ClosedLoop AI ClosedLoop AI

Product Context
in Claude Code

Claude codes better when it understands the real user problem, not just the ticket.
One command to install.

$ curl -fsSL https://closedloop.sh/install | bash
Claude Code
One-line install
Free
claude
❯ implement the data export feature
ClosedLoop AI — found customer evidence
───
Customer Evidence: data export
- Role-specific export templates — 6 signals
"Manual reporting takes ~3h/week, hundreds of rows nobody reads"
- Background export for large datasets — 4 signals DEAL BLOCKER
"We export 50k rows and it just times out"
- CSV export with filters — 8 signals
"I just need to export what I'm looking at, not the whole table"
───
18 signals from 12 customers. The main pain is large datasets timing out and no way to filter before exporting.
• Background async export with download link
• CSV with current filters applied (8 asked for this)
• Progress indicator — "I had no idea if it was running"
• Skip Excel/PDF for now — only 2 mentions
Want me to start with the background job implementation?
$ curl -fsSL https://closedloop.sh/install | bash

What you can ask Claude

Every feature is hundreds of decisions — API design, edge cases, what to ship now vs later. Claude makes better ones when it knows what users actually said.

Implement with context

Tell Claude to build a feature. It pulls in real user pain, workarounds, and expected behavior — then writes code that actually solves the problem.

"implement the Slack integration for feedback"

Generate a PRD

Run /closedloop:prd and get a full product requirements doc backed by real customer quotes, signal counts, and workarounds. Not opinions — evidence.

/closedloop:prd data export

Write a technical spec

Run /closedloop:spec and Claude searches your codebase, pulls customer evidence, and writes a design doc grounded in both code patterns and user needs.

/closedloop:spec Slack integration

Scope v1 from evidence

Claude sees which features have 12 signals and which have 1. Your v1 includes what users actually asked for and skips what they didn't.

"what's the minimum scope for export?"

Auto-injected evidence

Type "implement" or "build" and customer evidence appears automatically. No extra step — Claude already knows the user problem before it writes a line of code.

fires automatically on feature prompts

Search your feedback

Ask Claude about any topic and it searches your customer signals — pain points, workarounds, severity, deal blockers. The full picture, not a Jira summary.

"what are customers saying about search?"
$ curl -fsSL https://closedloop.sh/install | bash

Up and running in 3 steps

From zero to exploring product insights with Claude in under 2 minutes.

1

Get your API key

Go to app.closedloop.sh/api-keys and copy your API key.

2

Run the installer

One command adds ClosedLoop AI to Claude Code globally — works across all your projects.

$ curl -fsSL https://closedloop.sh/install | bash
3

Ask Claude

Restart Claude Code and start exploring your product insights and opportunities. Claude has full access to your data.

Start building from customer evidence

Get your API key, run one command, and ask Claude anything about your product opportunities and feedback.

$ curl -fsSL https://closedloop.sh/install | bash
Get API Key Read Docs