Generating Synthea Data

What it does

When your agent uses it

• Shareable test data for an OpenMed pipeline
• Reproducible fixtures for tests
• A held-out set for de-identification leakage gates
• Instead of touching real clinical data

Example prompts

• “Use the generating-synthea-data skill to generate synthetic but realistic patient records (FHIR R4 bundles, C-CDA documents, CSV) with MITRE Synthea…”
• “/generating-synthea-data”

Requirements

• Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

1. 1Choose scale & geography. -p N sets population; the state/location
2. 2Pick formats. Enable FHIR (exporter.fhir.export), C-CDA
3. 3Pin a seed (-s) for reproducible fixtures so test assertions are stable.
4. 4Select modules (optional). Synthea ships disease modules
5. 5Use as a leakage-gate corpus. Synthea emits known fake names, MRNs,
6. 6Commit fixtures under your test tree (e.g. tests/fixtures/synthea/) —

What it can do on your machine

Read from SKILL.md and the folder at commit 6b1bb2c. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • git

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • github.com

  Also links to:

  • hl7.org
  • doi.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Generating Synthea Data loads about 1.6k tokens when it runs. Until then it costs about 153 tokens; SKILL.md has 603 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~153

When it runs · the whole SKILL.md, loaded when a task matches

~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from maziyarpanahi/openmed at commit 6b1bb2c, republished under its Apache-2.0 licence (© maziyarpanahi). 603 words, ~1,610 tokens.

name

generating-synthea-data

description

Generates synthetic but realistic patient records (FHIR R4 bundles, C-CDA documents, CSV) with MITRE Synthea for development, CI fixtures, demos, and leakage-gate test sets — zero real PHI. Use when you need safe, shareable test data for an OpenMed pipeline, reproducible fixtures for tests, or a held-out set for de-identification leakage gates, instead of touching real clinical data. Synthea output feeds the FHIR/C-CDA ingestion skills and openmed.eval. Trigger keywords: Synthea, synthetic data, fake patients, test fixtures, demo data, FHIR bundle generator, synthetic EHR, no PHI.

license

Apache-2.0

metadata.project

OpenMed

metadata.category

data-ingestion

metadata.pairs

adjacent

metadata.version

1.0

# Requires Java 11+. Clone and build once.
git clone https://github.com/synthetichealth/synthea && cd synthea
./gradlew build -x test

# Generate 50 patients in Massachusetts as FHIR R4 + C-CDA + CSV.
./run_synthea -p 50 Massachusetts \
  --exporter.fhir.export=true \
  --exporter.ccda.export=true \
  --exporter.csv.export=true \
  --exporter.baseDirectory=./output

# Reproducible runs: fix the seed so fixtures are stable across CI.
./run_synthea -s 12345 -p 20 --exporter.baseDirectory=./fixtures

import json, openmed

bundle = json.load(open("output/fhir/Patient_xyz.json"))
for entry in bundle.get("entry", []):
    res = entry.get("resource", {})
    div = (res.get("text") or {}).get("div", "")     # narrative XHTML
    if div.strip():
        deid = openmed.deidentify(div, method="replace", policy="hipaa_safe_harbor")
        result = openmed.analyze_text(deid.text, output_format="dict")

© maziyarpanahi, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/generating-synthea-data of maziyarpanahi/openmed.

Open the folder on GitHubat commit 6b1bb2c