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AI agent for court reporters

Dictionary Conflict Update Agent

A dictionary update that removes conflicts and has been tested against real transcripts

Dictionary Conflict Update Agent: what goes in, what the agent does and what you get

What it does

A steno dictionary grows for years, and conflicts creep in: two words share one brief, or an entry produces the wrong word in a common phrase. This agent reads the reporter's dictionary and finds conflicting or ambiguous briefs. For each conflict it proposes a fix, such as a new brief or a context rule. It then tests the fix against past transcripts, the reporter's own text, and counts what it changes: what it fixes and what it would break. Fixes that cause new errors are dropped. Others are retested with the changes in place together, because two fixes can interfere. It repeats until the results are stable. The reporter approves the final dictionary changes. Edge case: a brief that reads correctly in medical testimony but wrong in contracts.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Reporter requests a dictionary review 2 USES A TOOL Read the dictionary and find duplicate or ambiguousbriefs 3 DOES Propose a fix for each conflict 4 USES A TOOL Test each fix on past transcripts and count whatchanges 5 CHECKS THE RESULT Does each fix correct more than it breaks? If not: drop the fix or change the brief and retest.Back to step 3. 6 USES A TOOL Retest all remaining fixes together 7 CHECKS THE RESULT Do the fixes work together with no new errors? If not: remove the interfering fix and retest. Back tostep 3. 8 DOES Prepare a dictionary update with the list of changes 9 YOU APPROVE Reporter approves the final dictionary 10 RESULT Updated dictionary and change report
Read the steps as a list
  1. Reporter requests a dictionary review
  2. Read the dictionary and find duplicate or ambiguous briefs
  3. Propose a fix for each conflict
  4. Test each fix on past transcripts and count what changes
  5. Does each fix correct more than it breaks?If not: drop the fix or change the brief and retest. Back to step 3.
  6. Retest all remaining fixes together
  7. Do the fixes work together with no new errors?If not: remove the interfering fix and retest. Back to step 3.
  8. Prepare a dictionary update with the list of changes
  9. Reporter approves the final dictionaryThe agent waits here for your OK.
  10. Updated dictionary and change report

How it decides

A fix is kept only if it corrects more words than it breaks on past transcripts, and it does not interfere with other approved fixes.

  • Drop any fix that creates more than it corrects
  • Test fixes on at least 10 transcripts
  • Retest the approved fixes together
  • Keep the old dictionary as a backup

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Transcripts used for testing
  • Break limit (default 0 new errors)
  • Review schedule
  • Backup location

What keeps you in control

It always asks you first

  • Final dictionary changes

Hard limits

  • Never overwrites the original dictionary
  • Never uses real case text outside the reporter's files

It stops when

  • Done: conflicts resolved and tests stable
  • Stop: no past transcripts are available for testing

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensThe agent found 27 conflicts. One brief for the word mortgage also fired on mortgagor. A proposed new brief for mortgagor fixed 41 cases and broke 3 in medical records, where it matched a drug name. It changed the brief and retested, with 41 fixed and 0 broken. Testing all fixes together revealed one clash. After removing it, the reporter approved 24 changes.

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