MEGA Code
Wisdom CurationSkill Enhancement

Verify & Strengthen

Skill Enhancement

Stop guessing whether your skills work. Benchmark every skill against real tasks, measure the ROI, and get automatically upgraded versions that perform better with fewer tokens.

Performance Score

Pass rate across held-out test queries — measures how reliably a skill triggers correctly and produces the right output. Higher is better.

Token Savings

Reduction in token usage per skill invocation after optimization. Directly translates to lower API costs and faster execution times.

Without vs. With Skill Enhancement

Most teams have no idea if their skills actually improve outcomes. Evaluation changes that.

No way to know if a skill actually helps

Every skill has a measurable performance score

Skills degrade silently over time

Continuous benchmarking catches regressions early

Manual trial-and-error to improve prompts

Automated optimization loop finds the best version

Token costs grow unchecked as skills expand

Token savings measured and optimized per skill

How It Works

A four-stage pipeline that benchmarks skills, measures ROI, and deploys upgraded versions automatically.

01

Generate Eval Queries

Realistic test prompts are generated — a mix of should-trigger and should-not-trigger cases. Edge cases and near-misses are prioritized over obvious matches to ensure rigorous evaluation.

20 eval queries generated: 10 should-trigger, 10 near-miss negatives

02

Run Benchmark Iterations

Each skill is tested with and without modifications across multiple iterations. Performance is measured on both training and held-out test sets to prevent overfitting.

Iteration 3/5 — train accuracy: 94%, test accuracy: 91% (+12% vs baseline)

03

Measure ROI

Every iteration produces concrete metrics: performance score improvements, token savings per invocation, and pass-rate deltas. No guesswork — just data.

Performance: +18% pass rate | Tokens: 2,340 → 1,870 (−20% savings)

04

Upgrade Automatically

The best-performing version is selected by test score (not train score) to avoid overfitting, then automatically applied. Your skill is upgraded with zero manual effort.

Best version selected from iteration 4 — deployed with 91% test accuracy

What You Get

A real evaluation result — showing exactly how much better the upgraded skill performs.

Evaluation Result

api-builder

Before

Pass Rate

73%

Tokens / Run

3,420

After

Pass Rate

91%

Tokens / Run

2,180

Performance:+18%
Token Savings:−36%

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