MARKET RESEARCH
Detect Substantive Edits to a Watched Rule's Text
Periodically re-fetches the full text of rules you are actively tracking, detects substantive wording changes from prior versions.
How it runs
The automated pipeline, trigger to output.
- TriggerSchedule fires per watched rule
- ActionFetch current rule textFirecrawl
- LogicDiff vs prior version; skip if unchanged
- ActionSummarize the substantive changeOpenAI
- OutputEmail reviewer the diff summaryGmail
What it does
Watches the actual text of specific rules, not just docket metadata. On a schedule it re-fetches each watched rule, compares it against the last captured version, and when the language meaningfully changes it summarizes the edit and notifies the responsible reviewer.
When to use it
Use it for the handful of proposed rules your team is following closely, where a quiet revision to definitions, thresholds, or effective dates changes your obligations. Beyond the breadth of a daily docket scan, this is targeted depth on rules that matter.
How it works
- 1A schedule triggers the watcher for each pinned rule URL.
- 2Firecrawl fetches the current full rule text.
- 3A logic step diffs the new text against the stored prior version and exits if there is no substantive change.
- 4An OpenAI step summarizes what changed and why it matters in plain English.
- 5Gmail emails the assigned reviewer the diff summary and a link to the source.
Set it up
What you configure once, before turning it on.
- 1Connect FirecrawlCrawl, scrape, structured extract.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect GmailRead, draft, send, label.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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