AI AGENTS
RFP Clarification Question Generator
When an RFP requirements doc is finalized, the agent finds ambiguous or contradictory requirements and drafts a clean list of clarification questions to email the issuing agency.
How it runs
The automated pipeline, trigger to output.
- TriggerNotion page marked intake-completeNotion
- ActionRead requirements textNotion
- ActionLook up unfamiliar standardsExa
- ActionGenerate clarification questionsOpenAI
- LogicAny questions generated?
- OutputEmail draft question list to proposal leadGmail
What it does
Reads a finalized RFP requirements document and identifies requirements that are vague, internally contradictory, or missing key detail needed to respond. It drafts a numbered list of clarification questions and sends it as a ready-to-review email to the proposal team.
When to use it
Use it right after intake, before drafting begins, when most RFPs allow a vendor Q&A window. Catching ambiguities early prevents wasted drafting and weak assumptions.
How it works
- 1A Notion page is marked intake-complete, firing the trigger.
- 2The agent reads the full requirements text from the page.
- 3Exa checks unfamiliar standards or acronyms so questions are informed, not naive.
- 4OpenAI flags ambiguous, conflicting, or underspecified requirements and writes a clarification question for each.
- 5A decision step checks whether any questions were generated at all.
- 6If questions exist, a formatted draft email is sent to the proposal lead via Gmail for review before submission to the agency.
Set it up
What you configure once, before turning it on.
- 1Connect NotionPages, databases, comments.
- 2Connect ExaNeural search across the web.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect GmailRead, draft, send, label.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Weekly On-Call Doc-Gap Digest
Each week the agent reviews every Sentry issue resolved in the last 7 days, ranks the ones whose runbook coverage is missing or thin.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.
