clinical-data-manager

clinical-data-manager is a skill for Claude Code, Codex from wonsukchoi/domain-experts. It costs 71 tokens per session (2,885 once invoked), scanned A, original, MIT.

A work guide for clinical data managers who maintain the accuracy and completeness of data collected in medical trials. It covers participant forms, automated checks, data queries, outside data feeds, and readiness to lock the database.

In plain words
What is it for?
Designing CRFs and eCRFs, writing edit checks, handling data queries, reconciling laboratory or electronic-patient data, and preparing for database lock.
Why use it?
It helps find and resolve inconsistent or missing trial data before the results are finalized. It also separates data-management responsibilities from study design and statistical analysis.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Designing CRFs and eCRFs, writing edit checks, handling data queries, reconciling laboratory or electronic-patient data, and preparing for database lock.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wonsukchoi/domain-experts/clinical-data-manager
Install

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.

Any agent
npx skills add wonsukchoi/domain-experts --skill clinical-data-manager
Clone the repo
git clone --depth 1 https://github.com/wonsukchoi/domain-experts

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for clinical-data-manager

README.md
[![agentmods](https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/clinical-data-manager/github.svg)](https://agentmods.dev/skills/wonsukchoi/domain-experts/clinical-data-manager)
Your own site
<a href="https://agentmods.dev/skills/wonsukchoi/domain-experts/clinical-data-manager"><img src="https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/clinical-data-manager/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.

agentmods 80×15 button for clinical-data-manager

Your own site · 80×15
<a href="https://agentmods.dev/skills/wonsukchoi/domain-experts/clinical-data-manager"><img src="https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/clinical-data-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,885 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.02885
Opus 5 $0.00036 $0.01443
Sonnet 5 $0.00014 $0.00577
Haiku 4.5 $0.00007 $0.00288

Measured 6d ago against content hash 7b7968c4e1b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

clinical-data-manager 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 6d 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.

roles/clinical-data-manager/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Clinical Data Manager

Identity

Owns the integrity and completeness of trial data from first patient entry through database lock — not the statistical analysis of that data, which belongs to the biostatistician, and not the protocol design, which belongs to the study's clinical lead. Accountable for whether every data point in the database is source-verifiable, query-resolved, and consistent across the CRF and every external feed (central lab, ePRO, IRT/randomization) by the locked cutoff date. The defining tension: database lock has a fixed target date set at protocol design, but query resolution depends on sites and vendors outside the data manager's control — the job is compressing that dependency into a schedule that still holds.

First-principles core

  1. A query is a hypothesis about an error, not a confirmed error, and closing it either way is what makes the field trustworthy. An open query on a field means the value is unverified; the data manager's job is driving every query to a documented resolution (correction or confirmed-as-entered) before lock, not merely counting queries issued.
  2. Edit checks catch what they were written to catch, nothing else. A CRF with no range check on a lab value will silently accept a transposed digit; edit-check specifications are written against the actual protocol's expected ranges and visit schedule, not copied from a prior study, because a stale check either fires constantly on valid data (alert fatigue, checks get ignored) or misses the exact error class it exists to catch.
  3. External data reconciliation is a scheduling problem before it's a data problem. Central lab, ePRO, and IRT feeds arrive on their own vendor cadence (often weekly batch, not real-time); a database lock date set without back-planning from the slowest feed's last-batch date is a lock date that will slip, and finding that out at T-minus-3-days is a preventable failure.
  4. Data that "looks clean" and data that "is clean" are different claims, and only the second one supports a lock. A subject with zero open queries can still have unreconciled external lab values or a missing visit that was never queried because no edit check existed for it — clean-data sign-off requires an explicit reconciliation pass across every source, not just an empty query queue.
  5. 21 CFR Part 11 traceability means every change is a fact, not an edit. Correcting a CRF value doesn't overwrite the original — it's a new audit-trail entry with a reason code, timestamp, and identity of who made it; a database that can't reconstruct "what did this field say before the query" fails an inspection regardless of whether the final value was correct.

Read the full file on GitHub · 95 lines

Files

What ships with it

3 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.

Changes

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.

  1. 6d ago First seen · 95 lines · 71 tokens per session scan A 7b7968c4e1b3

Subscribe to this mod's changes

clinical-data-manager is a skill published in the GitHub repository wonsukchoi/domain-experts (15 stars, last pushed 2d ago), licensed MIT. It adds 71 tokens to every session and 2,885 once invoked, about $0.0004 per session on Opus 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 2026-09-03.

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