AI & RAG

Coda Knowledge-Gap Logger

Captures questions hitting the QA endpoint that the corpus can't answer well, clusters the recurring gaps.

CategoryAI & RAG
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook logs a low-confidence questionHTTP webhook
  • ActionAppend the miss to a Supabase tableSupabaseSupabase
  • LogicCluster recent misses into recurring themes
  • ActionSummarize each gap with OpenAIOpenAI
  • OutputWrite prioritized gaps to a Coda trackerCodaCoda

What it does

Closes the loop between what users ask and what your docs actually cover. Whenever a question retrieves only low-confidence matches, this workflow logs it, and on a schedule it groups the recurring misses into themes and files them in a Coda gap-tracker for the documentation team.

When to use it

Run it behind any live QA endpoint or Slack bot. Instead of silently failing on unanswerable questions, you get a prioritized backlog of the content your knowledge base is missing.

How it works

  1. 1An HTTP webhook receives a low-confidence question event from the QA endpoint.
  2. 2Supabase appends the question, its top score, and timestamp to a misses table.
  3. 3A scheduled logic step clusters recent misses into recurring themes by frequency.
  4. 4OpenAI summarizes each cluster into a clear content-gap title and description.
  5. 5Coda writes the prioritized gaps into a knowledge-gap tracker table for doc owners.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect SupabaseTables, auth, storage, edge functions.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect CodaDocs, packs, automations.
  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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