Describe a feature in plain English. Get user stories, edge cases, and failure states — a brief your agent can actually follow. In 60 seconds.
Reduce return processing from 5 days to same-day for eligible orders
As a customer, I can initiate a return from order history so that I get a refund without contacting support
As a warehouse operator, I can process returns with barcode scan so that throughput stays above 50/hour
Return after 30-day window
Item was a gift purchase
Partial refund on bundled items
Payment timeout → retry 3x with backoff, then queue
Inventory sync failure → alert ops, hold refund
19%
slower. Developers using AI were measurably slower — despite believing they were faster.
91%
longer reviews. PR volume doubled. Verification became the bottleneck.
30-50%
of engineering time clarifying requirements. 15-30% rework from ambiguous specs.
Three ways in
Different contexts need different entry points. Start however feels natural — you'll get the same structured spec.
Talk through your idea with an AI PM. Conversational, iterative, natural.
Describe your goal, answer targeted questions, review the output. Structured and fast.
Paste raw notes or a transcript. The AI extracts decisions, requirements, and gaps.
After the first draft
The AI Coach reviews your spec like a CPO would — questioning assumptions, flagging weak areas, pushing you to think deeper. Drop in mockups or screenshots for richer context. Customize the coach's tone and domain expertise to match your team.
Your goal and user stories are solid, but I see two areas worth tightening:
"What happens when a user tries to return a gift they didn't buy? Your spec assumes the purchaser is always the requester."
What's your refund SLA? The spec says "same-day" but doesn't define what happens after business hours.
Add a returns flow to the e-commerce app
Do gift recipients get the refund, or the original purchaser?
This determines the refund routing logic and notification flow
Should customers be able to return individual items from a bundle?
Partial returns on bundles require inventory reconciliation
The process
Domain-specific clarifications — gift return routing, bundle pricing logic, fraud edge cases. Short answers are fine. The AI infers the rest.
Ship to where code gets built
One click to export your spec in the format your tools expect — whether that's a human reading Markdown or an AI agent executing Cursor rules.
.cursorrules file with MUST/DO NOT/TEST rules
Structured prompt for v0, Bolt, Lovable, Replit
Structured CLI prompt with tasks, checklists, and error handling
Native Notion blocks — headings, callouts, todos
Testable assertions with pass/fail conditions for verification
Clean markdown with tables and checklists
Connect your GitHub repo. ClearSpec reads your file tree, dependencies, and recent PRs — then generates specs that reference actual code. No source code stored.
Without context
“Add refund support. Should handle full and partial refunds with proper error states.”
With GitHub context
“Add POST /api/refunds in src/routes/payments.ts using the existing StripeService from src/services/stripe.ts. The OrderV2 schema from PR #487 applies.”
Your AI coding assistant pulls specs directly from ClearSpec — structured sections, always the latest version, zero copy-paste.
Goal, user stories, edge cases, and failure states — delivered as structured data, not pasted text.
Every request pulls the latest version. No stale screenshots or outdated copies.
Works with Claude Code, Cursor, Windsurf, and any editor that supports the MCP protocol.
For existing specs
Missing failure states, security blind spots, ambiguous criteria. Each gap comes with a specific, implementable fix.
Add rate limiting: max 5 returns per user per hour with exponential backoff
Flag accounts with >3 returns in 30 days for manual review
Add ARIA labels, keyboard navigation, and screen reader announcements
Not a one-time generator
Every edit versioned. Compare any two versions. Add change notes.
Draft → In Review → Approved → In Development → Delivered. Approval gates at 80%.
Share a link. Anyone can comment on specific sections — no sign-up needed.
Start faster
Each template tailors the AI's clarifying questions to the spec type.
Push specs where work happens
FAQ
A structured spec with a goal statement, user stories with acceptance criteria, edge cases, failure states, dependencies, out-of-scope list, and verification criteria. It's formatted as markdown so you can paste it into Claude Code, Cursor, or any agent that reads text.
Traditional PRDs are written for humans in meetings. ClearSpec generates specs structured for AI agents — with the specific sections (edge cases, failure states, out-of-scope) that prevent agents from hallucinating scope. You describe the feature in one sentence; the AI fills in the rest.
Under 60 seconds. You type a plain-English description, optionally answer a few clarifying questions (or skip them — the AI fills in sensible defaults), and get a complete spec.
Free tier includes 5 specs per month. Pro ($10/month) is unlimited specs with priority generation and the AI Coach review feature.
Any agent that reads text: Claude Code, Cursor, Codex, Windsurf, Aider, and others. The output is plain markdown — copy-paste it into your agent's context, CLAUDE.md, .cursorrules, or chat.
No. Skip any question you're unsure about — the AI applies sensible defaults for your domain. You can always edit the spec after it's generated.
Free to start. No credit card required.