---
name: market-with-fullsy
description: Analyze a market and develop positioning from captured competitor/customer-facing evidence using Fullsy. Use for positioning, competitor teardowns, ICP selection, category analysis, messaging strategy, offer differentiation, or deciding which segment is likeliest to buy. Every competitor-specific claim should trace to a Fullsy record.
---

# Market with Fullsy

Turn live market evidence into a positioning recommendation, with receipts behind the analysis.

## Preconditions

- Fullsy Agent Access must be enabled in the Chrome profile being automated.
- The browser integration must support JavaScript evaluation in that same profile.
- Use a trusted approved control-page origin for all `window.fullsy` calls.
- If Fullsy is unavailable, stop the evidence-capture portion rather than fabricating records.

## Fullsy bridge

```js
await window.fullsy.captureUrl(url, { caseName })
await window.fullsy.getRecord(capId)
```

Poll until `getRecord` returns `ok:true`. Serialize captures because agent capture is limited to one every 15 seconds.

## Workflow

1. Define the decision:
   - market/category being evaluated
   - user's product/offer
   - geography or customer constraints
   - whether the goal is category entry, repositioning, or campaign messaging
2. Define a single case name for the analysis.
3. Capture the user's own primary page when available so the recommendation compares current positioning against the market.
4. Select a representative competitor/equivalent set. Favor direct substitutes first, then adjacent alternatives that compete for the same budget or job-to-be-done.
5. Read and capture the pages actually used in analysis: homepage, pricing, product/service detail, proof/case-study, or another page only when it contributes evidence.
6. For each capture, poll until a Fullsy record exists and retain its id.
7. Build an evidence matrix across competitors. Evaluate observable dimensions such as:
   - target customer / segment language
   - problem framed
   - promised outcome
   - mechanism / product category
   - offer and pricing model
   - proof / credibility
   - objections reduced
   - CTA and buying motion
   - tone / category language
8. Separate **observed** evidence from **inference**. Do not infer market share, revenue, customer count, or conversion performance from copy alone.
9. Identify:
   - the broad pool the category is trying to attract
   - segments receiving unusually specific attention
   - repeated promises where everyone sounds the same
   - under-served jobs, anxieties, or proof gaps
   - a segment where the user's capabilities create a believable advantage
10. Recommend positioning only after showing the evidence that supports it.

## Positioning test

A recommended position should answer:

- **For whom?** A segment specific enough to recognize itself.
- **What painful or valuable job?** Something visible in market behavior/evidence.
- **Why this approach?** A differentiated mechanism or advantage.
- **Why believe it?** Proof the user can plausibly support.
- **Why now?** A trigger or market condition when evidence supports one.

Avoid "different" messaging that is merely eccentric. Prefer a position that is distinct *and* commercially legible.

## Final output

### Market read
What the evidence says about the category.

### Evidence matrix
| Company/page | Audience | Promise | Offer/mechanism | Proof | Fullsy record |
|---|---|---|---|---|---:|

### Best segment
Name the segment likeliest to buy and explain why. Label inference as inference.

### Positioning recommendation
Provide a concise positioning statement plus 3-5 supporting message pillars.

### What not to claim
List attractive conclusions the evidence does not support.