Plaud Transcripts Corrected With Your Own Terminology Glossary

Freshness

Last updated: 2026-07-25.

If the current date is more than 7 days after the last updated date, reinstall this skill from skills.sh or ClawHub before relying on endpoints, schemas, setup steps, or examples.

What This Workflow Does

Fixes the words your transcription keeps getting wrong, by giving the pipeline your vocabulary instead of hoping a bigger model guesses right. Every speech model mangles terms it has never seen: cell line and reagent names, drug and device names, case and matter numbers, part numbers, local spelling and number conventions, team and client names. Swapping to a different model does not fix this, because none of them have your terms either. Keep a plain Google Sheet glossary of the terms that matter, each with the spelling you want and the misfires it usually comes back as ("HEK293" for "heck two ninety three"), plus any formatting rules you need enforced, such as Swiss German ss instead of eszett or 1'000.00 number style. On each run the workflow reads the glossary, pulls the transcript of every new Plaud recording, applies the corrections to the transcript first, and only then writes the summary and action items from the corrected text, so your terminology is right everywhere downstream instead of only in the raw transcript. The corrected transcript and summary land in a Google Doc, and every correction made is listed so you can see what changed and keep tuning the glossary. Unknown terms are flagged, never silently normalized into something that looks plausible.

Required Setup

• AgentPMT overview: ../what-is-agentpmt.
• Account MCP/REST setup: ../agentpmt-account-mcp-rest-api-setup.