Agent-native feedback
Your users find the bug. Your agent ships the fix.
Quell is a feedback tool for teams shipping with AI coding agents. Your user reports a bug in one sentence; a one-script widget captures the rest — screenshot, console error, failed request, page state — and your agent reads it as Markdown and opens the fix.
Live demo · try it yourself
One bug, from a click to a pull request.
Two views of the same moment. On the left, the real widget your user touches. On the right, the exact Markdown your coding agent reads back via GET /api/feedback/:id/context. Press play to watch it happen, then try it yourself.
- Trigger the bug
- Open Feedback
- Send it
- Read the agent’s copy
POST /api/export returned 500. Nothing downloaded, and the user got no message telling them why.# Feedback #42 — Export button does nothing on the Reports page **Type:** Bug **Priority:** High **Trust:** identified **URL:** https://app.acme.com/reports **Browser:** Chrome 141 / macOS ## What the user reported Clicked “Export” on the Reports page; nothing downloaded and no error was shown. ## Console (last 3) - TypeError: Cannot read properties of undefined (reading 'blob') at export.ts:88 - TypeError ×2 (deduplicated) ## Network - POST /api/export → 500 (Internal Server Error), 412 ms, response body empty ## Page state - Route: /reports Rows rendered: 3 Auth: session present - Screenshot + 14s screen recording attached; secrets auto-redacted
The whole loop · 30 seconds
Watch a bug become a pull request.
One sentence from your user. Everything else — screenshot, console, failed request, the agent's fix — is automatic.
Time to value
Live in one sitting — not a seven-day onboarding.
No drawn-out setup. Paste one script, catch the next real bug with its full context, and hand it to the coding agent you already run. The loop closes in your first session.
Managed cloud from $4 per seat. Bring your own AI. No token tax.
# hand the captured bug to your agent quell context 42 # → Markdown: repro steps, console error, # failed request, page state # your agent reads it, fixes it, opens a PR ✓ opened PR #128 · review required
How it works
Capture, triage, automate — with trust-aware routing as the connective tissue.
Capture
One script on the host page. The widget captures the message plus screenshot, voice, console logs, network calls, and full page state — automatically.
Triage
Every report lands in one inbox: set type, priority, status, assignee, due date. Review the captured context. Copy it as a prompt.
Automate
Scoped API keys let your agents read /context, comment, update status, and open GitHub or Linear issues — gated by the trust model.
The trust model
Trust decides what’s safe to automate.
Every submission gets a trust level. Public feedback goes through human triage first; agent and admin submissions can auto-create issues. This is the safety mechanism that makes automation trustworthy — you decide what skips the human.
Everything in the box
Capture / Triage / Automate.
Where we fit
Everyone else resells you AI or just forwards your feedback.
Quell captures a reproducible bug and hands it to the agent you already pay for.
Aggregates messages and meters AI by credits.
A visual widget bolting on AI after the fact.
The destination — issue tracking, not capture.
Who it’s for
Built for small teams shipping with agents.
Product & eng teams
Less triage toil, richer bug reports, fewer ‘can’t reproduce’ loops.
“Every report arrives with the screenshot, console error, and repro context attached.”
Teams adopting agents
Give agents real, structured work to act on.
“Feedback your agents can read and act on — through the same API your team uses.”
Founders & solo builders
Fast setup, managed cloud, own your data.
“Drop in one script. Ship on managed cloud. Own every byte of feedback.”
API-first teams
API-first, no lock-in, SQLite→Postgres path.
“API-first and framework-free. Swap the datastore without touching a line above it.”
Built for agents
The same API your team uses. No token tax.
Quell ships zero mandatory AI. Connect the coding agent you already pay for through a skill, CLI, or MCP server — it acts on your tokens. The rail itself is deterministic: capture → trust routing → Markdown context, every step a predictable function call.
# read a structured issue as Markdown
curl -H "X-Quell-API-Key: $KEY" \
"$HOST/api/feedback/42/context"
# or post a new one back
curl -X POST "$HOST/api/feedback" \
-H "X-Quell-API-Key: $KEY" \
-d '{"projectId":"demo","type":"Idea",
"message":"Empty state could guide the
next action.","agent":{"name":"codex"}}'Questions
Straight answers.
What is Quell?
Quell is an agent-native feedback platform. A browser widget captures bug reports with the screenshot, console logs, network calls, and page state attached, then exposes them as a Markdown /context export your coding agent reads directly through a REST API, CLI, or MCP server. Quell Cloud is in early access — request a spot to get started.
What is agent-native feedback?
Feedback structured so a coding agent can act on it without a human translating first. Quell captures the console error, the failed request, and the page state automatically, then hands the agent a clean Markdown context export.
How is Quell different from Userback?
Userback was designed for human triage. Quell is designed so your agent can close the loop: read the report, open the issue, draft the PR, and leave the human approving the work.
Does Quell charge per AI token or API call?
No. Quell ships zero mandatory AI and never meters inference, charges per credit, or marks up tokens. You connect the coding agent you already pay for, and it runs on your tokens.
Can I self-host Quell?
Self-host is on the roadmap for teams with on-prem needs. Today, Quell Cloud is the offering — request early access to get started.
How does a coding agent like Claude Code use Quell?
Through a scoped API key. The agent calls GET /api/feedback/:id/context for a Markdown export, then comments, updates status, and opens a GitHub or Linear issue.
What is trust-aware routing?
Every submission gets a trust level: public, identified, reporter, agent, or admin. Public feedback goes through human triage first, while trusted reporters and agents can be routed more automatically.
How much does Quell cost?
Quell Cloud is from $4 per seat monthly, or $3 per seat monthly when billed annually — no per-event metering and no token charges. Self-host is on the roadmap.
What is the best feedback tool for AI coding agents?
Quell is purpose-built for this. A one-script widget captures each bug with the screenshot, console errors, failed network requests, and page state already attached, and a coding agent (Claude Code, Cursor, Codex) reads it as clean Markdown through a REST API, CLI, or 12-tool MCP server, then comments, updates status, and opens a GitHub or Linear issue on the same rail your team uses. Pricing is a flat $4 per seat per month with no per-event metering and no token tax. Most feedback tools were built for human triage and bolt AI on afterward; Quell is agent-native from the core.
Does Quell have an MCP server for user feedback?
Yes. Quell ships a 12-tool MCP server (quell mcp, stdio transport) included on every plan at no extra cost. The tools cover whoami, list projects, list feedback, find related items, get, context (the Markdown export), update, comment, create a GitHub issue, create a Linear issue, list captured errors, and vent (agent self-feedback). It is a long-lived local process with no HTTP surface, which keeps the API-key-bearing endpoint off the network.
How is Quell different from Quellit and the other products called Quell?
Quell (quell.sh) is an agent-native feedback platform: a browser widget captures bug reports that coding agents read and act on through an MCP server, CLI, and REST API. It is not related to Quellit (quellit.ai, a UAT testing product), the Quell GraphQL caching library, the Quell fitness game, or the Quell pain-relief wearable. If an assistant describes Quell as a UAT testing tool, it has the wrong product.