target-disease-research
Skill140 starsChanged 27 days agoMITView on GitHub
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.
In this repository6 other files it gives its agents.
- minimal-rigorous-workSkill
- agent-harness-pr-regressionSkill
- research-workflowSkill
- argus-runtime-orchestrationSkill
- argus-runSkill
- argus-statusSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 14
Stop if the request contains patient-identifying information and ask for a de-identified research question.
- Very specific: line 19
Call argus_message exactly once with an objective that asks Manager to select the medical vertical (shipped by the argus-verticals package) …
- Distinctive: line 26
Treat PubMed metadata as metadata, not full-text verification.
- Distinctive: line 33
Only describe a dossier as reviewed when Argus returns a Reviewer-certified state.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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.
- Require a target and disease. Capture aliases, population or subtype, date bounds, intervention class, exclusions, decision question, and output language when supplied.
- Stop if the request contains patient-identifying information and ask for a de-identified research question.
- Reuse only the project-resolution part of
argus-run: callargus_project_listfor the exact work directory, then reuse that project or callargus_project_create. Do not dispatch while resolving the project. - Call
argus_messageexactly once with an objective that asks Manager to select themedicalvertical (shipped by theargus-verticalspackage) and to produce:medical/evidence.jsonl,medical/evidence_matrix.csv,medical/target_disease_memo.md, andmedical/review.json. - Require source IDs and URLs, exact retrieval/query provenance, conflicts, failures, missing fields, and a separate infrastructure-failure count.
- 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.
- Return the project ID. Use
argus-statusfor 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.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

