Study Plan
anthropics/claude-for-legal
Build or update a long-term bar prep (or exam prep) study plan — phases, subjects weighted by weakness, daily session schedule, adaptive to session history in study-plan.yaml.
Applies the behavioral genetics and twin-study methodologies of Dorret I.
MITAuto-check passed
Install Dorret Boomsma
$ npx skills add K-Dense-AI/mimeographs --skill dorret-boomsma -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install K-Dense-AI/mimeographs dorret-boomsma --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/dorret-i-boomsma .claude/skills/dorret-boomsma && 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 "dorret-boomsma" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/dorret-i-boomsma into .claude/skills/dorret-boomsma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dorret-boomsma", 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/dorret-i-boomsmaType 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 dorret-boomsma -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install K-Dense-AI/mimeographs dorret-boomsma --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/dorret-i-boomsma .agents/skills/dorret-boomsma && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dorret-boomsma" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/dorret-i-boomsma into .agents/skills/dorret-boomsma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dorret-boomsma", 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 dorret-boomsma -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install K-Dense-AI/mimeographs dorret-boomsma --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/dorret-i-boomsma .cursor/skills/dorret-boomsma && 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 "dorret-boomsma" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/dorret-i-boomsma into .cursor/skills/dorret-boomsma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dorret-boomsma", 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/dorret-i-boomsma--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 dorret-boomsma -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install K-Dense-AI/mimeographs dorret-boomsma --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/dorret-i-boomsma .gemini/skills/dorret-boomsma && 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 "dorret-boomsma" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/dorret-i-boomsma into .gemini/skills/dorret-boomsma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dorret-boomsma", 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 dorret-boomsmaInstalls 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 dorret-boomsma -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/dorret-i-boomsma .github/skills/dorret-boomsma && 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 "dorret-boomsma" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/dorret-i-boomsma into .github/skills/dorret-boomsma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dorret-boomsma", 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 dorret-boomsma -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 dorret-boomsma --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/dorret-i-boomsma .opencode/skills/dorret-boomsma && 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 "dorret-boomsma" agent skill from https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/dorret-i-boomsma into .opencode/skills/dorret-boomsma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dorret-boomsma", 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
dorret-boomsma- GitHub stars
- 129
- Token cost
- ~1.6k tokens
- SKILL.md length
- 767 words
- Files
- 72 (incl. references)
- Skills in repo
- 60
- Repo updated
- First seen
- Licence
- MIT
At a glance
Applies the behavioral genetics and twin-study methodologies of Dorret I.
- Works in 4 steps: Recruit a large cohort of twins. → Extend recruitment to include parents,… → Collect longitudinal phenotype and… → …
- Reasoning about heritability
- SKILL.md covers Core principles, How Dorret I. Boomsma reasons, Applying the frameworks and Anti-patterns she pushes against, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Dorret Boomsma is an agent skill from K-Dense-AI/mimeographs. Applies the behavioral genetics and twin-study methodologies of Dorret I. Boomsma (behavior geneticist, Vrije Universiteit Amsterdam). Use this skill when reasoning about heritability, genetic epidemiology, nature vs. nurture debates, psychiatric genetics, or longitudinal phenotyping. Trigger this whenever the user asks about the genetic basis of intelligence, lifestyle factors, educational attainment, or psychopathology, or when designing epidemiological studies. It helps deconfound environmental and genetic…
Its SKILL.md is about 1.6k 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`).
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
- Reasoning about heritability
- Genetic epidemiology
- This whenever the user asks about the genetic basis of intelligence
- Lifestyle factors
Example prompts
- “Use the dorret-boomsma skill to apply the behavioral genetics and twin-study methodologies of Dorret I”
- “/dorret-boomsma”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Recruit a large cohort of twins.
- Extend recruitment to include parents, non-twin siblings, spouses, and adult offspring.
- Collect longitudinal phenotype and genotype data.
- Model the data simultaneously to correct for dependencies and test for a "special twin environment."
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
Dorret Boomsma loads about 1.6k tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 149 tokens; SKILL.md has 767 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). 767 words, ~1,597 tokens.
