027 | $0.00241 |
| Haiku 4.5 | $0.00013 | $0.00120 |
Grade A, and why
ronald-c-kessler 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 12d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Thinking like Ronald C. Kessler
Ronald C. Kessler's thinking bridges the gap between massive-scale epidemiological data and individualized clinical care. As a psychiatric epidemiologist, his approach is defined by a relentless focus on statistical power, pragmatic real-world evidence, and the brutal realities of patient attrition. He views mental health treatment not as a single acute intervention, but as a complex, sequential matching problem where the greatest risk is a patient giving up before finding what works.
His reasoning consistently pushes back against the traditional "gold standard" of small randomized clinical trials, arguing they are hopelessly underpowered for precision medicine. Instead, he advocates for leveraging massive observational datasets, tiered predictive modeling, and human-computer collaboration to get the right treatment to the right patient immediately.
Reach for this skill whenever you're designing clinical trials, evaluating mental health interventions, analyzing epidemiological survey data, or building clinical decision support algorithms.
Core principles
- Massive Sample Sizes for Precision Psychiatry: Reject small clinical trials for precision matching; rely instead on comparative effectiveness research using massive observational data to find true signals over statistical noise.
- Human-Computer Collaboration in Clinical Decisions: Design clinical algorithms to augment and interact with thoughtful human clinicians, rather than attempting to replace them.
- Treatment Persistence and Immediate Matching: Optimize systems to match patients with the right treatment on day one, because the primary bottleneck in psychiatric care is fatal patient drop-out, not a lack of effective treatments.
- Tiered Predictive Modeling: Exhaust scalable, inexpensive predictors (like self-reported adherence or clinical notes) before allocating resources to expensive biomarker tests.
- Measurement-Based Care and Cutting Losses: Mandate objective symptom tracking to identify and abandon failing treatments at three weeks instead of torturing the patient for eight weeks.
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 19 KB
- _workspace/discovery/books.json 10 KB
- _workspace/discovery/essays.json 9.4 KB
- _workspace/discovery/frameworks.json 9.7 KB
- _workspace/discovery/interviews.json 11 KB
- _workspace/discovery/letters.json 11 KB
- _workspace/discovery/papers.json 11 KB
- _workspace/discovery/podcasts.json 8.1 KB
- _workspace/discovery/ranked_sources.e584bd6c.json 37 KB
- _workspace/discovery/talks.json 8.8 KB
- _workspace/distilled/src_000.e584bd6c.json 572 B
- _workspace/distilled/src_001.e584bd6c.json 657 B
- _workspace/distilled/src_002.e584bd6c.json 660 B
- _workspace/distilled/src_003.e584bd6c.json 618 B
- _workspace/distilled/src_004.e584bd6c.json 342 B
- _workspace/distilled/src_005.e584bd6c.json 599 B
- _workspace/distilled/src_006.e584bd6c.json 424 B
- _workspace/distilled/src_007.e584bd6c.json 424 B
- _workspace/distilled/src_008.e584bd6c.json 719 B
- _workspace/distilled/src_009.e584bd6c.json 664 B
- _workspace/distilled/src_010.e584bd6c.json 8.8 KB
- _workspace/distilled/src_011.e584bd6c.json 478 B
- _workspace/distilled/src_012.e584bd6c.json 8.4 KB
- _workspace/distilled/src_014.e584bd6c.json 5.8 KB
- _workspace/distilled/src_015.e584bd6c.json 725 B
- _workspace/distilled/src_017.e584bd6c.json 5.9 KB
- _workspace/distilled/src_018.e584bd6c.json 1.3 KB
- _workspace/distilled/src_019.e584bd6c.json 475 B
- _workspace/distilled/src_020.e584bd6c.json 555 B
- _workspace/distilled/src_021.e584bd6c.json 797 B
- _workspace/distilled/src_022.e584bd6c.json 547 B
- _workspace/distilled/src_023.e584bd6c.json 2.6 KB
- _workspace/distilled/src_024.e584bd6c.json 488 B
- _workspace/distilled/src_025.e584bd6c.json 3.4 KB
- _workspace/distilled/src_026.e584bd6c.json 414 B
- _workspace/raw/src_000.json 2.3 KB
- _workspace/raw/src_001.json 4.1 KB
- _workspace/raw/src_002.json 2.4 KB
- _workspace/raw/src_003.json 3.8 KB
- _workspace/raw/src_004.json 2.0 KB
- _workspace/raw/src_005.json 3.2 KB
- _workspace/raw/src_006.json 2.8 KB
- _workspace/raw/src_007.json 23 KB
- _workspace/raw/src_008.json 6.7 KB
- _workspace/raw/src_009.json 50 KB
- _workspace/raw/src_010.json 37 KB
- _workspace/raw/src_011.json 26 KB
- _workspace/raw/src_012.json 38 KB
- _workspace/raw/src_014.json 41 KB
- _workspace/raw/src_015.json 4.1 KB
- _workspace/raw/src_017.json 22 KB
- _workspace/raw/src_018.json 3.1 KB
- _workspace/raw/src_019.json 2.1 KB
- _workspace/raw/src_020.json 7.9 KB
- _workspace/raw/src_021.json 2.1 KB
- _workspace/raw/src_022.json 8.9 KB
- _workspace/raw/src_023.json 15 KB
- _workspace/raw/src_024.json 13 KB
- _workspace/raw/src_025.json 12 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.
- 12d ago First seen · 58 lines · 133 tokens per session scan A 4c446aa2af25
ronald-c-kessler is a skill published in the GitHub repository K-Dense-AI/mimeographs (123 stars, last pushed 23d ago), licensed MIT. It adds 133 tokens to every session and 1,204 once invoked, about $0.0007 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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