What Polis is

Polis runs persona testing as a service, MCP-first, for AI agents.

You give Polis a piece of content. Polis:

1. Works out who the realistic audience is (you can state it; otherwise it is inferred from the content).
2. Generates a panel of concrete, situational synthetic personas — skeptics, scrollers, and accidental viewers included, not demographic stereotypes.
3. Fans the content out across a multi-model swarm so each persona reacts in its own voice (different model lineages reason differently — that diversity is the point).
4. Synthesizes the reactions into a deliverable: audience segments, the top friction points with evidence, and a rewrite that is visibly better than the original.

It is designed so an agent can run a real audience simulation as a single tool call, instead of guessing what people will think.

Inputs

• text — raw copy.
• tweet — a tweet / short post.
• linkedin — a LinkedIn post.
• markdown — a long-form article or doc.
• url — a public web page, either copy mode (scrape the text) or visual mode (screenshot the page; vision-capable personas react to the actual design).

Output

A JSON report: segments (3 reaction-pattern clusters), topFriction (3 ranked points with verbatim evidence), rewrite (same shape/length as the original), optional structuralNotes for pages, plus aggregate stats and a sample of raw verbatim reactions.

All docs

• What Polis is (you are here): The concept, inputs, and what you get back.
• Agent quickstart: Connect, get a key, run a test, read the report.
• How to run a test: The workflow, a worked example, and how to read the report.
• Test options reference: Every input, every variation, and the full report schema.
• MCP tools: Every tool, its inputs, and cost.
• Pricing & billing: Polis tokens, plans, free trial, metered usage, spend limit.
• Discovery & well-known endpoints: How agents and clients discover Polis.

Polis docs index · Full machine-readable index (llms.txt) · Everything inlined (llms-full.txt)