CONTENT CREATION
Evergreen Post Refresh: Quarterly Stat-Decay Triage to Slack
Each quarter, scores every published post for stat decay and sends a ranked Slack digest of which articles need updating, with the specific outdated numbers called out.
How it runs
The automated pipeline, trigger to output.
- TriggerQuarterly schedule fires
- ActionRead post list and traffic from AirtableAirtable
- ActionExtract key statistics per post (LLM)OpenAI
- ActionPull current source valuesFirecrawl
- LogicScore decay severity weighted by traffic
- OutputPost ranked refresh-needed digest to SlackSlack
What it does
Gives a content team a prioritized to-do list instead of silent edits. It reads your post catalog, checks each statistic against live data, and produces a Slack report ranked by how stale and how high-traffic each post is — so editors spend their refresh time where it matters most.
When to use it
You have too many evergreen posts to rewrite blindly and want a human in the loop. This is the triage layer: it tells you what's decayed and by how much, but leaves the editorial decision and rewrite to your team.
How it works
- 1A quarterly schedule starts the audit.
- 2Read the published-post list and traffic metrics from Airtable.
- 3An LLM extracts each post's key statistics.
- 4Firecrawl pulls the current value for each cited source.
- 5A logic step scores decay severity and weights it by traffic.
- 6Posts above the threshold are sorted into a ranked digest.
- 7Post the digest to a Slack channel with per-post stale-stat callouts and links.
Set it up
What you configure once, before turning it on.
- 1Connect AirtableBases, tables, views, automations.
- 2Connect FirecrawlCrawl, scrape, structured extract.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect SlackChannels, DMs, threads, mentions.
- 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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Run this workflow in your colony.
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