AI & RAG

Spec Answer with Confidence Gate and Escalation

Responds to a Slack slash command by retrieving Dropbox spec context and answering.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSlack /spec slash command invokedSlack
  • ActionEmbed question and retrieve passages with scores from PostgresPostgreSQLPostgres
  • LogicBranch on retrieval confidence threshold
  • ActionGenerate grounded cited answer when confidentOpenAI
  • OutputReply to user, or escalate question to on-call channelSlack

What it does

Answers ad-hoc spec questions invoked via a Slack slash command, but adds a quality gate. It scores how well the retrieved Dropbox spec passages cover the question. High-coverage questions get an immediate grounded answer; low-coverage questions are escalated to the human on-call channel so nobody gets a confidently wrong reply.

When to use it

Use it when hallucinated answers carry real risk and you want the bot to know its limits. Good for teams that want self-serve spec lookup without the assistant fabricating behavior the docs don't actually describe.

How it works

  1. 1An engineer runs a `/spec` slash command in Slack with their question.
  2. 2The question is embedded and matched against the spec index in Postgres, returning passages and similarity scores.
  3. 3A logic gate checks whether retrieval coverage clears a confidence threshold.
  4. 4If confident, OpenAI generates a grounded, cited answer returned to the requester.
  5. 5If not, the workflow escalates the raw question to the human on-call Slack channel.

Set it up

What you configure once, before turning it on.

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

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