Independent hackathon demo. Not affiliated with Meta or Facebook Marketplace.Independent demo. Not affiliated with Meta.

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Second-hand items. First-hand evidence.

Sellers choose a category, tap attributes or write their claims, and take the photos those claims need. Meta's Muse Spark describes each photo without seeing the claims, and fixed rules show buyers what's supported, what's contradicted, and what photos can't settle.

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  • 12/12labelled cases right
  • 0false reassurances
  • 3.5¢per live check

From our 12-case furniture evaluation with Muse Spark and one live check. How we measured

Uses

Muse Spark 1.3Observes each photo, claims hidden
SAM 3.1Second-opinion counts, damage boxes
Muse Glimmer 30BEvaluation on a local GPU

How a report gets made

The model describes; it never decides. Every verdict comes from plain rules you can read, applied to what was actually in the photos.

  1. 1
    4 chairsWhiteNo scratchesSolid oak

    Claims first

    Each claim gets a type: a piece count, a colour, no visible damage, no visible damage on a specific part, label text, or other. Other claims stay on the report, marked as something photos can't show.

  2. 2
    6YA7

    Only the photos they need

    A count needs the front and side; damage adds a close-up. The listing's code goes on paper in the front photo.

  3. 3
    "Set of 4 chairs"

    Blind observation

    Muse Spark gets one photo at a time and the nouns to count, never the claims. SAM 3.1 counts again and boxes the damage.

  4. 4
    sha256 · 9f2c…41e7

    Rules decide, the report is sealed

    The report is fingerprinted with its photos. Editing the listing voids it, the seller can withdraw it, and it expires in 30 days.

What a buyer opens

This is what the sample produces: recorded Muse Spark observations of our own test photos of a dining set.

White dining table with four chairs; the listing's code 6YA7 is on a piece of paper on the table.
Front, side and close-up: the photos the four claims need.

Evidence report · sample

White dining table with 4 chairs

  • 1contradicted
  • 2supported
  • 1inconclusive
  • Contradicted

    No scratches or stains

    Seen: peeling in the detail photo (tabletop near edge).

  • Supported

    Set of 4 chairs

    The front photo shows all 4 chairs.

  • Supported

    White finish

    The item in the photo is white.

  • Inconclusive

    Solid oak, not veneer

    Photos can't show this.

Why the model doesn't judge the claims

We ran 12 labelled furniture cases two ways with Muse Spark 1.3: blind observation followed by the rules, and the model shown the claim next to the photos and asked for a verdict.

Blind observation + fixed rules12/12

0 false reassurances, cases marked supported that shouldn't be

Model shown the claim, asked to judge9/12

2 false reassurances, both on photos too blurry or too dark to tell

Synthetic furniture photos; labels written before the first run. The new categories and part/label rules are not covered by this evaluation. A sanity check, not a benchmark: the two set-ups also differ in their instructions. Muse Glimmer 30B gave the same split. The whole run cost $0.22.

The case that decided it

"Three seat cushions", next to a photo of a sofa too dark to make out.

Supported the model, judging directly
Inconclusive blind: it reported the photo as too dark, and the rule refused to decide

What a report is, and what it isn't

It contrasts claims with photo evidence and says what stays inconclusive. It never certifies the item or the seller.

It is

  • A record of what specific photos showed about specific claims, on one version of the listing.
  • A signal against reused or downloaded photos, when the listing's code is read in a usable photo.
  • Tamper-evident: a fingerprint covers the report and its photos.

It isn't

  • Proof of ownership, current possession or authenticity.
  • A check of function, full condition or the seller's trustworthiness. It never scores people.
  • Aware of edits made on Marketplace itself; only edits in Verified Asset void a report.

See the whole flow in a minute

The sample replays recorded Muse Spark observations of our test photos, so it needs no photos of yours and makes no API call. It starts without the close-up: check, see Spark ask for it, add it and check again.

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