skills.rest
PHMbench
PHMbenchOFFICIAL
Explore all skills by this author →
GitHub

config-manager-skill

Automate PHM-Vibench experiment configuration with recursive merging and validation.

18|9|Updated Apr 20, 2025
Search Tags:#automation#templates#validation#yaml#merging#config-management#phm-vibench
One-click install
npx skills add https://github.com/PHMbench/PHM-Vibench --skill config-manager-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: config-manager-skill
Source: https://github.com/PHMbench/PHM-Vibench/tree/main/.claude/skills/config-manager-skill
Command: npx skills add https://github.com/PHMbench/PHM-Vibench --skill config-manager-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml, and includes scripts (resource) components.

What problem does it solve?

PHM-Vibench Config Manager Skill provides a centralized, predictable way to manage, validate, and generate PHM-Vibench experiment configurations, reducing manual errors and enabling reproducible workflows.

Core Features & Use Cases

  • Unified interface: a single load_config() handles all configuration needs across presets, templates, and custom builds.
  • Recursive merging and smart overrides: deeply merge nested YAML config fragments with safe defaults.
  • Validation and standardization: auto-correct naming, enforce Vbench naming conventions, and verify parameter ranges before saving.
  • Template and paper-config support: generate HSE-Prompt configurations and table-based paper experiments to accelerate research workflows.

Quick Start

Load a quickstart preset and save a validated configuration for a basic experiment.

Frequently Asked Questions about config-manager-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate YAML configuration merging for reproducible experiment workflows?▼

Automating YAML configuration merging uses recursive merging to deeply combine nested config fragments with safe defaults, creating reproducible experiment workflows while reducing manual errors.

What is the best way to validate parameter ranges and naming conventions in YAML configs?▼

Validating parameter ranges and naming conventions auto-corrects naming, enforces Vbench naming rules, and verifies parameter ranges before saving configurations to standardize outputs and prevent invalid setups.

Can I generate experiment templates and paper configurations from YAML presets?▼

Generating experiment templates and paper configurations from YAML presets supports HSE-Prompt configurations and table-based paper experiments to accelerate research workflows using a unified load_config interface.

Do I need PyYAML to manage PHM-Vibench configurations?▼

Managing PHM-Vibench configurations requires PyYAML as a dependency to parse, apply chainable updates, and safely save or export validated YAML configuration files for audit trails.

How does chainable configuration updates work when applying presets?▼

Chainable configuration updates apply presets sequentially through a unified load_config interface, allowing smart overrides to merge new YAML fragments while maintaining safe defaults for reproducible builds.

Related Skills

Explore More Software Engineering Skills→
Fudan-SMI-labFudan-SMI-lab
39

torch-npu-pyyaml-preinstall

Preinstall PyYAML before torch-npu to prevent transitive dependency failures.

Official
Intermediate
sencersoylusencersoylu

computational-study

Plan and execute computational experiments for algorithm benchmarking and ablation studies.

Community
Advanced
cloudlinesscloudliness

evaluating-llms-harness

Benchmark large language models across standardized tasks with reproducible configurations.

Community
Advanced
GeneralReasoningGeneralReasoning
4

yaml-config

Parse and validate YAML configuration files using safe_load with default merging.

Official
Intermediate