SOCIAL MEDIA
Archive Discord Sentiment History and Flag Multi-Week Drift
Periodically scores Discord channel sentiment, appends each reading to a Postgres history table.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled cadence (e.g. every 4 hours)
- ActionCollect recent Discord messages per channelDiscord
- ActionScore sentiment and confidence with OpenAIOpenAI
- ActionAppend reading to Postgres history tablePostgres
- LogicFit trend, detect sustained negative slope
- OutputNotify brand team in Slack on confirmed driftSlack
What it does
Builds the long-memory layer the alerting workflows lack. On a schedule it scores current Discord sentiment, writes the reading to a Postgres history table, and runs a regression over recent readings to catch slow, multi-week erosion that no single-window alert would notice. A sustained downward slope notifies the brand team.
When to use it
Use it when you care about gradual decay, not just spikes: a community slowly souring on the product over weeks. It also gives you a queryable sentiment dataset for reporting and board reviews.
How it works
- 1A schedule fires the run on a regular cadence (for example every 4 hours).
- 2Recent Discord messages per watched channel are collected.
- 3OpenAI returns a sentiment score and confidence per channel.
- 4Each reading is appended to a Postgres sentiment-history table.
- 5A logic step fits a trend over recent readings and detects a sustained negative slope.
- 6If drift is confirmed, Slack gets a notice with the slope, duration, and channel breakdown.
Set it up
What you configure once, before turning it on.
- 1Connect DiscordCommunity channels + voice + bots.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect PostgresAny Postgres URL — query, write, migrate.
- 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.
More Social Media workflows
A/B carousel cover variants from one brief
Takes a single approved brief and uses an LLM to write three distinct cover-slide headlines, renders a carousel cover for each, and logs the variants to Airtable for an A/B test.
Localized carousel variants per target market
From one approved master brief, translates the copy into each target locale, renders a localized carousel per market, and publishes each to its region's platform account.
Multi-Platform Comment Escalation Router
Ingests inbound comments and replies from your connected social platforms, classifies each for legal or PR risk.
Post-event Discord attendance recap and host digest
After a synced calendar event ends, reconciles who RSVP'd against who actually showed, posts a thank-you recap in Discord, and emails the host a digest of attendance and no-shows.
Agent-Driven Comment Policy Review Queue
An agent reviews ambiguous comments against your brand's response policy, decides whether to auto-clear, draft a reply for approval, or escalate, and routes its decision…
Carousel render with brand-safety pre-check
Before rendering, an LLM checks the brief copy against brand and policy rules; clean briefs render and archive to S3, flagged briefs route to a review queue instead.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.