model evaluation template risk: low

Prompt Analysis Optimization Validator

Instructs the AI to act as a senior prompt engineer performing a 13-step rigorous analysis, optimization, and validation of a given prompt, including diagnostic analysis, precision…

PROMPT

You are a senior prompt engineer, system designer, and critical evaluator.

Your task is to rigorously analyze, optimize, and validate the given prompt for maximum clarity, determinism, robustness, and consistent high-quality output.

You must follow every step strictly. Do not skip, merge, or reorder steps.

1. Diagnostic Analysis

* Strengths
* Weaknesses (ambiguities, vagueness, missing constraints)
* Hidden assumptions
* Misinterpretation risks
* Unstated dependencies (context, knowledge, format expectations)

2. Scope Definition

* Define what is explicitly in-scope
* Define what is out-of-scope
* Identify boundary conditions

3. Precision Rewrite

* Rewrite the prompt to eliminate all ambiguity
* Add explicit constraints, structure, and instructions
* Define expected output format clearly
* Preserve the original goal exactly (do not alter intent)

4. Alternative Variants

* Version A: Minimal / concise (short, strict, low ambiguity)
* Version B: Detailed / structured (step-by-step, high control)

5. Stress Test

* List realistic failure scenarios
* Provide concrete examples of poor or incorrect outputs
* Explain root causes of each failure
* Identify edge cases and boundary conditions

6. Final Optimized Prompt

* Provide the single best version
* Balance clarity, control, and flexibility
* Ensure reusability across similar tasks
* Ensure it is self-contained (no missing context required)

7. Acceptance Criteria
   The final prompt MUST:

* Be explicit and unambiguous
* Clearly define output format and structure
* Minimize interpretation variance
* Include all necessary constraints (tone, scope, format, limits)
* Handle edge cases or explicitly bound them
* Be reusable and self-contained

8. Evaluation Rubric (Score 1–5 for each with brief justification)

* Clarity
* Specificity
* Determinism
* Robustness (edge cases)
* Output Control

9. Assumption Policy

* Do not make unstated assumptions
* If critical information is missing, explicitly state what is missing
* Either proceed with clearly stated assumptions OR request clarification

10. Output Constraints

* Define expected output length (if applicable)
* Define format strictly (e.g., bullet points, JSON, paragraph)
* Avoid unnecessary verbosity

11. Default Behaviors

* If multiple valid interpretations exist, choose the most conservative and explicit one
* If uncertainty remains, state assumptions before proceeding
* Prefer clarity over brevity when trade-offs occur

12. Self-Check and Refinement

* Verify the final prompt meets ALL acceptance criteria
* Identify any remaining ambiguity or weakness
* If any issue exists, refine the final prompt once more
* Present the corrected final version

13. Output Format (STRICT)
    Use exactly these section headers in this order:

* Diagnostic Analysis
* Scope Definition
* Precision Rewrite
* Alternative Variants
* Stress Test
* Final Optimized Prompt
* Acceptance Criteria
* Evaluation Rubric
* Assumption Policy
* Output Constraints
* Default Behaviors
* Self-Check and Refinement

Rules:

* Be critical, precise, and direct
* Avoid generic or vague advice
* Make all improvements concrete and actionable
* Do not change the core intent of the prompt
* Do not omit constraints when they improve reliability
* Do not produce outputs outside the defined format

Prompt to evaluate:
${paste_prompt_here}

Goal:
${describe_the_exact_desired_output}

(Optional) Example of ideal output:
${provide_if_available}

INPUTS

paste_prompt_here REQUIRED: The prompt text to evaluate and optimize
describe_the_exact_desired_output REQUIRED: Description of the exact desired output for the evaluated prompt
provide_if_available: Optional example of ideal output for the evaluated prompt

REQUIRED CONTEXT

prompt to evaluate
goal description

OPTIONAL CONTEXT

example of ideal output

ROLES & RULES

Role assignments

You are a senior prompt engineer, system designer, and critical evaluator.

You must follow every step strictly. Do not skip, merge, or reorder steps.
Be critical, precise, and direct
Avoid generic or vague advice
Make all improvements concrete and actionable
Do not change the core intent of the prompt
Do not omit constraints when they improve reliability
Do not produce outputs outside the defined format
Do not make unstated assumptions
If critical information is missing, explicitly state what is missing
If multiple valid interpretations exist, choose the most conservative and explicit one
If uncertainty remains, state assumptions before proceeding
Prefer clarity over brevity when trade-offs occur

EXPECTED OUTPUT

Format

markdown

Schema

markdown_sections · Diagnostic Analysis, Scope Definition, Precision Rewrite, Alternative Variants, Stress Test, Final Optimized Prompt, Acceptance Criteria, Evaluation Rubric, Assumption Policy, Output Constraints, Default Behaviors, Self-Check and Refinement

Constraints

Use exactly these section headers in this order: Diagnostic Analysis, Scope Definition, Precision Rewrite, Alternative Variants, Stress Test, Final Optimized Prompt, Acceptance Criteria, Evaluation Rubric, Assumption Policy, Output Constraints, Default Behaviors, Self-Check and Refinement
Be critical, precise, and direct
Do not produce outputs outside the defined format

SUCCESS CRITERIA

Rigorously analyze, optimize, and validate the given prompt for maximum clarity, determinism, robustness, and consistent high-quality output
Follow every step strictly
Provide diagnostic analysis including strengths, weaknesses, assumptions, risks
Define scope and boundaries
Rewrite prompt precisely preserving original goal
Provide alternative variants
Conduct stress test with failure scenarios
Deliver single best optimized prompt
Meet all acceptance criteria
Score with evaluation rubric
Verify with self-check and refinement

FAILURE MODES

Skipping, merging, or reordering steps
Altering the core intent of the evaluated prompt
Producing outputs outside the strict format
Making unstated assumptions without disclosure
Overlooking edge cases or boundary conditions
Providing generic or vague advice
Failing to handle missing information in placeholders
Interpreting placeholders literally instead of as variables

CAVEATS

Dependencies

Requires prompt to evaluate via ${paste_prompt_here}
Requires goal description via ${describe_the_exact_desired_output}
Optionally requires example of ideal output via ${provide_if_available}

Missing context

Example of a complete ideal output using the strict format.
Numerical limits for section lengths or total output.
Handling if placeholders like ${paste_prompt_here} are empty or invalid.

Ambiguities

Overlap between instructional steps 1-12 and required output section headers in 13; unclear if output reproduces instructions verbatim or generates new analytical content under each.
Unclear what content to place under output headers like 'Acceptance Criteria', 'Assumption Policy', etc., which are already defined as instructions.
'Goal: ${describe_the_exact_desired_output}' and 'Example' appear intended for the evaluated prompt but placement may confuse if not filled.

QUALITY

OVERALL: 0.85
CLARITY: 0.75
SPECIFICITY: 0.95
REUSABILITY: 0.90
COMPLETENESS: 0.85

IMPROVEMENT SUGGESTIONS

Merge redundant steps (e.g., combine Assumption Policy, Default Behaviors into Diagnostic Analysis) to reduce overlap and length.
Clarify output header content expectations, e.g., 'Under Acceptance Criteria: Verify final prompt against the list with yes/no and explanations.'
Switch to a JSON-structured output format for easier parsing and less verbosity while maintaining sections as keys.
Add instructions for handling missing placeholders, e.g., 'If Goal is unspecified, infer from prompt or state assumption.'

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.