Clinical ASR Flywheel — Stage 1 (Setup)

Clinical ASR Flywheel — Stage 1 (Setup)

Agent: this file is the complete Stage 1 procedure. Do not invoke find, ls, rg, or grep looking for an installer or hidden config — there isn't one. The four sections below (outbound-data disclosure, three numbered checks, sibling hand-off) are all required reading; don't skip any. Function IDs, env-var conventions, and the smoke-test gate are inlined further down — answer from what's actually written here rather than from prior Riva/NVCF familiarity.

Stage 1 has one job: prove the user can reach NVIDIA's hosted speech stack with the NVIDIA_API_KEY they currently hold. Once a single clinical sentence round-trips through Magpie TTS → Parakeet/Nemotron ASR successfully, the user is cleared to advance to /digital-health-clinical-asr-build.

The four-stage flywheel exists to drive down KER (keyword error rate) on clinical entities — drugs, procedures, anatomy, conditions, labs, roles. WER averages obscure the failures that hurt clinically; KER is what Stage 3 will measure you against.

There is no installer script anywhere in this skill — not install.sh, not setup.py, nothing hidden. Stage 1 is the three steps below: verify the key, install Python deps, run the smoke test. Anything past Stage 1 is composed from sibling skills (/data-designer, /riva-tts, the inlined Stage 3 ASR recipe, /riva-asr-custom). If a user asks "what script installs everything?", answer from this paragraph; don't go searching.

Outbound data flows — surface before any text or audio is sent

Two external endpoints receive data during this flywheel. The user has to acknowledge both before Stage 2 begins, against whatever data-governance policy their organization enforces. Render the table below word-for-word in your response — a paraphrase doesn't satisfy the disclosure; the literal phrasing is what counts.

The data is synthetic by construction — the flywheel manufactures sentences and audio from a user-curated term list, never from real patient encounters. That said: do not feed real patient transcripts, recorded clinical audio, or any PHI through any stage. If the term list itself contains sensitive material (codename drugs, unreleased product names), the user should consult their organization's external-API policy before proceeding. Either endpoint can be turned off:

• Skip Merriam-Webster entirely: leave DICTIONARY_API_KEY unset and don't run a scraper. Stage 2 falls back to Magpie G2P, which still works but with weaker coverage on long-tail clinical terms.
• Skip NVCF: this is a hard stop. Magpie TTS + Parakeet/Nemotron ASR are the workload; without them this skill family is the wrong tool — a self-hosted ASR/TTS pipeline is what you want instead.

Recommend a copy of this notice lands in the user's workspace README.md; bring it forward on first invocation if it isn't already there.

Purpose

Get a fresh environment ready for Stage 2. Three things to confirm: key is present, deps import cleanly, hosted stack actually answers. Close by naming which skill to run next.

The four digital-health-clinical-asr-* skills are self-contained — every TTS, ASR, IPA-tagging, and scoring recipe lives inside them; no other agent skill needs installing to run the flywheel end-to-end.

This skill takes no opinion on workspace layout. The user decides where their cycle artifacts live; data/eval_sets/cycle<N>/ is not imposed.

When to use this skill