target-disease-research

target-disease-research is a skill for Claude Code, Codex from lbx154/Argus. It costs 40 tokens per session (392 once invoked), scanned A, original, MIT.

A research workflow for investigating how a biological target relates to a disease, including human evidence, clinical trials, safety, and failed programs. It is intended for pharmaceutical portfolio decisions, not patient diagnosis or treatment selection.

In plain words
What is it for?
It helps produce an evidence file, comparison table, target-disease report, and review record for a defined target and disease, with source identifiers and retrieval details.
Why use it?
It organizes evidence and records sources, search details, disagreements, missing information, and infrastructure failures. This makes the research auditable and separates confirmed evidence from assumptions.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the argus plugin — 3 skills, 1 MCP server shipped together

Good fit It helps produce an evidence file, comparison table, target-disease report, and review record for a defined target and disease, with source identifiers and retrieval details.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lbx154/argus/target-disease-research
View source ↗ lbx154/Argus
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 lbx154/Argus --skill target-disease-research
Clone the repo
git clone --depth 1 https://github.com/lbx154/Argus

Made for: Claude Code, Codex.

Or install argus, the plugin that ships this one along with the rest of its 3 skills, 1 MCP server.

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 target-disease-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/lbx154/argus/target-disease-research/github.svg)](https://agentmods.dev/skills/lbx154/argus/target-disease-research)
Your own site
<a href="https://agentmods.dev/skills/lbx154/argus/target-disease-research"><img src="https://agentmods.dev/badge/skills/lbx154/argus/target-disease-research/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 target-disease-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/lbx154/argus/target-disease-research"><img src="https://agentmods.dev/badge/skills/lbx154/argus/target-disease-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 392 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 $0.00040 $0.00392
Opus 5 $0.00020 $0.00196
Sonnet 5 $0.00008 $0.00078
Haiku 4.5 $0.00004 $0.00039

Measured 9d ago against content hash 186141aeedc5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

target-disease-research 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 9d 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.

plugins/argus/skills/target-disease-research/SKILL.md · 34 lines

What it actually says

Target-Disease Research

This workflow supports pharmaceutical research and portfolio decisions. It does not diagnose a patient, select treatment, or assert that a new drug was created.

  1. Require a target and disease. Capture aliases, population or subtype, date bounds, intervention class, exclusions, decision question, and output language when supplied.
  2. Stop if the request contains patient-identifying information and ask for a de-identified research question.
  3. Reuse only the project-resolution part of argus-run: call argus_project_list for the exact work directory, then reuse that project or call argus_project_create. Do not dispatch while resolving the project.
  4. Call argus_message exactly once with an objective that asks Manager to select the built-in medical vertical and to produce: medical/evidence.jsonl, medical/evidence_matrix.csv, medical/target_disease_memo.md, and medical/review.json.
  5. Require source IDs and URLs, exact retrieval/query provenance, conflicts, failures, missing fields, and a separate infrastructure-failure count.
  6. Treat PubMed metadata as metadata, not full-text verification. Treat trial registration as trial existence/design, not evidence of efficacy. Qualify cross-trial comparisons unless population, endpoint, comparator, follow-up, treatment line, and data cutoff align.
  7. Return the project ID. Use argus-status for later progress or artifact inspection instead of polling in the same turn.

Only describe a dossier as reviewed when Argus returns a Reviewer-certified state. Preserve negative and contradictory evidence.

Files

What ships with it

1 file 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.

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. 9d ago First seen · 34 lines · 40 tokens per session scan A 186141aeedc5

Subscribe to this mod's changes

target-disease-research is a skill published in the GitHub repository lbx154/Argus (317 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 392 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.

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