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Agent Orchestration
Skill

/target-disease-research

Use when researching a biomedical target and disease relationship, mechanism, human evidence, clinical translation, safety, failed programs, competitive trials, or an auditable pharmaceutical decision dossier.

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From plugin
argusagent
1413 skills1 MCP
Install
$ npx -y skills add microsoft/ArgusAgent --skill target-disease-research --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/target-disease-research

Context preview

The summary Claude sees to decide when to auto-load this skill.

Use when researching a biomedical target and disease relationship, mechanism, human evidence, clinical translation, safety, failed programs, competitive trials, or an auditable pharmaceutical decision dossier.

SKILL.md

target-disease-research.SKILL.md
name: target-disease-research
description: Use when researching a biomedical target and disease relationship, mechanism, human evidence, clinical translation, safety, failed programs, competitive trials, or an auditable pharmaceutical decision dossier.

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 `medical` vertical (shipped by the `argus-verticals` package) 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.

Read more
Ships withargusagent

A persistent, reviewed multi-agent runtime for long-horizon research and engineering.

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Python
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MIT
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Repo: microsoft/ArgusAgent

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