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config-state-patterns Skill

AI Agent SkillPythonOpen source

Use when your tool needs persistent configuration files with safe defaults merging, atomic state writes that survive crashes, or conventional file locations for config vs state vs secrets. Published by microsoft in amplifier-bundle-skills.

What is config-state-patterns Skill?

Use when your tool needs persistent configuration files with safe defaults merging, atomic state writes that survive crashes, or conventional file locations for config vs state vs secrets. Published by microsoft in amplifier-bundle-skills. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
26/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Data analysis
  • Design and media
  • Writing
  • Data analysis use cases
  • Design and media use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use config-state-patterns Skill

  • Use it for data analysis.
  • Use it for design and media.
  • Use it for writing.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: microsoft
  • Repository: microsoft/amplifier-bundle-skills
  • Skill file: skills/config-state-patterns/SKILL.md

What it does

Use when your tool needs persistent configuration files with safe defaults merging, atomic state writes that survive crashes, or conventional file locations for config vs state vs secrets.

Skill instructions

Configuration & State Management The Pattern Problem: Your tool has user-configurable settings (host, port, auth mode) and runtime state (which sessions are active, device heartbeats) that must persist across restarts and handle concurrent reads/writes safely. Approach: Separate config from state. Use a defaults-merge-overlay pattern with known-keys-only filtering for settings. Use atomic writes (write-to-tmp-then-os.replace) for state. Use asyncio locks for concurrent access. Follow XDG-conventional paths. Pattern proven in production across multiple Python CLI tools and web services. Key Design Decisions 1. Defaults-merge-overlay — never trust the file alone The settings file might be from an older version (missing new keys) or a newer version (has keys we don't understand). The loadsettings() pattern handles both: python def loadsettings() - dict: result = copy.deepcopy(DEFAULTSETTINGS) start with ALL defaults try: text = SETTINGSPATH.readtext() data = json.loads(text) for key in DE

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Frequently asked questions

What is config-state-patterns?

config-state-patterns is a open-source AI agent skill with Copy skill directory. Use when your tool needs persistent configuration files with safe defaults merging, atomic state writes that survive crashes, or conventional file locations for config vs state vs secrets.

Who is config-state-patterns best for?

config-state-patterns is best for reusing agent instructions, scripts, and references, data analysis workflows, design and media workflows, writing workflows.

How do I install config-state-patterns?

Install or run config-state-patterns using Copy skill directory. Check config-state-patterns for the latest setup command.

Is config-state-patterns actively maintained?

config-state-patterns may need a closer maintenance check before production use.

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Stars
10
Forks
9
Last commit
9 days ago
Repository age
5 months
License
MIT

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