AI Prompt Linter

Audit prompts for goals, context, constraints, success criteria, output contracts, and agent approval boundaries.

Prompt to review

Prompt score

88/100

Approx. tokens

129

Characters

515

Quality checks

Clear goal

Relevant context

Constraints

Output format

Success criteria

Autonomy boundaries

Examples or references

Add an example only when it clarifies a product requirement or tricky edge case.

Lean instructions

Improved prompt scaffold

## Goal
Review the attached API migration plan and identify the five risks most likely to cause data loss or extended downtime.

Context: The service handles 10,000 writes per minute and must remain available during the migration.

Constraints:
- Do not propose a full rewrite.
- Separate confirmed risks from assumptions.
- Ask before suggesting destructive database operations.

Success criteria: every risk includes impact, likelihood, evidence, and one concrete mitigation.

Return a Markdown table ordered by severity.

## Context
[Keep the relevant context from the prompt above]

## Constraints
[Consolidate the hard constraints from the prompt above]

## Success criteria
[Consolidate the completion criteria]

## Output format
[Keep the requested output contract]

Private by default: this tool runs entirely in your browser. Nothing you paste is uploaded to Execute.Online.

About AI Prompt Linter & Prompt Optimizer Online

Audit AI prompts for goals, context, constraints, output format, success criteria, and agent approval boundaries. Private and browser-based.

How to use AI Prompt Linter

1Paste a user, system, or developer prompt.
2Review the score and failed quality checks.
3Use the generated scaffold to consolidate missing requirements.
4Copy the improved prompt and test it on representative tasks.

Frequently Asked Questions

What does the AI Prompt Linter check?

It checks whether a prompt clearly states its goal, context, constraints, output contract, success criteria, examples, and approval boundaries for agentic work.

Does this tool call an AI model?

No. The analysis is deterministic and runs locally, so private system prompts never leave your browser.

Why check autonomy boundaries?

Agentic models can take multi-step actions. Clear boundaries tell the model what it may do automatically and which external or destructive actions require confirmation.

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