AI AGENTS

Opposition Comment Counter-Research Agent

When an opposing public comment is filed, the agent fact-checks its claims against independent sources and drafts a point-by-point rebuttal with citations.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook with opposing comment to rebutHTTP webhook
  • ActionDecompose comment into discrete claimsOpenAI
  • ActionResearch evidence for each claimExa
  • LogicClassify claims supported/refuted/unclear
  • ActionDraft point-by-point cited rebuttalOpenAI
  • OutputSave rebuttal draft for legal reviewCodaCoda

What it does

This agent ingests a specific opposing comment, breaks it into discrete factual and legal claims, and runs each claim through independent research to confirm, refute, or qualify it. It then drafts a structured point-by-point rebuttal that maps every counterpoint to a cited source, ready for counsel to refine.

When to use it

Use it when an influential industry or advocacy comment lands in the docket and you need a defensible, evidence-anchored response rather than a quick reaction. Ideal for the deeper drafting work that follows an initial go/no-go decision.

How it works

  1. 1A webhook trigger receives the URL or text of the opposing comment to rebut.
  2. 2OpenAI decomposes the comment into a numbered list of distinct claims.
  3. 3Exa and Brave Search retrieve independent evidence for each claim in parallel.
  4. 4A logic step classifies each claim as supported, refuted, or unclear.
  5. 5OpenAI drafts a point-by-point rebuttal mapping counterpoints to citations.
  6. 6The finished draft is saved to Coda for legal review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect OpenAIModels, embeddings, files.
  2. 2
    Connect ExaNeural search across the web.
  3. 3
    Connect Brave SearchWeb, news, image, video search.
  4. 4
    Connect CodaDocs, packs, automations.
  5. 5
    Connect HTTP webhookTrigger any URL on agent actions.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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