Agent skill

Rare Disease Cancer

by exon-research in exon-research/genomi

Plan rare disease, hereditary disease, cancer risk, carrier-relevance, and observed-condition source investigation from public targets or selected active genome evidence.

Apache-2.0Auto-check passedResearch & Science

Install Rare Disease Cancer

skills CLI
$ npx skills add exon-research/genomi --skill rare-disease-cancer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install exon-research/genomi rare-disease-cancer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/exon-research/genomi.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/rare-disease-cancer .claude/skills/rare-disease-cancer && rm -rf skills-src

Use ~/.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/

Facts

Skill name
rare-disease-cancer
GitHub stars
484
Token cost
~2.7k tokens
SKILL.md length
1,098 words
Files
1
Skills in repo
20
Repo updated
First seen
Licence
Apache-2.0

At a glance

Plan rare disease, hereditary disease, cancer risk, carrier-relevance, and observed-condition source investigation from public targets or selected active genome evidence.

  • Tasks that involve Bioinformatics
  • SKILL.md covers Contract, First Tool, Source Review and Evidence Checks, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Rare Disease Cancer is an agent skill from exon-research/genomi. Plan rare disease, hereditary disease, cancer risk, carrier-relevance, and observed-condition source investigation from public targets or selected active genome evidence.

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Bioinformatics. The repository describes itself as: Local-first, open-source Claude Science alternative, before Claude Science is a thing. Turn your AI agent into personal DNA expert. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Bioinformatics

Example prompts

  • “/rare-disease-cancer”

What it can do on your machine

Read from SKILL.md and the folder at commit 1df4f5b. 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

Rare Disease Cancer loads about 2.7k tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 1,098 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~48
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

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 exon-research/genomi at commit 1df4f5b, republished under its Apache-2.0 licence (© exon-research). 1,098 words, ~2,749 tokens.

Download SKILL.mdSave it as .claude/skills/rare-disease-cancer/SKILL.md (or your agent's skills folder).
name
rare-disease-cancer
description
Plan rare disease, hereditary disease, cancer risk, carrier-relevance, and observed-condition source investigation from public targets or selected active genome evidence.
tools
phenotype.plan_risk_investigation, phenotype.normalize_terms, phenotype.retrieve_gene_disease_associations, phenotype.compare_disease_evidence…
mutating
true

Condition Review

Use this skill when the user asks about rare disease, hereditary disease, cancer risk genes, hereditary cancer, GeneCards-style gene context, MalaCards disease context, HPO/phenotype-to-disease review, HPO-style phenotype-to-gene review, carrier-relevance evidence, observed-condition review, or disease-gene source review.

Not for common-trait phenotypes. Common, complex-disease, GWAS-style, or drug-target candidate-gene questions use the matching source-specific tool. Use this skill when the phenotype is explicitly rare/Mendelian, HPO-style, or hereditary cancer.

Contract

Support both public-only questions and selected active genome evidence.

  • Public-only questions stay public-only.
  • Active genome evidence is used only when the current chat has selected or approved active genome access.
  • GeneCards and MalaCards are context sources, not clinical-validity sources by themselves.
  • Cancer-gene role, somatic cancer evidence, and inherited germline risk remain separate unless a reviewed source links them.
  • Carrier-review output consumes ClinVar carrier_relevance groups and ranks review targets by evidence strength plus missing interpretation gates.
  • Observed-condition review consumes observed-condition, uncertainty/conflict, risk-association, benign/counterevidence, and population-context groups.
  • Reviewed source findings are stored before final interpretation or reporting.
  • HPO and symptom overlap can prioritize review targets, but it is not a diagnosis.

First Tool

Call phenotype.plan_risk_investigation first. Provide any public targets the user gave:

  • phenotype.plan_risk_investigation with {"question":"BRCA1 hereditary breast cancer risk","gene":"BRCA1","investigation_type":"cancer_risk"}
  • phenotype.plan_risk_investigation with {"question":"carrier relevance review","investigation_type":"carrier_review"}
  • phenotype.plan_risk_investigation with {"question":"observed ClinVar condition review","investigation_type":"observed_condition_review"}

For a selected Active Genome Index, add:

  • phenotype.plan_risk_investigation with {"question":"rare disease review for GENE2","gene":"GENE2","include_active_genome_index":true}

If the user did not select active genome evidence, do not add active genome parameters.

