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Generate a concise weekly progress summary for the pharma_skills repository. Use this to summarize recent commits, PRs, and issues, then post the update to Slack and save it as a markdown file.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Simulates an independent statistical reviewer auditing a clinical trial submission package (SDTM, ADaM, TLG/TLF, SAP, CSR). Use when the user provides clinical trial datasets, tables, listings, figures, analysis outputs, or submission materials and wants an independent check of correctness, consistency, traceability, or data realism. Reviews denominators, populations, endpoints, multiplicity, safety summaries, cross-layer links from TLF to ADaM to SDTM/source, and whether data looks clinically plausible. Trigger on requests to review TLFs, audit a submission package, verify an analysis, reproduce endpoints, check SDTM/ADaM, assess data quality, or detect fabricated or unrealistic trial data across any therapeutic area.
Derives an ADaM Subject-Level Analysis Dataset (ADSL) using the {admiral} R package and pharmaverse ecosystem. Use when a user needs to create ADSL from SDTM domains, derive standard subject-level variables (treatment dates, disposition, demographics, population flags), or generate QC-ready R code following CDISC ADaM conventions. Requires SDTM input data and an ADaM spec.
Parent skill for the admiral ADaM derivation family. Covers shared conventions used across all admiral child skills: library setup, pipe style, date derivation rules, flag variable conventions, and QC patterns. Route to a child skill for dataset-specific derivation workflows.
Design and simulate clinical trials using the TrialSimulator R package and produce a QC-ready build-order-spine report that pairs each block of code with rationale, parameters, and operating characteristics.
Auto-discover all skills with evals in RConsortium/pharma-skills, benchmark each with vs. without skill using matched isolated sessions, and post scored results to the linked GitHub issue. Use whenever someone says "run benchmarks", "compare skill performance", "eval the skills", or wants to measure whether a skill improves output quality.
Converts one or more GitHub Issues into standardized benchmark data using automated scripts. Use when a user provides an issue number or URL and wants to add it to the evaluation suite.
| name | weekly-summary |
| description | Generate a concise weekly progress summary for the pharma_skills repository. Use this to summarize recent commits, PRs, and issues, then post the update to Slack and save it as a markdown file. |
This skill automates the generation of a developer-focused weekly summary for the RConsortium/pharma_skills repository.
Before running, read _automation/weekly-summary/config.json to load:
max_words — word limit for the summary (default 150)slack_channel — Slack channel ID to post to (overridden by PHARMA_SKILLS_SLACK_CHANNEL env var)lookback_days — how many days of activity to include (default 7)If PHARMA_SKILLS_SLACK_CHANNEL is set in the environment, it takes precedence over config.json.
If neither is set, stop and report an error — do not guess a channel ID.
Research Recent Activity
python3 _automation/weekly-summary/scripts/get_weekly_data.py
Generate Summary
max_words words (from config) in Slack mrkdwn format.Slack Output
PHARMA_SKILLS_SLACK_CHANNEL, falling back to slack_channel in config.json.File Output
/sessions/[session-dir]/mnt/outputs/pharma-skills-weekly-summary-[YYYY-MM-DD].md.