Download SKILL.mdSave it as
.claude/skills/dorret-boomsma/SKILL.md (or your agent's skills folder). This skill also uses 71 other files; get the full folder from GitHub.- name
- dorret-boomsma
- description
- Applies the behavioral genetics and twin-study methodologies of Dorret I. Boomsma (behavior geneticist, Vrije Universiteit Amsterdam). Use this skill when reasoning about heritability, genetic epidemiology, nature vs. nurture debates, psychiatric genetics, or longitudinal phenotyping. Trigger this whenever the user asks about the genetic basis of intelligence, lifestyle factors, educational attainment, or psychopathology, or when designing epidemiological studies. It helps deconfound environmental and genetic variables using extended family designs and discordant twin models.
Thinking like Dorret I. Boomsma
Dorret I. Boomsma's thinking revolves around the rigorous partitioning of human traits into genetic and environmental variance. As a pioneer in behavioral genetics and twin registries, her approach treats large, well-phenotyped family databases as quasi-experimental sandboxes. She does not view genetics as destiny; rather, she uses genetic similarity to isolate and understand environmental impacts, and vice versa.
Her signature cognitive move is to challenge default assumptions about "environment." When society assumes a behavior (like smoking, diet, or parenting) is a purely environmental input, she asks if the selection of that environment is actually driven by the genome. Reach for this skill whenever you're analyzing the root causes of human behavior, designing epidemiological studies, evaluating psychiatric diagnostic criteria, or debating the heritability of complex traits.
Core principles
- High Heritability ≠ High Predictability: Treat genetic influence as a probabilistic baseline, not a deterministic outcome; even genetic clones exhibit discordance in disease risk and personality.
- Lifestyle Factors are Genetically Influenced: When evaluating "environmental" risk factors like diet or exercise, account for the fact that genes drive individuals to select or create these specific environments.
- Diagnostic Labels Require Biological Meaning: Do not accept clinical validity as proof of biological reality; always subtype phenotypes based on co-morbidities before searching for genetic linkages.
- Extended Family Designs Validate Twin Studies: Never rely solely on MZ/DZ twins; include siblings, parents, and spouses to explicitly test if results generalize to singletons and to rule out a "special twin environment."
- Longitudinal Phenotyping Requires DNA Typing: To understand how traits evolve, combine lifespan phenotypic tracking with large-scale DNA typing to watch genetic architecture shift over time.
For detailed rationale and quotes, see references/principles.md.
How Dorret I. Boomsma reasons
Boomsma starts by asking how a trait's variance can be partitioned. She immediately looks for natural controls—specifically monozygotic twins—to hold the genome constant while isolating environmental pathways. She is highly skeptical of studies that lump complex, co-morbid psychiatric conditions into single diagnostic buckets, preferring deep, longitudinal phenotyping.
When analyzing how traits change over time (like childhood IQ), she applies the Developmental Genetic Architecture model, looking for how the relative proportions of genetic and environmental variance shift continuously across a lifespan. She also distinguishes between Variability vs. Level Genes, separating genes that affect a baseline trait from those that dictate an individual's sensitivity to environmental inputs. For the full catalog of her mental models, see references/mental-models.md.
Applying the frameworks
Extended Twin-Family Design
Use this when you need to test the underlying assumptions of a standard twin study or estimate complex variance components.
- Recruit a large cohort of twins.
- Extend recruitment to include parents, non-twin siblings, spouses, and adult offspring.
- Collect longitudinal phenotype and genotype data.
- Model the data simultaneously to correct for dependencies and test for a "special twin environment."
Show full SKILL.md (303 more words)Show less
Monozygotic Discordant (MZD) Design
Use this when you need to perfectly control for genetic background to isolate purely environmental causes of a disease or trait.
- Identify monozygotic (MZ) twin pairs discordant for a specific phenotype (e.g., depression).
- Conduct deep phenotyping on both twins.
- Analyze intra-pair differences to isolate environmental factors, knowing the genetic sequence is identical.
For more frameworks, including SEM for Twin Data and Retrospective Epigenetic Profiling, see references/frameworks.md.
Anti-patterns she pushes against
- Equating Heritability with Determinism: Assuming that because a trait is highly heritable, its outcome is highly predictable, ignoring the discordance found in genetic clones.
- Treating Lifestyle as Purely Environmental: Ignoring the genetic factors that drive individuals to select or create their environments (e.g., diet, smoking).
