CUSTOMER SUPPORT
Weekly report on Front draft acceptance and tone drift
Each week compares the AI-suggested Front drafts against what agents actually sent, scores edit distance and tone drift.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule
- ActionPull draft-vs-sent pairs from PostgresPostgres
- ActionScore edit distance and tone driftOpenAI
- LogicAggregate acceptance rate and top topics
- OutputPost Slack digest and log to NotionSlack
What it does
It closes the loop on auto-drafting by measuring it. Each week it pairs the draft the system suggested with the reply the agent actually sent, scores how much was changed and where tone drifted, and reports the trend. You learn whether drafts are saving time or being thrown away.
When to use it
Use it once a Front auto-draft workflow is live and you need evidence, not vibes: acceptance rate, heaviest-edited topics, and tone-drift hot spots that signal your example store needs refreshing.
How it works
- 1A weekly schedule triggers the report.
- 2It pulls the past week's draft-and-sent pairs and metadata from Postgres.
- 3OpenAI scores each pair for edit magnitude and tone drift and clusters the recurring problem topics.
- 4A logic step rolls scores into acceptance rate and top drift categories.
- 5A summary posts to Slack and a structured record is written to Notion for the historical trend.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Connect NotionPages, databases, comments.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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