Signals Over Noise Tools

Things I built along the way

Tools Born From Curiosity

Two free tools — pick the one that matches what you need to know. Both are built on the same methodology as everything else here, and both are a lot faster than doing this by hand.

Beta v2.0

Mention Rate Tool

The Signals Over Noise method, automated.

Know how often your brand appears across repeated AI-search samples.

Best for
Visibility measurement
Output
Mention rate percentage
Method
Repeated structured sampling

Run a sample →

How it works, and how to choose a sampling tier

I was doing mention rate tracking by hand — building query sets in a spreadsheet, running them through AI platforms one at a time, tallying up results, calculating percentages. It worked. It was also taking forever.

So I built this tool. It does the structured sampling, tracks which responses include your brand, and calculates your mention rate across however many queries and runs you set up. The same methodology, a lot less manual effort.

  • Structured query sets

    Built around your specific entities — not random prompts, but queries that actually reflect how your audience searches.

  • Consistent sampling

    Same queries, multiple runs — so you’re measuring a distribution, not a single result that could go either way.

  • Mention rate scoring

    A single percentage you can track over time, compare to past periods, and actually use to make decisions.

  • Real data, not screenshots

    The output is a number backed by a defined sample size — not a collection of screenshots that may or may not represent anything.

Choose your sampling tier before you start

The tool runs at one of three tiers. Pick the one that matches how much you can trust your results to matter.

  • Tier 1 — Directional
    20 prompts × 5 runs = 100 samples. Good for early exploration or pressure-testing a topic. Treat it as a signal, not a conclusion.
    ±10% margin
  • Tier 2 — Validated
    40 prompts × 10 runs = 400 samples. Reliable for monthly tracking and internal reporting. You can detect real shifts and start comparing over time.
    ±5% margin
  • Tier 3 — Statistical
    80 prompts × 30 runs = 2,400 samples. Decision-grade data. For board reporting, competitive claims, or measuring campaign impact.
    ±2% margin

Important: only compare distributions to distributions. If your margin of error is ±5%, a 2-point change means nothing. A 9-point shift probably does.


Free

Topic Entity Schema Generator

Schema markup without the tedium.

Turn your positioning and entity relationships into structured schema.

Best for
Entity clarity
Output
Usable JSON-LD

What it generates

  • Person schema

    Your identity, expertise areas, and knowsAbout fields — the signals that associate you with your topics.

  • Organization schema

    Brand identity and founding relationships — helps AI systems understand seo SUSTAINABLE as an entity, not just a website.

  • Topic entity relationships

    The connections between your expertise areas — how your topics relate to each other and to the entities AI already recognizes.

  • Article & WebPage markup

    Page-level schema that tells AI systems what a piece of content is about, who wrote it, and why it’s authoritative.

Generate schema →

Why this generator exists

Schema is a place where a lot of people either skip it entirely or generate something that validates but doesn’t actually reinforce entity recognition in a meaningful way.

The types matter. The relationships matter. This generator is built around the schema patterns that are most useful for AI visibility specifically — not just for traditional SEO crawlers.

I built it while working through the Structure stage of the framework. The manual version worked, but it was slow and error-prone. This is faster and more consistent.