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Methodology2026-03-028 min

The 6 Prompt Scoring Dimensions, Explained

A detailed walkthrough of each AES dimension with examples, scoring criteria, and actionable tips to improve your weakest areas.

The 6 Prompt Scoring Dimensions, Explained

The AI Effectiveness Score isn't a black box. It's built from 6 independently-tracked dimensions, each capturing a distinct skill. Here's what each one measures and how to improve it.

1. Specificity (20% weight)

What it measures: How precisely you define what you want.

High-scoring signals:

  • Named technologies ("TypeScript", "PostgreSQL", "Next.js 16")
  • Defined input/output types ("takes a string, returns an array of objects")
  • Measurable criteria ("under 500ms response time")
  • Constraints and boundaries ("must work with Node 20+")
  • Quick win: Replace every instance of "some" and "stuff" with specific terms.

    2. Context Engineering (20% weight)

    What it measures: How well you provide background information.

    High-scoring signals:

  • Role assignment ("You are a senior backend engineer")
  • Relevant code or error messages
  • Environment details
  • What you've already tried
  • Quick win: Always include the error message, stack trace, or relevant code when debugging.

    3. Task Decomposition (15% weight)

    What it measures: Whether you break complex work into steps.

    High-scoring signals:

  • Numbered steps or bullet points
  • Sequential language ("First... Then... Finally...")
  • Focused scope (one concern per prompt)
  • Building on previous steps
  • Quick win: If your prompt is more than 3 sentences, add structure with numbers or bullets.

    4. Iteration Quality (10% weight)

    What it measures: How effectively you refine AI responses.

    High-scoring signals:

  • Specific references to prior output ("The function works but...")
  • Clear keep/change instructions ("Keep the recursive approach, but fix the edge case")
  • Quoted sections from prior responses
  • Targeted follow-up questions
  • Quick win: Never say "try again." Instead, say exactly what was wrong and what to preserve.

    5. Token Efficiency (15% weight)

    What it measures: Conciseness without sacrificing clarity.

    High-scoring signals:

  • High information density (no filler words)
  • No unnecessary preamble ("I was wondering if you could maybe...")
  • Appropriate length for the task
  • No restating information the AI already has
  • Quick win: Delete the first sentence of your prompt. If nothing is lost, it was filler.

    6. Output Specification (20% weight)

    What it measures: How clearly you define the response format.

    High-scoring signals:

  • Format type ("Return as JSON", "Format as a markdown table")
  • Length constraints ("In 2-3 paragraphs")
  • Structure ("Include sections for: Overview, Implementation, Testing")
  • Tone and audience ("Explain for a non-technical PM")
  • Quick win: End every prompt with one sentence about what format you want the answer in.


    Putting It Together

    You don't need to score 100 on every dimension. The most effective approach is to identify your 1-2 weakest dimensions and focus there. Even a 10-point improvement on your weakest dimension typically raises your overall AES by 5-8 points.

    Start tracking with Measurably to see your personal dimension breakdown and get targeted coaching tips.

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