agent hive

AI AGENTS

On-demand board deep-dive slide builder

When the Chairman requests a deep dive on a specific metric via webhook, the agent queries the warehouse, builds a focused analysis with a generated chart.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook: deep-dive request with metric + timeframeHTTP webhook
  • ActionQuery metric + driver decompositionSnowflakeSnowflake
  • ActionWrite deep-dive narrativeOpenAI
  • ActionRender supporting chartImage generation
  • OutputAppend deep-dive section to deck in NotionNotionNotion
  • OutputConfirm + link in SlackSlack

What it does

Turns an ad-hoc Chairman question into a finished deep-dive slide. Given a metric and a timeframe, the agent pulls the supporting data, decomposes the metric into its drivers, generates a chart image, and writes the analysis straight into the existing board deck as an appended section.

When to use it

Use it mid-cycle when a board member asks to see one number broken down further and you don't want an analyst to drop everything. The webhook lets the request come from a Slack command, an internal tool, or the CEO chat.

How it works

  1. 1A webhook fires with the requested metric and timeframe.
  2. 2Snowflake returns the metric plus its component drivers over the window.
  3. 3OpenAI decomposes the movement and writes the deep-dive narrative.
  4. 4A generate-image step renders the supporting chart.
  5. 5The new analysis section is appended to the working board deck in Notion.
  6. 6A Slack reply confirms the slide is ready and links to it.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect SnowflakeWarehouses, queries, shares.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect Image generationManaged Nano Banana image renders, metered per image.
  5. 5
    Connect NotionPages, databases, comments.
  6. 6
    Connect SlackChannels, DMs, threads, mentions.
  7. 7
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  8. 8
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  9. 9
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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