AI AGENTS

URL-Triggered Teardown to Airtable Tracker

Drop a competitor's website URL into a webhook and the agent scrapes the site, drafts a teardown scored against your evaluation rubric, self-critiques the scores.

CategoryAI Agents
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook receives competitor URLHTTP webhook
  • ActionCrawl site pages with FirecrawlFirecrawl
  • ActionScore competitor on rubric with OpenAIOpenAI
  • LogicSelf-critique: verify each score against evidence
  • OutputAppend structured row to Airtable trackerAirtableAirtable

What it does

Give it one competitor URL and it returns a rubric-scored teardown as a structured record. It scrapes the actual site, scores each dimension, then second-guesses its own scores before writing a clean row to your Airtable tracker.

When to use it

When you maintain a competitive matrix and want every new entrant evaluated the same way. Use it to keep an apples-to-apples Airtable comparison without an analyst manually filling cells.

How it works

  1. 1A webhook receives a competitor homepage URL, optionally with a rubric override.
  2. 2Firecrawl crawls the site — homepage, pricing, product, and docs pages — into clean text.
  3. 3The agent scores the competitor on each rubric dimension (positioning, pricing clarity, depth, ICP fit) with a short justification per score.
  4. 4A self-critique pass checks whether each score is actually supported by the scraped evidence and corrects inflated or harsh ratings.
  5. 5It assembles a structured record: scores, justifications, key quotes, and an overall threat level.
  6. 6The reviewed record is appended as a new row in the Airtable competitive tracker.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect FirecrawlCrawl, scrape, structured extract.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect AirtableBases, tables, views, 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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