For phenotype-first questions, normalize and rank the public targets:

  • phenotype.normalize_terms with {"text":"ataxia; microcephaly; seizures; HP:0001250"}
  • phenotype.retrieve_gene_disease_associations with {"genes":["PIEZO2"]}
  • phenotype.compare_disease_evidence with {"phenotypes":["ataxia","microcephaly","seizures"],"candidate_diseases":["condition A","condition B"],"source_records":[{"diseases":["condition A"],"verified_fields":{"diseases":["condition A"],"phenotypes":["ataxia"]},"support_spans":[{"field":"phenotypes","text":"source-backed ataxia text"}]}]}
  • phenotype.compare_disease_evidence with {"hpo_ids":["HP:0000822","HP:0001965"],"genes":["PIEZO2"]}
  • phenotype.compare_gene_hpo_evidence with {"phenotypes":["ataxia","microcephaly"],"genes":["PNKP","SPG7"],"source_records":[{"genes":["PNKP"],"verified_fields":{"genes":["PNKP"],"phenotypes":["ataxia","microcephaly"]},"support_spans":[{"field":"genes","text":"source-backed PNKP text"}]}]}

Use phenotype.compare_disease_evidence when the answer choices are diseases or syndromes. Also use it when the input is HPO terms plus known or candidate genes but the requested output is a disease name, syndrome name, or OMIM-style diagnosis. In that shape, gene resolution is not the answer; the load-bearing step is within-gene disease-family discrimination by the patient's specific HPO pattern. phenotype.retrieve_gene_disease_associations returns the GenCC primary gene-disease association set for supplied genes. phenotype.compare_disease_evidence uses that association set as the gene-derived candidate universe and uses HPO disease annotations only for phenotype terms. Use phenotype.compare_gene_hpo_evidence for HPO IDs, patient-specific phenotypes, rare-disease phenotype matching, or single-subject causal-gene questions. Keep this phenotype/HPO evidence separate from population-trait, drug-target, and perturbation evidence. When HPO IDs are available, pass them so public phenotype-to-gene annotation can be checked across the full candidate set. Do not pick a gene from partially reviewed evidence; gather better source support or state that the source evidence is incomplete.

Source Review

Use the investigation guidance to decide which source to review next:

  • ClinVar for exact variant assertions and review status.
  • gnomAD for public population frequency when an exact allele matters.
  • ClinGen and GenCC for gene-disease validity.
  • GeneReviews for inheritance, mechanism, penetrance, and disease context.
  • GeneCards for gene aliases, function, pathways, and disease-association triage.
  • MalaCards for disease aliases, phenotype context, and associated genes.
  • NCI cancer genetics for hereditary cancer background and counseling boundaries.
  • COSMIC Cancer Gene Census for cancer-gene role context, not standalone germline-risk evidence.
  • HPO for phenotype identifiers and synonyms.
  • MONDO for disease identifiers, aliases, and ontology context.
  • Orphanet and OMIM for rare disease phenotype and gene relationship context.

Evidence Checks

For active genome evidence:

  • Use variant.gather_gene_context for selected genes.
  • Use variant.gather_allele_context for selected exact alleles.
  • Use active_genome_index.classify_genotype_support before personal wording about an observed allele.
  • Use active_genome_index.classify_region_callability before negative or absence wording.
  • Use gnomad.fetch_population_frequency when public frequency is missing and would change interpretation.

For phenotype-first ranking, use reviewed records with source-backed fields or support spans. Direct answers require a source to support both the candidate and the relevant phenotype, disease, or HPO context.

Answering

Mention Active Genome Index use only when it changes the result, limitation, or next action. Keep risk language qualitative unless a cited source gives a quantitative estimate. Recommend clinical genetics confirmation for medical decisions.

Show full SKILL.md (454 more words)Show less

Cross-Capability Synthesis

A scope-limited result from this capability is not a final user-facing answer when other Genomi capabilities can contribute orthogonal evidence to the same question. Returning "cannot answer" while applicable capabilities remain unexamined is a host-agent failure mode.

Tools

phenotype.compare_disease_evidence

Compare supplied or primary gene-derived diseases against phenotype/HPO evidence without selecting the diagnosis.

Use when: Compares phenotype/HPO terms against supplied diseases, disease source records, or primary gene-disease associations. Uses GenCC primary gene-disease associations as the gene-derived disease candidate universe when gene symbols are supplied.

Why necessary: Candidate diseases must be compared against phenotype/HPO evidence without letting the tool choose a diagnosis.

Result semantics: Returns phenotype/disease evidence rows, disease identifiers, HPO overlap counts, and source coverage; the host agent chooses the answer. The tool uses primary gene-disease retrieval for enumeration and HPO disease annotations for phenotype terms.

phenotype.compare_gene_hpo_evidence

Compare candidate genes using phenotype, HPO, and curated rare-disease annotation evidence only.

Use when: Returns phenotype, HPO, OMIM, Orphanet, and rare-disease annotation evidence for candidate genes.

Why necessary: Rare-disease candidate genes need HPO/phenotype evidence, not GWAS, drug-target, or pathway priors.

Not for: common-trait GWAS ranking, drug-target evidence, or medication response.

Example prompts: Which of these genes best matches ataxia and microcephaly?