- Blaming Parents for Heritable Disorders: Attributing highly heritable childhood conditions (like ADHD or aggression) to poor parenting rather than the genome.
- Ignoring Comorbidity in Psychiatric Genetics: Conducting linkage studies on complex psychiatric disorders without phenotypic subtyping, mixing different underlying genotypes.
- Relying Solely on Classical Twin Designs: Failing to include non-twin siblings to prove that twin results actually generalize to the broader population.
How to use this skill in conversation
When the user is analyzing human behavior, epidemiological data, or psychiatric traits, channel Boomsma's rigorous variance-partitioning mindset.
If the user assumes a trait is purely environmental (like a child's educational attainment or a patient's lifestyle choices), gently introduce the principle that Lifestyle Factors are Genetically Influenced. If they assume genetics dictate destiny, apply the High Heritability ≠ High Predictability principle, citing the discordance in MZ twins.
Name her frameworks explicitly (e.g., "If we apply Dorret I. Boomsma's Monozygotic Discordant Design here...") to help the user structure their epidemiological or experimental thinking. Do not pretend to be Boomsma; instead, act as an analytical assistant applying her specific behavioral genetics toolkit to the user's problem.
© 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/dorret-i-boomsma 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_003.e584bd6c.json
- _workspace/distilled/src_005.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
Dorret Boomsma 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 |
|---|---|---|---|---|---|---|
| Dorret Boomsma this skillK-Dense-AI/mimeographs | 129 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Study Plananthropics/claude-for-legal | 9.6k | 3 repos | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Benchmark Methodologyaffaan-m/ECC | 277k | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Evaluation Methodologywshobson/agents | 40k | — | ~2k | Automated safety check: Pass | MIT | |
| SPARC Development Methodologyruvnet/ruflo | 74k | 1 repos | ~829 | Automated safety check: Pass | MIT | |
| Study BuddyLeoYeAI/openclaw-master-skills | 2.2k | — | ~5.5k | Automated safety check: Pass | MIT |
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Questions about Dorret Boomsma
What does Dorret Boomsma do?
Applies the behavioral genetics and twin-study methodologies of Dorret I. Dorret Boomsma is an agent skill from K-Dense-AI/mimeographs. Applies the behavioral genetics and twin-study methodologies of Dorret I.
When should I use Dorret Boomsma?
Dorret Boomsma fits situations like: reasoning about heritability; genetic epidemiology; this whenever the user asks about the genetic basis of intelligence; lifestyle factors.
How do I install Dorret Boomsma in Claude Code?
Run `npx skills add K-Dense-AI/mimeographs --skill dorret-boomsma -a claude-code`. Or copy the skill folder (mimeographs/dorret-i-boomsma in K-Dense-AI/mimeographs) into .claude/skills/dorret-boomsma in your project. Claude Code loads it when a task matches its description.
How do I install Dorret Boomsma in Codex?
Run `npx skills add K-Dense-AI/mimeographs --skill dorret-boomsma -a codex`. Or copy the skill folder (mimeographs/dorret-i-boomsma in K-Dense-AI/mimeographs) into .agents/skills/dorret-boomsma in your project. Codex loads it when a task matches its description.
Can I use Dorret Boomsma 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 dorret-boomsma -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dorret-boomsma, .gemini/skills/dorret-boomsma, .github/skills/dorret-boomsma and .opencode/skills/dorret-boomsma in your project.
What does Dorret Boomsma need to run?
SKILL.md names no scripts, command-line tools or credentials: Dorret Boomsma is instructions for the agent only.
Does Dorret Boomsma 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 Dorret Boomsma 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 Dorret Boomsma use?
Dorret Boomsma 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 Dorret Boomsma use?
About 1.6k tokens (SKILL.md is roughly 6.4k 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 4.5k tokens, read only when the agent opens those files.
What are the alternatives to Dorret Boomsma?
Skills that share tags, products or a category with Dorret Boomsma: Study Plan (anthropics/claude-for-legal, 9.6k stars), Benchmark Methodology (affaan-m/ECC, 277k stars), Evaluation Methodology (wshobson/agents, 40k stars) and SPARC Development Methodology (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Dorret Boomsma?
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.