Skill Perfv1.0.2

A developer wants to measure the token consumption and latency of a custom skill before deploying it to production. Using skill-perf, they can run concurrent tests, compare hot vs. cold cache performance, and generate a detailed HTML report with confidence ratings, ensuring the skill meets SLA requirements.

An AI architect is evaluating two alternative skill implementations for the same task (e.g., text summarization vs. keyword extraction) to determine which is more token-efficient. skill-perf executes both skills side-by-side, subtracting system noise, and provides a clear cost comparison to guide architecture decisions.

Before releasing a skill update, a QA engineer runs skill-perf to verify that the new version does not regress in terms of token usage or response time. The tool automatically generates a benchmark report that can be included in release notes or CI/CD pipeline gate checks.

A product manager notices user complaints about slow responses from a skill. They use skill-perf to measure actual latency and token consumption under different loads, identifying bottlenecks and validating the impact of subsequent optimizations.

An enterprise needs to audit third-party skills for cost efficiency before integration. skill-perf provides unbiased performance metrics and a confidence rating, helping the procurement team make data-driven decisions.

Offer skill-perf as a metered service where customers pay per benchmark run. This aligns with usage-based pricing and appeals to developers who want to validate performance before committing to larger subscriptions.

Bundle skill-perf with a performance SLA for enterprise customers. The tool provides evidence of meeting token and latency targets, enabling premium pricing for guaranteed performance.

License skill-perf as an automated plugin for continuous integration pipelines. Teams set up automated benchmarks on every skill update, reducing manual testing effort and ensuring consistent quality.