synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and instructions.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/synthetic-sciences/opensciencenpx agentmods add skills/synthetic-sciences/openscience/clinical-reportsWrote 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/synthetic-sciences/openscience/clinical-reports)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/clinical-reports"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/clinical-reports/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/synthetic-sciences/openscience/clinical-reports"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/clinical-reports.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00071 | $0.08612 |
| Opus 5.5 | $0.00028 | $0.03445 |
| Sonnet 5.5 | $0.00014 | $0.01722 |
| Haiku 4.5 | $0.00007 | $0.00861 |
Grade A, and why
clinical-reports 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 1mo 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- clinical-reports — 98% identical, 16 lines differ
- clinical-reports — 97% identical, 17 lines differ
- clinical-reports — 95% identical, 19 lines differ
- clinical-reports — 95% identical, 19 lines differ
- clinical-reports-hardened — 95% identical, 23 lines differ
- clinical-reports — 95% identical, 19 lines differ
- clinical-reports — 95% identical, 16 lines differ
- clinical-reports — 95% identical, 16 lines differ
How it starts
The opening of the file, as written. The whole thing — 1,137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clinical Report Writing
Overview
Clinical report writing is the process of documenting medical information with precision, accuracy, and compliance with regulatory standards. This skill covers four major categories of clinical reports: case reports for journal publication, diagnostic reports for clinical practice, clinical trial reports for regulatory submission, and patient documentation for medical records. Apply this skill for healthcare documentation, research dissemination, and regulatory compliance.
Critical Principle: Clinical reports must be accurate, complete, objective, and compliant with applicable regulations (HIPAA, FDA, ICH-GCP). Patient privacy and data integrity are paramount. All clinical documentation must support evidence-based decision-making and meet professional standards.
When to Use This Skill
This skill should be used when:
- Writing clinical case reports for journal submission (CARE guidelines)
- Creating diagnostic reports (radiology, pathology, laboratory)
- Documenting clinical trial data and adverse events
- Preparing clinical study reports (CSR) for regulatory submission
- Writing patient progress notes, SOAP notes, and clinical summaries
- Drafting discharge summaries, H&P documents, or consultation notes
- Ensuring HIPAA compliance and proper de-identification
- Validating clinical documentation for completeness and accuracy
- Preparing serious adverse event (SAE) reports
- Creating data safety monitoring board (DSMB) reports
Visual Enhancement with Scientific Schematics
⚠️ MANDATORY: Every clinical report MUST include at least 1 AI-generated figure using the scientific-schematics skill.
This is not optional. Clinical reports benefit greatly from visual elements. Before finalizing any document:
- Generate at minimum ONE schematic or diagram (e.g., patient timeline, diagnostic algorithm, or treatment workflow)
- For case reports: include clinical progression timeline
- For trial reports: include CONSORT flow diagram
What ships with it
30 files 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.
- assets/case_report_template.md 9.5 KB
- assets/clinical_trial_csr_template.md 9.0 KB
- assets/clinical_trial_sae_template.md 10 KB
- assets/consult_note_template.md 7.2 KB
- assets/discharge_summary_template.md 12 KB
- assets/hipaa_compliance_checklist.md 12 KB
- assets/history_physical_template.md 9.0 KB
- assets/lab_report_template.md 8.3 KB
- assets/pathology_report_template.md 6.5 KB
- assets/quality_checklist.md 9.7 KB
- assets/radiology_report_template.md 7.8 KB
- assets/soap_note_template.md 7.1 KB
- IMPLEMENTATION_SUMMARY.md 18 KB
- README.md 8.4 KB
- references/case_report_guidelines.md 18 KB
- references/clinical_trial_reporting.md 20 KB
- references/data_presentation.md 21 KB
- references/diagnostic_reports_standards.md 18 KB
- references/medical_terminology.md 15 KB
- references/patient_documentation.md 21 KB
- references/peer_review_standards.md 15 KB
- references/regulatory_compliance.md 17 KB
- scripts/check_deidentification.py 10 KB runs code
- scripts/compliance_checker.py 2.1 KB runs code
- scripts/extract_clinical_data.py 2.5 KB runs code
- scripts/format_adverse_events.py 2.8 KB runs code
- scripts/generate_report_template.py 4.4 KB runs code
- scripts/terminology_validator.py 3.8 KB runs code
- scripts/validate_case_report.py 11 KB runs code
- scripts/validate_trial_report.py 2.7 KB runs code
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.
- 1mo ago Changed · +8 lines f723ab787e87
- 1mo ago Changed aaffa5c8ed35
- 1mo ago Changed a51e712ee057
- 1mo ago First seen · 1,129 lines · 71 tokens per session scan A 7a1289adfb47
clinical-reports is a skill published in the GitHub repository synthetic-sciences/openscience (4,082 stars, last pushed today), licensed Apache-2.0. It adds 71 tokens to every session and 8,612 once invoked, about $0.0003 per session on Opus 5.5. 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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