feat(skills): add agent skills as a plugin

[mkmeral]

Depends on #1740

All the hook, decorator, steering related changes are from that PR. Current PR only focuses on skills and skills plugin

Description

Motivation

See design strands-agents/docs#528

This PR adds SkillsPlugin, a first-class plugin that brings Agent Skills support to Strands. It follows the spec's progressive disclosure model: lightweight metadata (name + description) is injected into the system prompt at startup, and full instructions are loaded on-demand when the agent activates a skill via a tool call. This keeps context usage low while giving agents access to rich, task-specific instructions when needed.

Public API Changes

New SkillsPlugin class and Skill dataclass, both exported from the top-level strands package:

from strands import Agent
from strands.plugins.skills import SkillsPlugin, Skill

# Load skills from filesystem (individual dirs or parent dirs)
plugin = SkillsPlugin(skills=["./skills/pdf-processing", "./skills/"])

# Or provide Skill instances directly
skill = Skill(name="my-skill", description="A custom skill", instructions="Do the thing")
plugin = SkillsPlugin(skills=[skill])

agent = Agent(plugins=[plugin])

The plugin registers a skills tool that the agent calls to activate a skill by name. When activated, the tool returns the full instructions along with metadata (allowed tools, compatibility, location) and a listing of available resource files (scripts/, references/, assets/) for filesystem-based skills.

Skill metadata is injected into the system prompt as XML before each invocation, following the recommended format from the integration spec:

<available_skills>
<skill>
  <name>pdf-processing</name>
  <description>Extract text and tables from PDF files.</description>
  <location>/path/to/pdf-processing/SKILL.md</location>
</skill>
</available_skills>

The active skill selection is persisted to agent.state for session recovery.

Use Cases

• Skill libraries: Point the plugin at a directory of skills and let the agent pick the right one based on the user's request
• Dynamic specialization: Swap agent behavior at runtime without rebuilding prompts or agents
• Portable skills: Share skill directories across teams and agents using the Agent Skills standard format

Related Issues

#1181

Documentation PR

TBD

Type of Change

New feature

Testing

• Manually tested using jupyter notebook and set of skills from anthropic/skills repository

• 56 unit tests covering the plugin, tool, XML generation, response formatting, resource listing, session persistence, and skill resolution

• 2 integration tests against a real Bedrock model: model-driven skill activation with codeword verification, and direct tool invocation with state persistence checks

• All existing plugin tests (136 total) continue to pass

• I ran hatch run prepare

Checklist

• I have read the CONTRIBUTING document
• I have added any necessary tests that prove my fix is effective or my feature works
• I have updated the documentation accordingly
• I have added an appropriate example to the documentation to outline the feature, or no new docs are needed
• My changes generate no new warnings
• Any dependent changes have been merged and published

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[codecov]

Codecov Report

❌ Patch coverage is 95.56787% with 16 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
src/strands/plugins/skills/skills_plugin.py	93.24%	6 Missing and 4 partials ⚠️
src/strands/hooks/_type_inference.py	91.42%	3 Missing ⚠️
src/strands/plugins/plugin.py	93.33%	2 Missing ⚠️
src/strands/plugins/skills/loader.py	98.92%	0 Missing and 1 partial ⚠️

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