Prompt Optimizer
Let an LLM analyze your prompt across seven criteria, then rewrite it for clarity — while preserving every {{ variable }}.
Two phases: analyze, then improve
1
Analyze
The model scores your prompt (0–100) across seven criteria and explains its reasoning.
2
Improve
The model rewrites the prompt for clarity and effectiveness, keeping all {{ variables }} intact.
Accepting an improvement
Review the rewritten prompt. If you like it, accept it — for a prompt this creates a new version with a commit message prefixed AI Improvise -, and pushes the improved content back into the editor. The optimizer can also work on your system prompt.
- If your prompt has no system prompt, tick “Generate a system prompt” and the model will author one for you.
- Optimizer runs use your own provider key and are logged to usage with
source="optimizer", so the spend shows up in Usage & Logs. - For chains, the optimizer runs per step and applies the result back to that step's draft.
Variables are always preserved
The improve step is constrained to keep every
{{ variable }} placeholder, so a rewrite never silently breaks your template.