plugin-discovery-patterns Skill
Use when making a system extensible at runtime. Covers plugin discovery via Python entry points, a file-based plugin registry, multi-backend provider abstractions, and schema-driven input validation. Published by microsoft in amplifier-bundle-skills.
Decision snapshot
Is this a fit?
Design and media, Includes SKILL.md, Reusable instructions
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Copy skill directory
2 months ago · MIT license
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What is plugin-discovery-patterns Skill?
Use when making a system extensible at runtime. Covers plugin discovery via Python entry points, a file-based plugin registry, multi-backend provider abstractions, and 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.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Design and media
- Design and media use cases
Declared skill metadata
- Source file: skills/plugin-discovery-patterns/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use plugin-discovery-patterns Skill
- Use it for design and media.
Built with
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 at runtime. Covers plugin discovery via Python entry points, a file-based plugin registry, multi-backend provider abstractions, and 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
Verified compatibility and discovery
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 at runtime. Covers plugin discovery via Python entry points, a file-based plugin registry, multi-backend provider abstractions, and schema-driven input.
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.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