Result semantics: Returns source-local phenotype/HPO evidence only; the host agent decides whether this prior matches the question.

phenotype.normalize_terms

Normalize phenotype text and HPO IDs into public evidence-review targets.

Use when: Normalizes supplied HPO IDs or free-text phenotypes into public evidence-review targets.

Why necessary: Free-text symptoms need normalization before HPO and rare-disease tools can compare them reliably.

Result semantics: Returns lexical phenotype normalization and safe public targets; it does not diagnose or call external ontology APIs.

phenotype.plan_risk_investigation

Plan rare disease, cancer risk, carrier-relevance, or observed-condition investigation from public targets and optionally selected Active Genome Index evidence.

Use when: Returns rare disease, hereditary disease, hereditary cancer, cancer-risk-gene, carrier-relevance, observed-condition, and disease-gene source-review plans. Can include selected active-genome-index review targets when explicitly supplied or approved.

Why necessary: Broad disease and cancer-risk questions need declared source-review boundaries before any personal-risk wording.

Example prompts: Any inherited disease or cancer-risk findings worth following up?

Result semantics: Returns structured investigation guidance, relevant public source classes, reviewed-research gaps, and optional selected active-genome-index candidate_review_groups. Without include_active_genome_index or explicit matches, the operation stays public-only. GeneCards and MalaCards are treated as context sources that require cross-checking before clinical, carrier, or personal-risk wording.

phenotype.retrieve_gene_disease_associations

Retrieve primary gene-disease associations from GenCC for supplied gene symbols.

Use when: Returns GenCC primary gene-disease associations for supplied genes, filtered to declared validity classifications.

Why necessary: Gene-disease validity should come from primary association sources before phenotype matching or diagnosis-like wording.

Result semantics: Returns a primary gene-disease candidate universe for downstream phenotype/HPO comparison. Does not ingest agent-supplied source records and does not diagnose.

© exon-research, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/rare-disease-cancer of exon-research/genomi.

Open the folder on GitHubat commit 1df4f5b

Compare with similar skills

Rare Disease Cancer 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.

Rare Disease Cancer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Rare Disease Cancer this skillexon-research/genomi484—~2.7kAutomated safety check: PassApache-2.0
Alphagenome Single Variant Analysisgoogle-deepmind/science-skills3.2k2 repos~3kAutomated safety check: NotesApache-2.0
13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills48k1 repos~3.2kAutomated safety check: PassMIT
Clinvar Databasegoogle-deepmind/science-skills3.2k2 repos~3.9kAutomated safety check: NotesApache-2.0
Metabolic Study Planneraiming-lab/AutoResearchClaw15k—~1.9kAutomated safety check: PassMIT
Dbsnp Databasegoogle-deepmind/science-skills3.2k2 repos~3.4kAutomated safety check: NotesApache-2.0

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Questions about Rare Disease Cancer

What does Rare Disease Cancer do?

Plan rare disease, hereditary disease, cancer risk, carrier-relevance, and observed-condition source investigation from public targets or selected active genome evidence. Rare Disease Cancer is an agent skill from exon-research/genomi. Plan rare disease, hereditary disease, cancer risk, carrier-relevance, and observed-condition source investigation from public targets or selected active genome evidence.

When should I use Rare Disease Cancer?

Rare Disease Cancer fits situations like: tasks that involve Bioinformatics.

How do I install Rare Disease Cancer in Claude Code?

Run `npx skills add exon-research/genomi --skill rare-disease-cancer -a claude-code`. Or copy the skill folder (skills/rare-disease-cancer in exon-research/genomi) into .claude/skills/rare-disease-cancer in your project. Claude Code loads it when a task matches its description.

How do I install Rare Disease Cancer in Codex?

Run `npx skills add exon-research/genomi --skill rare-disease-cancer -a codex`. Or copy the skill folder (skills/rare-disease-cancer in exon-research/genomi) into .agents/skills/rare-disease-cancer in your project. Codex loads it when a task matches its description.

Can I use Rare Disease Cancer 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 exon-research/genomi --skill rare-disease-cancer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rare-disease-cancer, .gemini/skills/rare-disease-cancer, .github/skills/rare-disease-cancer and .opencode/skills/rare-disease-cancer in your project.

What does Rare Disease Cancer need to run?

SKILL.md names no scripts, command-line tools or credentials: Rare Disease Cancer is instructions for the agent only.

Does Rare Disease Cancer 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 Rare Disease Cancer 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 Rare Disease Cancer use?

Rare Disease Cancer is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Rare Disease Cancer use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Rare Disease Cancer?

Skills that share tags, products or a category with Rare Disease Cancer: Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars), Clinvar Database (google-deepmind/science-skills, 3.2k stars) and Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Rare Disease Cancer?

exon-research (a GitHub organization) maintains it in exon-research/genomi, which has 484 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on August 31, 2026.

Source: exon-research/genomi on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.