# Run and schedule benchmarks

How to trigger a benchmark manually, put it on a recurring schedule, and read benchmarks as the periods that drive your score trend.

A benchmark : a **run** : is one pass of your active question library across ChatGPT, Claude, Perplexity, and Gemini, scored end to end. Runs are the heartbeat of the product: each one is a fresh measurement, and the sequence of them is your score trend over time.

Open **Benchmarks → Results** in the [console](https://app.knitknot.ai) to run or schedule the benchmark. Use **Benchmarks → Runs** to inspect batches, progress, and individual Answers.

## Trigger a run

Use **Run all** to start a benchmark immediately. You can pick which engines to include; leaving all four selected gives you the complete picture. The run executes in the background : you'll see live progress and per-question logs as each engine responds and each response is scored. When it finishes, your report updates to reflect the latest numbers.

Trigger a manual run after you've shipped a fix and want to check whether AI has picked it up, or any time you want a fresh reading.

## Put it on a schedule

Most of the value comes from a steady cadence, not one-off runs : a trend only exists if you measure repeatedly. Set a schedule to have KnitKnot run benchmarks for you: choose **weekly**, **biweekly**, **monthly**, or a **custom** cadence, or turn scheduling off entirely. Weekly is a sensible default for actively managing your presence.

Scheduled runs use the same active library and engines as a manual run, so results stay directly comparable to the ones you trigger by hand.

## Runs, periods, and your trend

Runs group into periods, and each completed run writes a snapshot of your headline numbers. That is what the score trend on **Overview** reads from: the same formulas as the report, captured per run, rather than a re-estimate.

Because runs are what get measured and billed, treat them as deliberate events. There's no benefit to hammering the **Run all** button repeatedly : back-to-back runs against unchanged content just measure the same thing twice. Run when something has changed: new content shipped, a product added, the library or competitor set updated.

Next: once a run completes, [read your report](/docs/read-your-report/) and work through the [issues and playbooks](/docs/issues-and-playbooks/) it surfaces.

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Run and schedule benchmarks

How to trigger a benchmark manually, put it on a recurring schedule, and read benchmarks as the periods that drive your score trend.

Updated 23 Aug 2026

A benchmark : a run : is one pass of your active question library across ChatGPT, Claude, Perplexity, and Gemini, scored end to end. Runs are the heartbeat of the product: each one is a fresh measurement, and the sequence of them is your score trend over time.

Open Benchmarks → Results in the console to run or schedule the benchmark. Use Benchmarks → Runs to inspect batches, progress, and individual Answers.

Trigger a run

Use Run all to start a benchmark immediately. You can pick which engines to include; leaving all four selected gives you the complete picture. The run executes in the background : you’ll see live progress and per-question logs as each engine responds and each response is scored. When it finishes, your report updates to reflect the latest numbers.

Trigger a manual run after you’ve shipped a fix and want to check whether AI has picked it up, or any time you want a fresh reading.

Put it on a schedule

Most of the value comes from a steady cadence, not one-off runs : a trend only exists if you measure repeatedly. Set a schedule to have KnitKnot run benchmarks for you: choose weekly, biweekly, monthly, or a custom cadence, or turn scheduling off entirely. Weekly is a sensible default for actively managing your presence.

Scheduled runs use the same active library and engines as a manual run, so results stay directly comparable to the ones you trigger by hand.

Runs, periods, and your trend

Runs group into periods, and each completed run writes a snapshot of your headline numbers. That is what the score trend on Overview reads from: the same formulas as the report, captured per run, rather than a re-estimate.

Because runs are what get measured and billed, treat them as deliberate events. There’s no benefit to hammering the Run all button repeatedly : back-to-back runs against unchanged content just measure the same thing twice. Run when something has changed: new content shipped, a product added, the library or competitor set updated.

Next: once a run completes, read your report and work through the issues and playbooks it surfaces.