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Run npx skillmds@latest add tomevault-io/evaluator-optimizer in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Evaluator Optimizer free to use?

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Who published Evaluator Optimizer?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Evaluator Optimizer by tomevault-io

Name: Evaluator Optimizer
Author: tomevault-io

Evaluator Optimizer

Iterative refinement workflow for polishing code, documentation, or designs through systematic evaluation and improvement cycles. Use when refining drafts into production-grade quality. Use when this capability is needed.

tomevault-io 5234c32 2 files · 3.7 KB Updated Sep 17, 2026

File contents

Evaluator-Optimizer

Iterative refinement workflow that takes existing code, documentation, or designs and polishes them through rigorous cycles of evaluation and improvement until they meet production-grade quality standards.

When to Use This Skill

Refining a rough draft of code into production quality
Polishing documentation for clarity, completeness, and accuracy
Iteratively improving a design or architecture proposal
Systematic quality improvement where "good enough" is not sufficient
When you need to converge on high quality through structured iteration

Quick Reference

Task	Load reference
Evaluation criteria and quality rubrics	`skills/evaluator-optimizer/references/evaluation-criteria.md`

Workflow: The Loop

For any given artifact (code, text, design):

Accept: Take the current version of the artifact.
Evaluate: Act as a harsh critic. Rate the artifact on correctness, clarity, efficiency, style, and safety. Assign a score out of 100.
Decide:
- Score >= 90: Stop and present the result.
- Score < 90: Refine.
Refine: Rewrite the artifact, specifically addressing the critique from step 2. List what changed and why.
Repeat: Return to step 2 with the new version.

Behavioral Rules

Do not settle: "Good enough" is not good enough. You are here to polish.
Be explicit: When evaluating, list specific flaws. "The function process_data is O(n^2) but could be O(n)."
Show your work: Summarize changes in each iteration.
Self-correct: If a refinement breaks something, revert and try a different approach.
Converge: Each iteration must improve the score. If two consecutive iterations do not improve the score, stop and present the best version.

Iteration Output Template

## Iteration [N] Evaluation

| Criterion | Score (1-10) | Notes |
|-----------|-------------|-------|
| Correctness | | |
| Clarity | | |
| Efficiency | | |
| Style | | |
| Safety | | |
| **Total** | **/50** | **[x100/50]** |

### Issues Found
1. [Specific issue with location]
2. [Specific issue with location]

### Refinements Applied
- [Change 1 and rationale]
- [Change 2 and rationale]

Example Interaction

Input: "Refine this Python script."

Iteration 1 Evaluation:

Functionality: Good
Efficiency: Poor - uses nested loops for matching
Style: Variable names a and b are unclear
Score: 60/100

Refinements applied:

Flattened loops using a set lookup (O(n))
Renamed a to users, b to active_ids
Added type hints

Iteration 2 Evaluation:

Functionality: Good
Efficiency: Excellent
Style: Good
Score: 95/100

Result: Present the refined script.

Converted and distributed by TomeVault — claim your Tome and manage your conversions.

---name: evaluator-optimizerdescription: Iterative refinement workflow for polishing code, documentation, or designs through systematic evaluation and improvement cycles. Use when refining drafts into production-grade quality. Use when this capability is needed.---# Evaluator-OptimizerIterative refinement workflow that takes existing code, documentation, or designs and polishes them through rigorous cycles of evaluation and improvement until they meet production-grade quality standards.## When to Use This Skill- Refining a rough draft of code into production quality- Polishing documentation for clarity, completeness, and accuracy- Iteratively improving a design or architecture proposal- Systematic quality improvement where "good enough" is not sufficient- When you need to converge on high quality through structured iteration## Quick Reference| Task | Load reference || --- | --- || Evaluation criteria and quality rubrics | `skills/evaluator-optimizer/references/evaluation-criteria.md` |## Workflow: The LoopFor any given artifact (code, text, design):1. **Accept**: Take the current version of the artifact.2. **Evaluate**: Act as a harsh critic. Rate the artifact on correctness, clarity, efficiency, style, and safety. Assign a score out of 100.3. **Decide**: - Score >= 90: **Stop** and present the result. - Score < 90: **Refine**.4. **Refine**: Rewrite the artifact, specifically addressing the critique from step 2. List what changed and why.5. **Repeat**: Return to step 2 with the new version.## Behavioral Rules- **Do not settle**: "Good enough" is not good enough. You are here to polish.- **Be explicit**: When evaluating, list specific flaws. "The function `process_data` is O(n^2) but could be O(n)."- **Show your work**: Summarize changes in each iteration.- **Self-correct**: If a refinement breaks something, revert and try a different approach.- **Converge**: Each iteration must improve the score. If two consecutive iterations do not improve the score, stop and present the best version.## Iteration Output Template```markdown## Iteration [N] Evaluation| Criterion | Score (1-10) | Notes ||-----------|-------------|-------|| Correctness | | || Clarity | | || Efficiency | | || Style | | || Safety | | || **Total** | **/50** | **[x100/50]** |### Issues Found1. [Specific issue with location]2. [Specific issue with location]### Refinements Applied- [Change 1 and rationale]- [Change 2 and rationale]```## Example Interaction**Input**: "Refine this Python script."**Iteration 1 Evaluation**:- Functionality: Good- Efficiency: Poor - uses nested loops for matching- Style: Variable names `a` and `b` are unclear- Score: 60/100**Refinements applied**:- Flattened loops using a set lookup (O(n))- Renamed `a` to `users`, `b` to `active_ids`- Added type hints**Iteration 2 Evaluation**:- Functionality: Good- Efficiency: Excellent- Style: Good- Score: 95/100Result: Present the refined script.---> Converted and distributed by [TomeVault](https://tomevault.io/claim/nickcrew) — claim your Tome and manage your conversions.

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