Today, I’m open-sourcing /fuck-cancer, an AI skill that helps patients and caregivers navigate cancer diagnosis and treatment and advocate for themselves and their loved ones.

Here’s what patients and caregivers have told me since I shared my mom’s story:

“You have to be a huge patient advocate. Ask questions and push for answers, biopsies, and proper testing.”

“I need help navigating difficult conversations and advocating for myself.”

“The volume of doctors, documents, and insurance paperwork can quickly become overwhelming.”

I built the skill to help with these problems. It creates and updates a practical brief with five sections:

1. Patient and care-team information for easy reference during calls

2. What to do next, limited to three specific actions

3. What we know, separating confirmed facts from what remains unclear

4. Medical terms explained in plain English

5. A care log with recent updates and decisions

It builds this brief from documents, and context you provide. When research is needed, it uses trusted sources such as the National Cancer Institute and the ClinicalTrials gov API.

I use it with ChatGPT/Codex and Claude Code to prepare for conversations and research. It can save the brief locally as a Markdown file or update a shareable Google Doc so the whole family can work from the same information.

Get the free, open-source skill here: https://github.com/petergyang/fuck-cancer/…

If you find it useful, please the repo and share it with someone going through this BS disease.

petergyang/fuck-cancer

Source: https://github.com/petergyang/fuck-cancer

Fuck Cancer

Create and update a practical brief to help patients and caregivers advocate for themselves.

https://github.com/user-attachments/assets/551549ee-4afa-4c4e-ae07-6266ec4a129d

Problem

Since I published my mom’s story, I’ve heard from many people supporting a loved one through cancer.

The last thing a patient or caregiver needs is a pile of confusing medical terms, hype, and scattered information. Instead, they need clear answers to three questions: What should we do next? What do we know? How can we advocate for ourselves?

Here’s what patients and caregivers have told me:

“You have to be a huge patient advocate. Push for answers. Push for biopsies. Push for proper testing. Ask questions.”

“I need help navigating difficult conversations and advocating for myself.”

“The volume of doctors, documents, and insurance paperwork can quickly become overwhelming.”

What this skill does

This skill creates a concise, fact-based brief with 5 sections:

1. Patient information. Essential identifiers, care team contacts, and more for easy reference during phone calls.
2. What to do next. Up to 3 specific actions naming the next steps.
3. What we know. The shortest useful summary of what’s confirmed vs. what’s still ambiguous. Can also include research on clinical trials.
4. Medical terms. Plain-English explanations of medical terms and acronyms.
5. Care log. A compact history of recent updates.

It creates this brief based on documents and context that you share with it and trusted medical sources like NCI’s PDQ summaries and the ClinicalTrials.gov API.

On first use, the skill will ask you whether to create the brief in a local Markdown file or a shareable Google Doc. You can run the skill with more context to update the brief over time.

How to install the skill

The easiest way to install the skill is to paste this into ChatGPT, Claude Code, or your favorite agent:

Install the /fuck-cancer skill globally from https://github.com/petergyang/fuck-cancer

You can also install it with npx:

npx skills add petergyang/fuck-cancer --skill fuck-cancer --global --yes

How to use the skill

Start with a brain dump:

/fuck-cancer My dad was just diagnosed. Here’s what I know.

Paste or upload a report:

/fuck-cancer Explain this report and help me prepare for doctor meeting.

Research trials or second opinions:

/fuck-cancer Find relevant trials near Toronto for this diagnosis.

Share new information as it arrives:

/fuck-cancer Update our brief with this new biomarker report.

Trusted medical sources

The skill grounds its research in trusted medical sources:

1. Evidence and treatment context: NCI’s PDQ summaries or the official cancer agency for the patient’s country.
2. Drug approvals and labels: The patient’s national regulator, such as the FDA, Health Canada, EMA, MHRA, or TGA.
3. Testing and clinical guidance: Current official publications from groups such as ASCO, ESMO, CAP, or NICE when they directly apply.
4. Clinical trials: The official ClinicalTrials.gov API, including the status of the individual site.
5. Medical definitions: The NCI Dictionary of Cancer Terms or an equivalent official national source.
6. Emerging questions: Peer-reviewed primary research indexed in PubMed, with early or indirect evidence labeled as such.
7. Specialists and services: Official academic cancer-center pages for their own clinicians, programs, and trials.

Disclaimer

The skill supports decisions with current evidence. It does not diagnose cancer, choose treatment, determine trial eligibility, or replace the patient’s medical team.

What’s inside

1. SKILL.md contains the complete care-navigation and research workflow.
2. search_trials.py searches ClinicalTrials.gov API v2, filters sites by distance from home with --near LAT,LON, labels each site’s recruitment status, and ranks likely matches first.
3. eval.md checks the destination, brief structure, action specificity, medical boundaries, and concise care-log format.
4. test_search_trials.py covers location normalization, distance filtering, site-status handling, pagination, criteria previews, and relevance ordering.
5. openai.yaml contains the Codex skill metadata.

Local Markdown mode requires no account, database, or API key. Google Doc mode uses the user’s connected Google Drive integration; if it is not connected, the skill asks the user to enable it before writing. The trial-search helper requires no API key, uses only Python’s standard library, and requires Python 3.8 or newer.

License

MIT