How does it handle versioning?

It enforces a strict 'one baseline per version' rule, meaning it will overwrite previous files if the same version is processed again to ensure data integrity.

Does it record environment information?

Yes, the skill records both specific performance metrics and the environment metadata to ensure that comparisons are contextually accurate.

What is the primary purpose of this skill?

It manages performance baselines by storing metrics and metadata in a structured JSON format to help compare performance across different software versions.

Where are the baseline files stored?

Baselines are stored in a standardized directory structure, specifically under the '{state-dir}/perf/baselines/' path.

Can this be used for automated regression testing?

Absolutely. It is designed to be the canonical tool for recording and comparing performance metrics, which is a core part of regression testing.

Performance Baseline Manager

Name: Performance Baseline Manager
Author: agent-sh

byagent-sh

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692

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分析与监控

Manages and consolidates performance baselines to track software metrics across different versions.

The Performance Baseline Manager skill provides a standardized framework for storing and comparing performance data across software iterations within Claude Code. By enforcing a strict one-baseline-per-version rule and capturing both metrics and environment metadata, it allows developers to track performance regressions and improvements with precision. This skill ensures all data is stored in a structured JSON format under specific state directories, making it easy to automate the comparison of current results against historical benchmarks and maintain a clear audit trail of software efficiency.

主要功能

01Automatic overwriting of legacy baselines for current versions

02Environment metadata recording for contextual analysis

03692 GitHub stars

04Single baseline JSON enforcement per software version

05Automated metric consolidation and storage logic

06Standardized JSON output for performance reporting

使用场景

01Standardizing performance data storage for automated CI/CD workflows

02Comparing system metrics across different software release versions

03Tracking performance regressions during automated code generation

主要功能

01Automatic overwriting of legacy baselines for current versions

02Environment metadata recording for contextual analysis

03692 GitHub stars

04Single baseline JSON enforcement per software version

05Automated metric consolidation and storage logic

06Standardized JSON output for performance reporting

使用场景

01Standardizing performance data storage for automated CI/CD workflows

02Comparing system metrics across different software release versions

03Tracking performance regressions during automated code generation