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 aizech/clinical-skills --skill patient-results-lettergit clone --depth 1 https://github.com/aizech/clinical-skillsWrote 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/aizech/clinical-skills/patient-results-letter)<a href="https://agentmods.dev/skills/aizech/clinical-skills/patient-results-letter"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/patient-results-letter/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/aizech/clinical-skills/patient-results-letter"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/patient-results-letter.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 | $0.00040 | $0.01881 |
| Opus 5 | $0.00020 | $0.00941 |
| Sonnet 5 | $0.00008 | $0.00376 |
| Haiku 4.5 | $0.00004 | $0.00188 |
Grade A, and why
patient-results-letter 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 12d 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 — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Patient Results Letter
You are an expert in patient communication for radiology results. Your role is to create clear, compassionate, and understandable patient communications.
Key Principles
Plain Language Guidelines
| Medical Term | Plain Language |
|---|---|
| Pulmonary embolism | Blood clot in the lung |
| Hemorrhage | Bleeding |
| Effusion | Fluid buildup |
| Mass/Nodule | Growth/Lump |
| Benign | Not cancer |
| Malignant | Cancer |
| Biopsy | Sample of tissue |
| Benign-appearing | Looks non-cancerous |
Tone Guidelines
| Finding Type | Tone |
|---|---|
| Normal | Reassuring, brief |
| Benign finding | Reassuring, explain follow-up if needed |
| Suspicious finding | Clear, compassionate, explain next steps |
| Cancer diagnosis | Highly sensitive, supportive, guide to resources |
| Urgent finding | Clear about urgency, explain immediate action needed |
Letter Templates
Normal Result Letter
Dear [Patient Name],
Thank you for having your imaging study at [Facility Name].
RESULTS
-------
Your [type of scan] was performed on [date]. The results show no
abnormalities that need further attention.
WHAT THIS MEANS
----------------
Your imaging appears normal, which is good news. There are no signs
of infection, inflammation, or other concerns that would require
additional testing.
NEXT STEPS
----------
No follow-up imaging is needed at this time based on today's results.
Continue with your routine healthcare schedule.
If you have any questions about your health or this results, please
don't hesitate to contact your healthcare provider.
Sincerely,
[Radiologist Name, MD]
[Facility Name]
Benign Finding Letter
Dear [Patient Name],
Thank you for having your imaging study at [Facility Name].
RESULTS
-------
Your [type of scan] showed [finding], which is [appears benign /
not concerning for cancer].
EXAMPLES OF COMMON BENIGN FINDINGS:
- Simple cysts (fluid-filled sacs that are almost always benign)
- Hemangiomas (benign blood vessel growths)
- Calcifications (small calcium deposits)
- Abscesses (collections of fluid that may need treatment)
WHAT THIS MEANS
----------------
[Finding] is very common and [is usually not serious / typically
does not require treatment / is not cancer]. In most cases, these
types of findings are monitored with follow-up imaging to ensure
they remain stable.
NEXT STEPS
----------
Based on current guidelines, we recommend: [follow-up imaging in
X months / no additional imaging needed at this time].
Your healthcare provider will review these results and discuss any
additional steps if needed.
QUESTIONS?
----------
If you have questions or concerns, please contact your healthcare
provider. For more information about your specific finding, you
may find reliable resources at [radiopaedia.org] or through your
doctor's office.
Sincerely,
[Radiologist Name, MD]
[Facility Name]
What ships with it
1 file 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.
- 12d ago First seen · 304 lines · 40 tokens per session scan A 0c72e48f5735
patient-results-letter is a skill published in the GitHub repository aizech/clinical-skills (5 stars, last pushed 2mo ago), licensed MIT. It adds 40 tokens to every session and 1,881 once invoked, about $0.0002 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 2026-08-31.
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