agent hive

SECOPS

Compile a weekly exposed-secret audit report to Notion

Each week, aggregates all secret-scan findings and rotation events from the audit database, summarizes trends, and publishes a reviewable report page to Notion.

CategorySecOps
EngineSim + Paperclip
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionQuery Postgres for 7 days of audit eventsPostgreSQLPostgres
  • ActionSummarize findings and trends with OpenAIOpenAI
  • LogicFlag weeks exceeding rotation SLA
  • ActionPublish dated report page to NotionNotionNotion
  • OutputShare report link in SlackSlack

What it does

Pulls a week of secret-scanning and rotation history from your Postgres audit store, summarizes it into trends (new exposures, mean time to rotate, repeat offenders), and publishes a dated report page in Notion that security and engineering leads can review in their weekly sync.

When to use it

Use it when you have automated scanning and rotation running but no regular human review of how the program is performing. This turns raw audit rows into a digestible weekly artifact for governance, retro discussions, and showing auditors a consistent review cadence.

How it works

  1. 1A weekly schedule trigger fires.
  2. 2The flow queries the Postgres audit table for the past seven days of exposure and rotation events.
  3. 3An OpenAI step summarizes the dataset into trends, highlights, and recommended follow-ups.
  4. 4A logic step flags weeks where mean-time-to-rotate exceeded the SLA threshold.
  5. 5It creates a dated Notion page with the summary, metrics table, and any SLA breaches.
  6. 6It drops a link to the new report in Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect NotionPages, databases, comments.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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