AI agent for product managers

Senior-grade PRD — from the first prompt

You describe the task in Claude, Cursor or ChatGPT — Monstro gathers the context and returns a reference-grade document with depth and recommendations. Save hours of rework.

⚡ Connects over MCP in a couple of clicks, no config · $20/mo

Sound familiar?

This is exactly what Monstro takes off your plate.

“Tired of redoing docs in circles”

A reference result on the first pass: PRD, Roadmap, UX-flow, analytics. No endless iterations and edits.

“Not sure my output is market-grade”

A senior standard as your benchmark. Hand work to a client with no doubt about its level.

“I want my own agent stack, but no time to dig into it”

We handle selection, setup and updates for new models. You set the task — you get the finished result.

“Everyone on the team does it differently”

One standard and shared context for everyone — the whole team works in sync.

Live example

Prompt → a ready PRD.

A short dialog on the left — a finished senior document on the right. Nothing to configure.

context.md
echo-prd.md
Chat · Agent

Write a PRD for a referral program for our fintech app (neobank N). Product context is in @context.md.

Read @context.md

A couple of questions:

  1. Reward — cash or a product bonus?
  2. Count a referral right away or after the friend activates?
  3. Break the rollout into phases?

Cash, both sides; on activation; yes, in phases.

Done — the PRD is on the right: state machine, metrics with baselines, USM, funnel and acceptance cases. Debatable points are flagged in open questions.

16 sections · 4 diagrams · anti-fraud loop
checked against the rubric: metrics · edge · fraud
⌘Kask the agentLn 214, Col 1  ·  Markdown  ·  UTF-8
What Monstro gives you

Less rework. More depth. All in a single pass.

★ Self-critique by rubric

Critiques itself like a senior — and rewrites.

It gathers context, drafts, checks against a senior rubric and strengthens the weak spots. The output is a worked-through result, not a raw first answer.

Pricing

You pay for the result, not for tokens.

One pass instead of 10–20 rounds of “do it properly” — tokens are already included in the Credit.

Orchestration

A swarm of sub-agents per task, not a single prompt.

Each task gets its own set of sub-agents and skills. We pick and assemble it — you don’t have to.

Edge cases & risks

It checks what usually surfaces after handoff.

Negative scenarios, edge cases and risks are built into the process — they don’t pop up in front of a stakeholder.

★ One standard

Output in a format your team can use.

One senior standard for everyone — work you can show your team and client right away.

Agent skills

All of a PM’s work. In one agent.

Not separate prompts for every task, but one agent that knows the PM craft and switches modes itself.

01
PRD Writerdetailed PRDs in minutes, not days
02
User ResearchJTBD, insights, user pains
03
Discoveryhypotheses, interview questions, synthesis
04
Market & Competitorscompetitors, trends, positioning
05
Requirementscapturing and prioritizing requirements
06
PrioritizationRICE, KANO, SWOT — pick your own
07
Roadmap Builderclear roadmaps for stakeholders
08
Stakeholder Commsupdates, emails, presentations
09
USM + BreakdownUser Story Map and task breakdown
10
Experiment Designhypotheses and clean A/B tests
11
Prototype → fake-doora working mockup to validate an idea fast
Built-in frameworksRICEAARRRJTBDSWOTKANO
How it works

Three steps to the result.

01

Connect in a couple of clicks

Monstro hooks into Claude, ChatGPT or your editor (Cursor, VS Code, Claude Code) over MCP. In 1 minute — no config, no API keys of your own.

~/.cursor/mcp.json
02

Call the agent

Describe the task in plain text. The agent picks the right sub-agents itself.

write a PRD for a referral program…
03

Get the artifact

A ready PRD, research or USM in a format you can proudly show your team.

echo-prd.md ●
Live · rebuild
PRD Agent
rebuilt for the latest models
2 days ago
what’s new: added a sub-agent for
competitive analysis
Only what passes workflow tests makes it into the build — not random GitHub skills picked by stars.
Why a subscription, not a one-off file

Models change every month. Your agent does too.

A prompt set built for an old model quietly degrades with every release. We do that work for you: we test builds on new models, reassemble the best skill combinations and hold the quality. You’re always on the top build and configure nothing.

Coming soon
Open benchmark

Honest agent scoring. In the open.

We’re building an engine that runs different agents on the same tasks and, across dozens of criteria, shows who’s better and where. No “stars” and no marketing — just run results, out in the open.

What we measure
Completeness & structureMetrics with baselinesEdge cases & risksConsistencyGoal attainment
Transparent

Methodology and runs are open — you can double-check.

Independent

We benchmark ourselves too. If we lose on a task, we’ll show it.

Live

Recomputed for new models — not a one-off PDF.

Compare

Why not just build such an agent yourself?

You can. The question is at what quality and at what cost in time.

CapabilityBare promptGitHub skillMonstro
Goal-directed for the task
Metrics with baselinessometimes
Negative / edge casesrarely
Self-critique & rewriting
Risk / anti-fraud sections
One standard for the team
Freshness for new modelsgoes stale
Checked on evalsstars ≠ quality
Entry barrierrawhours to assemble1 click
Pricing

Pricing.

1 Credit = 1 finished artifact (PRD, research, USM…), built by the full workflow. Unused Credits roll over for 1 month.

early access
Pro
$20/ mo
  • 100 Credits / mo (≈ 100 documents — 3–4 a day)
  • Any environment (IDE + AI desktop)
  • Always the latest build
  • Priority queue
  • Telegram support
Get Pro for $20/mo
Team
$80/ mo
  • 500 Credits / mo for the team (≈ 500 documents)
  • Everything in Pro
  • Shared access and one senior artifact standard for everyone
  • Priority support
Contact us
Your price
$/ mo
  • Name the price you’d connect Monstro for
FAQ

Answers to the key questions.

How is this better than just asking ChatGPT or Cursor?
ChatGPT gives you one “shot” of the model: a first answer where you orchestrate the steps, catch the gaps and rewrite in circles yourself. Monstro is a process on top of the same model: it gathers context, writes, critiques itself against a senior rubric, checks edge cases and risks — and only then hands off. Hence a reference result on the first pass, not a draft to redo.
Do I need my own API keys or a model subscription?
No. Credits are the tokens of the model the agent runs on: you connect nothing of your own. 1 Credit = 1 finished artifact built by the full workflow (context gathering, draft, self-critique, rubric check). The agent takes dozens of steps per run — all tokens are already included in the Credit. You pay for the result, not for counting tokens or keeping a separate subscription.
What about my data?
The agent runs in your editor and connects over MCP. We don’t train models on your data and don’t use your work beyond your task.
Which IDEs are supported?
Practically any. Monstro connects over MCP — an open standard supported by almost every modern AI editor: Cursor, VS Code, Windsurf, Claude Code, Claude Desktop and more. If it has MCP, Monstro works. Setup takes a minute, no config.
I’m not a developer. Will I figure it out?
Yes. No code: you write the task in text — the agent does the rest.
How is this better than a free set of prompts from GitHub?
A list of prompts is raw material that you assemble into a process and update for every new model yourself. We select skills by tests (not by stars), assemble a ready orchestrated agent with self-checking and keep the build fresh. You pay for the assembled process and freshness, not for access to files.

Join the top 1%
who get the most out of AI.

Most people write prompts and redo them. You work alongside a senior brain in your usual environment (ChatGPT / Claude / Cursor etc.) — you get a worked-through result and see where to dig deeper.

We’ll send access to your work email. For now Monstro is for PMs; next — marketing, design, support, analytics.

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