Borrowing it
Nothing to install: this file belongs to omar-A-hassan/medsci-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/omar-A-hassan/medsci-agent/main/.opencode/skills/opentargets/SKILL.mdgit clone --depth 1 https://github.com/omar-A-hassan/medsci-agentWrote 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/omar-a-hassan/medsci-agent/opentargets)<a href="https://agentmods.dev/skills/omar-a-hassan/medsci-agent/opentargets"><img src="https://agentmods.dev/badge/skills/omar-a-hassan/medsci-agent/opentargets/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/omar-a-hassan/medsci-agent/opentargets"><img src="https://agentmods.dev/badge/skills/omar-a-hassan/medsci-agent/opentargets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00016 | $0.00421 |
| Opus 5.5 | $0.00006 | $0.00168 |
| Sonnet 5.5 | $0.00003 | $0.00084 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
opentargets scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
r = requests.post(OT_URL, json={"query": query, "variables": {"id": "ENSG00000141510"}}) What it actually says
Open Targets Platform
Overview
Open Targets integrates genetics, genomics, transcriptomics, drugs, and literature to score target-disease associations. It uses evidence from GWAS, differential expression, pathways, drugs, and more.
GraphQL API
import requests
OT_URL = "https://api.platform.opentargets.org/api/v4/graphql"
query = """
query target($id: String!) {
target(ensemblId: $id) {
approvedSymbol
approvedName
associatedDiseases(page: {index: 0, size: 5}) {
rows {
disease { id name }
score
datatypeScores { componentId score }
}
}
}
}
"""
r = requests.post(OT_URL, json={"query": query, "variables": {"id": "ENSG00000141510"}})
data = r.json()["data"]["target"]
Search
search_q = 'query search($q: String!) { search(queryString: $q, entityNames: ["target"], page: {index: 0, size: 5}) { hits { id name entity } } }'
r = requests.post(OT_URL, json={"query": search_q, "variables": {"q": "BRAF"}})
Key Details
- Association score: 0-1 combining all evidence datatypes.
- Datatypes: genetic_association, somatic_mutation, known_drug, affected_pathway, literature, rna_expression, animal_model.
- Target IDs: Ensembl gene IDs (ENSG...). Disease IDs: EFO or MONDO IDs.
- No API key required; rate limit ~10 req/s.
- Use
associatedTargetson disease nodes for reverse lookups. - Genetics Portal provides variant-to-gene (V2G) and colocalisation data.
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 · 47 lines · 16 tokens per session scan A bf658a5488fe
opentargets is a skill published in the GitHub repository omar-A-hassan/medsci-agent (17 stars, last pushed 2mo ago), licensed MIT. It adds 16 tokens to every session and 421 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
opentargets compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| opentargetsomar-A-hassan/medsci-agent | Skill | 17 | 2mo ago | MIT | A | 16 | OpenCode |
| build-expression-treejimmc414/claude-code-plugin-marketplace | Skill | 4 | yesterday | MIT | A | 24 | Claude Code |
| find-convex-hulljimmc414/claude-code-plugin-marketplace | Skill | 4 | yesterday | MIT | A | 31 | Claude Code |
| dfam-checkearthtojake/text-to-cad | Skill | 26k | yesterday | MIT | A | 117 | Claude Code, Codex |
| peer-reviewxintaofei/codeg | Skill | 4.2k | 6d ago | Apache-2.0 | A | 71 | Claude Code |
| scientific-critical-thinkingxintaofei/codeg | Skill | 4.2k | 6d ago | Apache-2.0 | A | 63 | Claude Code |
| tooluniverse-phylogeneticsmims-harvard/ToolUniverse | Skill | 1.8k | yesterday | Apache-2.0 | A | 155 | Claude Code |