drug-targets

drug-targets is a skill for Claude Code, Codex from exon-research/genomi. It costs 31 tokens per session (1,018 once invoked), scanned A, original, Apache-2.0.

A research skill for finding genes linked to how drugs work and for prioritising possible drug targets. It uses public records about drugs, mechanisms, diseases, and candidate genes.

In plain words
What is it for?
Reviewing drug targets, mechanisms of action, disease-specific clinical candidates, drug classes, and candidate gene lists.
Why use it?
It separates direct evidence that a drug acts on a gene from weaker evidence that a gene is merely associated with a disease.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Reviewing drug targets, mechanisms of action, disease-specific clinical candidates, drug classes, and candidate gene lists.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/exon-research/genomi/drug-targets
Install

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.

Any agent
npx skills add exon-research/genomi --skill drug-targets
Clone the repo
git clone --depth 1 https://github.com/exon-research/genomi

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for drug-targets

README.md
[![agentmods](https://agentmods.dev/badge/skills/exon-research/genomi/drug-targets/github.svg)](https://agentmods.dev/skills/exon-research/genomi/drug-targets)
Your own site
<a href="https://agentmods.dev/skills/exon-research/genomi/drug-targets"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/drug-targets/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.

agentmods 80×15 button for drug-targets

Your own site · 80×15
<a href="https://agentmods.dev/skills/exon-research/genomi/drug-targets"><img src="https://agentmods.dev/badge/skills/exon-research/genomi/drug-targets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,018 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.01018
Opus 5 $0.00015 $0.00509
Sonnet 5 $0.00006 $0.00204
Haiku 4.5 $0.00003 $0.00102

Measured 11d ago against content hash 05321c8b5018, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

drug-targets 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.

skills/drug-targets/SKILL.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Drug Targets

Use this skill for disease-scoped clinical drug-target retrieval, direct drug-target records, PharmaProjects-style target context, ChEMBL mechanism genes, DrugBank target context, or candidate-gene review for a drug, drug class, or mechanism.

Contract

  • Direct drug-target or mechanism evidence outranks target-disease association scores and GWAS-style association.
  • ChEMBL, DrugBank, and PharmaProjects-style records can support direct target claims when the source supports both the gene and the drug, class, mechanism, or indication context.
  • Open Targets association context is useful for review; direct drug-target evidence comes from source records that support the drug, class, or mechanism relationship.
  • Open Targets disease drug and clinical candidate records can retrieve disease-scoped clinical drug-target genes when the drug target comes from a mechanism-of-action row.
  • Treat returned rankings as source evidence. The agent decides whether the drug-target prior matches the question. When using cross-source comparison, use prior_fit before reading a panel as task-relevant and audit decision_evidence before answering.

Tool Flow

  1. phenotype.retrieve_disease_drug_targets retrieves Open Targets clinical drug candidate target genes for a supplied disease anchor.
  2. phenotype.compare_drug_target_evidence compares candidate genes against direct drug-side context: drug, drug class, or mechanism.
  3. If source support is missing, use research.list_sources to choose direct target sources, review them, and store narrow findings with research.record.
  4. Re-run the same selected tool after recording reviewed findings.

Example:

  • phenotype.retrieve_disease_drug_targets with {"disease":"asthma","genes":["ADRB2","IL13"]}
  • phenotype.compare_drug_target_evidence with {"drug_class":"beta agonist","phenotype":"asthma","genes":["ADRB2","IL13"],"source_records":[{"genes":["ADRB2"],"drug_class":"beta agonist","verified_fields":{"genes":["ADRB2"],"drug_class":"beta agonist"},"support_spans":[{"field":"genes","text":"source-backed ADRB2 text"}]}]}

Read the full file on GitHub · 102 lines

Changes

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.

  1. 11d ago First seen · 102 lines · 31 tokens per session scan A 05321c8b5018

Subscribe to this mod's changes

drug-targets is a skill published in the GitHub repository exon-research/genomi (482 stars, last pushed 10d ago), licensed Apache-2.0. It adds 31 tokens to every session and 1,018 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

release-doi

A release procedure for research repositories that publish versions with a DOI, a permanent identifier for scholarly work, through Zenodo.

shimo4228/claude-harness · 126 tokens

autoresearch

Canonical around-the-clock research loop. Defines the agent's outer loop — read taste corpus + queue, pick the next experiment, mutate the explicitly-declared mutation surface, run the experiment under a hard time budget against a frozen metric, score, codify, repeat. Augmented with Karpathy's sharp primitives (frozen…

Rockielab/rockie-claude · 106 tokens

experiment

Run a materials-science / ML compute job on Rockie GPU capacity. Trigger words "run experiment", "submit job", "/experiment", or requests to quote/approve GPU spend before an experiment. Picks the right GPU type and count from a natural-language description (DFT for QE/VASP/ABINIT, MD for GROMACS/LAMMPS/OpenMM…

Rockielab/rockie-claude · 141 tokens

physics

Route physics simulation, modeling, validation, and research-compute requests across force fields, molecular dynamics, electronic structure, particle transport/collision, continuum multiphysics, plasma/PIC, nuclear/radiation, and astro/cosmology. Use open-source-first engines, refuse local heavyweight execution on the…

Rockielab/rockie-claude · 75 tokens

sota-delta

Track 3 quickstart wrapper that reproduces a paper or repository baseline on Rockie GPU, then extends it with a user-specified delta and compares baseline versus delta.

Rockielab/rockie-claude · 39 tokens

post-run-review

After an experiment finishes, structured review emits {isbug, failureclass, summary, metric, lowerisbetter}, auto-closes the journal node, emits a [LEARN] block when isbug=true, and files a [DEAD-END] when the failureclass is "bad-hypothesis". Use immediately after any training/eval run — the agent invokes this…

Rockielab/rockie-claude · 91 tokens