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plugin-discovery-patterns Skill

AI Agent SkillPythonOpen source

Use when making a system extensible with runtime plugin discovery via Python entry points, a file-based plugin registry, multi-backend provider abstractions, or schema-driven input validation. Published by microsoft in amplifier-bundle-skills.

What is plugin-discovery-patterns Skill?

Use when making a system extensible with runtime plugin discovery via Python entry points, a file-based plugin registry, multi-backend provider abstractions, or schema-driven input validation. 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
  • Design and media
  • Design and media use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use plugin-discovery-patterns Skill

  • Use it for design and media.

Built with

PythonCopy skill directory

Editorial notes

Source

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

What it does

Use when making a system extensible with runtime plugin discovery via Python entry points, a file-based plugin registry, multi-backend provider abstractions, or schema-driven input validation.

Skill instructions

Plugin Discovery & Abstractions The Pattern Problem: You have a tool that needs to support multiple backends (e.g., GitHub vs a self-hosted git server), load user-installed plugins (custom implementations), and validate dynamically-generated forms against schemas that change based on user actions. Approach: Two-tier plugin discovery (entry points + file-based registry), a frozen dataclass provider abstraction with auto-derived URLs, and schema-driven validation with function-call evaluation. Pattern proven in production across multiple Python CLI tools and web services. Key Design Decisions 1. Two-tier plugin discovery: entry points + file-based registry Plugins are discovered at runtime via importlib.metadata.entrypoints(): python def loadplugin(name: str) - object | None: """Load a plugin by name via entrypoints.""" try: eps = entrypoints(group="mytool.plugins") for ep in eps: if ep.name == name: pluginclass = ep.load() return pluginclass() except Exception: logger.debug("Failed to d

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Frequently asked questions

What is plugin-discovery-patterns?

plugin-discovery-patterns is a open-source AI agent skill with Copy skill directory. Use when making a system extensible with runtime plugin discovery via Python entry points, a file-based plugin registry, multi-backend provider abstractions, or schema-driven input validation.

Who is plugin-discovery-patterns best for?

plugin-discovery-patterns is best for reusing agent instructions, scripts, and references, design and media workflows.

How do I install plugin-discovery-patterns?

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

Is plugin-discovery-patterns actively maintained?

plugin-discovery-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

Auto-fetched from GitHub.

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