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.
npx skills add PKU-YuanGroup/OpenAI4S --skill bio-clinical-biostatistics-cdisc-data-handlinggit clone --depth 1 https://github.com/PKU-YuanGroup/OpenAI4SWrote 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/pku-yuangroup/openai4s/bio-clinical-biostatistics-cdisc-data-handling)<a href="https://agentmods.dev/skills/pku-yuangroup/openai4s/bio-clinical-biostatistics-cdisc-data-handling"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-clinical-biostatistics-cdisc-data-handling/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/pku-yuangroup/openai4s/bio-clinical-biostatistics-cdisc-data-handling"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-clinical-biostatistics-cdisc-data-handling.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 | $0.00136 | $0.07958 |
| Opus 5 | $0.00068 | $0.03979 |
| Sonnet 5 | $0.00027 | $0.01592 |
| Haiku 4.5 | $0.00014 | $0.00796 |
Grade A, and why
bio-clinical-biostatistics-cdisc-data 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.
This is a copy
100% identical to bio-clinical-biostatistics-cdisc-data — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 492 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: pyreadstat 1.2+, pandas 2.1+, numpy 1.26+. CDISC standards referenced: SDTM 2.0 / SDTMIG 3.4 (SDTM 3.0 / SDTMIG 4.0 in public review through April 2026); ADaMIG v1.3 (2021); OCCDS v1.1 (Nov 2021); BDS-for-TTE v1.0; Define-XML 2.1 (FDA-recommended for studies starting on/after March 15, 2023); Dataset-JSON v1.1 (Dec 2024; FDA Federal Register notice April 2025); Pinnacle 21 Community 4.0+; CORE (CDISC Open Rules Engine, 2021). Define-XML 2.1 FDA support began March 15, 2021 and is required for studies starting on/after March 15, 2023.
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - R packages cited (essential for ADaM derivation): admiral (Roche/openpharma), metacore, metatools, xportr
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
CDISC SDTM and ADaM Data Handling
"Load clinical trial data" -> Parse CDISC SDTM domain files; build or consume ADaM analysis-ready datasets; preserve subject-level and event-level structure; respect traceability and validation expectations for regulatory submission.
- Python:
pyreadstat.read_xport(),pd.read_sas(),pd.merge() - R:
haven::read_xpt(),admiralfor ADaM derivation,Pinnacle21orCOREfor validation
Aggregation Strategy Taxonomy -- Choose the Right Question
| Strategy | Scientific question answered | Example endpoint | Fails when |
|---|---|---|---|
| Any event (binary) | Does treatment change probability of experiencing the event at all? | Had any serious AE: Yes/No | Treatment changes event burden but not anyone-event probability |
| Event count | Does treatment change burden of events per patient? | Total AE count per subject | Subjects with 1 vs 10 events treated equivalently |
| Maximum severity | Does treatment shift patients toward more severe manifestations? | Worst AESEV per subject | Confounded with event count (more events -> higher chance of severe) |
| First event + time | Does treatment delay onset of the event? | Time to first serious AE (TTE) | Multiple events per subject ignored |
| Rate (events per person-time) | What is the per-time-unit rate? | AEs per subject-year | Requires exposure-time tracking; differential dropout biases rates |
| Composite (per ICH E9 R1) | Event becomes part of endpoint definition | Death = treatment failure | Direction of components conflict; needs hierarchy |
What ships with it
2 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.
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.
- 9d ago First seen · 492 lines · 136 tokens per session scan A 9ac30ee0f63f
bio-clinical-biostatistics-cdisc-data is a skill published in the GitHub repository PKU-YuanGroup/OpenAI4S (407 stars, last pushed yesterday), licensed MIT. It adds 136 tokens to every session and 7,958 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to bio-clinical-biostatistics-cdisc-data, differing in 12 lines, and is treated as a copy.
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