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 hollandkevint/data-product-operator --skill healthcare-data-readiness-debriefgit clone --depth 1 https://github.com/hollandkevint/data-product-operatorWrote 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/hollandkevint/data-product-operator/healthcare-data-readiness-debrief)<a href="https://agentmods.dev/skills/hollandkevint/data-product-operator/healthcare-data-readiness-debrief"><img src="https://agentmods.dev/badge/skills/hollandkevint/data-product-operator/healthcare-data-readiness-debrief/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/hollandkevint/data-product-operator/healthcare-data-readiness-debrief"><img src="https://agentmods.dev/badge/skills/hollandkevint/data-product-operator/healthcare-data-readiness-debrief.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 | $0.00059 | $0.02321 |
| Opus 5.5 | $0.00024 | $0.00928 |
| Sonnet 5.5 | $0.00012 | $0.00464 |
| Haiku 4.5 | $0.00006 | $0.00232 |
Grade A, and why
healthcare-data-readiness-debrief 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Healthcare Data Readiness Debrief
Help a healthcare data professional answer: What made this project's data preparation hard, what remains unresolved, and what should we check next?
Work on one project and one intended use. A retrospective can end with lessons for the next project. An active project should end with an evidence request or check that helps its owner make the next decision.
Using this file
Read the questions as a worksheet, or give this file and the relevant linked reference to your team's approved AI assistant. Start with an approved summary of one project. Ask for one question at a time, or request a brief from the summary. Say “brief now” to stop the interview. No patient records or database access are needed.
The output is a short brief with the intended use, what happened, unresolved questions, next checks and owners to confirm. The instructions below guide the assistant; you do not need to answer every question in this file.
See a complete fictional brief · Browse synthetic scenarios · Setup and testing limits · Install in Codex or Claude Code · Full skill library
Keep the supporting files with this skill. If your assistant cannot open a reference, supply that file separately. No other skill or plugin is required. Use approved summaries or synthetic examples, not patient records, credentials, confidential contracts or restricted study materials. This debrief does not audit a dataset or approve a launch. Your chosen assistant's data-handling rules still apply.
Instructions for the assistant
Start with their account
Read any supplied summary first. If it answers a question below, do not ask it again. If nothing was supplied, open with:
“What was someone supposed to be able to do with the data in the project you want to review?”
Ask one question per turn. Follow the uncertainty that most affects the intended use. Offer a brief after a few useful exchanges, but do not hide a material dependency to meet a question limit. If the user requests a brief now, produce it without restarting intake. Accept “unknown” and put it in the output with a way to resolve it.
What ships with it
6 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.
- 1mo ago Changed · +10 lines 9237254d00c9
- 1mo ago First seen · 120 lines · 59 tokens per session scan A c7543f81fbef
healthcare-data-readiness-debrief is a skill published in the GitHub repository hollandkevint/data-product-operator (5 stars, last pushed 4d ago), licensed MIT. It adds 59 tokens to every session and 2,321 once invoked, about $0.0002 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 2026-09-09.
healthcare-data-readiness-debrief compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| healthcare-data-readiness-debriefhollandkevint/data-product-operator | Skill | 5 | 4d ago | MIT | A | 59 | Claude Code |
| shipkyle-chalmers/ticketwright | Skill | 4 | 2d ago | MIT | A | 50 | Claude Code |
| ticketkyle-chalmers/ticketwright | Skill | 4 | 2d ago | MIT | A | 48 | Claude Code |
| reviewkyle-chalmers/ticketwright | Skill | 4 | 2d ago | MIT | A | 40 | Claude Code |
| close-daype-menezes/pm-chief-of-staff | Skill | 5 | 3d ago | MIT | A | 25 | Claude Code |
| process-meetingpe-menezes/pm-chief-of-staff | Skill | 5 | 3d ago | MIT | A | 124 | Claude Code |
| prep-conversationpe-menezes/pm-chief-of-staff | Skill | 5 | 3d ago | MIT | A | 135 | Claude Code |