skill-adapter: Analyzes existing plugins to extract their capabilities, then adapts and applies those skills to the current task. Acts as a universal skill chameleon that learns from other plugins. Activates when you request "skill adapter" functionality.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
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skills listSkill Instructions
name: skill-adapter description: | Analyzes existing plugins to extract their capabilities, then adapts and applies those skills to the current task. Acts as a universal skill chameleon that learns from other plugins. Activates when you request "skill adapter" functionality. allowed-tools: Read, Grep, Glob, Bash version: 1.0.0
Skill Adapter - Universal Plugin Capability Extractor
Purpose
Analyzes plugins in the claude-code-plugins marketplace to understand their capabilities, extracts the core patterns and approaches, then adapts those skills to solve the current user's task. Acts as a "skill chameleon" that can adopt any plugin's capabilities.
How It Works
1. Task Analysis
When user presents a task:
- Identify the core capability needed (e.g., "analyze code quality", "generate documentation", "automate deployment")
- Determine the domain (security, devops, testing, etc.)
- Extract key requirements and constraints
2. Plugin Discovery
Search existing plugins for relevant capabilities:
# Find plugins in relevant category
ls plugins/community/ plugins/packages/ plugins/examples/
# Search for keywords in plugin descriptions
grep -r "keyword" --include="plugin.json" plugins/
# Find similar commands/agents
grep -r "capability-name" --include="*.md" plugins/
3. Capability Extraction
For each relevant plugin found, analyze:
Commands (commands/*.md):
- Read the markdown content
- Extract the approach/methodology
- Identify input/output patterns
- Note any scripts or tools used
Agents (agents/*.md):
- Understand the agent's role
- Extract problem-solving approach
- Note decision-making patterns
- Identify expertise areas
Skills (skills/*/SKILL.md):
- Read the skill instructions
- Extract core capability
- Note trigger conditions
- Understand tool usage patterns
**Scripts (scripts/.sh, .py):
- Analyze script logic
- Extract reusable patterns
- Identify best practices
- Note error handling approaches
4. Pattern Synthesis
Combine learned patterns:
- Merge multiple approaches if beneficial
- Adapt to current context and constraints
- Simplify or enhance based on user needs
- Ensure compatibility with current environment
5. Skill Application
Apply the adapted skill:
- Use the learned approach
- Follow the extracted patterns
- Apply best practices discovered
- Adapt syntax/tools to current context
Example Workflows
Example 1: Learning Code Analysis from Security Plugins
User task: "Analyze this codebase for issues"
Process:
- Search for security and code-analysis plugins
- Find:
owasp-top-10-scanner,code-quality-enforcer,security-audit-agent - Extract patterns:
- OWASP scanner checks for: SQL injection, XSS, CSRF, auth issues
- Quality enforcer looks at: complexity, duplication, standards
- Audit agent examines: dependencies, secrets, permissions
- Synthesize approach:
- Run multi-layer analysis
- Check security patterns first
- Then code quality metrics
- Then dependency issues
- Apply to user's codebase with adapted checks
Example 2: Adopting Documentation Skills
User task: "Generate API documentation"
Process:
- Find documentation plugins
- Discover:
api-documenter,openapi-generator,readme-builder - Extract approaches:
- API documenter: parses code, generates OpenAPI spec
- OpenAPI generator: creates interactive docs
- README builder: structures documentation hierarchically
- Synthesize:
- Parse code for endpoints
- Generate OpenAPI/Swagger spec
- Create interactive documentation
- Build comprehensive README
- Apply combined approach to user's API
Example 3: Learning Automation from DevOps Plugins
User task: "Automate deployment process"
Process:
- Search DevOps category
- Find:
deployment-automation,ci-cd-pipeline,docker-compose-generator - Extract patterns:
- Deployment automation: build → test → deploy → verify
- CI/CD pipeline: trigger conditions, parallel jobs, rollback
- Docker compose: service orchestration, environment management
- Synthesize deployment workflow
- Apply to user's specific tech stack
Reasoning Process
When to Use Skill Adapter
Trigger when:
- User needs capability that might exist in marketplace
- Task could benefit from existing plugin patterns
- User asks: "Is there a plugin for this?"
- Similar problems have been solved before
- Multiple approaches could be combined
Plugin Selection Criteria
Choose plugins based on:
- Relevance: Matches task domain/requirements
- Quality: Well-documented, clear approach
- Simplicity: Not overly complex for the task
- Recency: Updated plugins preferred
- Popularity: Featured or well-maintained plugins
Adaptation Strategy
When adapting skills:
- Keep: Core logic and proven patterns
- Adapt: Syntax, tool names, specific commands
- Enhance: Add error handling, user feedback
- Simplify: Remove unnecessary complexity
- Contextualize: Adjust to user's environment
Limitations and Boundaries
What Skill Adapter CAN Do:
✅ Read and analyze plugin source code ✅ Extract patterns and approaches ✅ Adapt methodologies to new contexts ✅ Combine multiple plugin capabilities ✅ Apply learned skills with reasoning
What Skill Adapter CANNOT Do:
❌ Execute compiled code (MCP servers) ❌ Access external APIs without credentials ❌ Modify original plugins ❌ Guarantee exact plugin behavior replication ❌ Use plugins that require specific environment setup
Success Criteria
Skill adaptation is successful when:
- User's task is completed effectively
- Approach borrowed makes logical sense
- Adapted skill is properly contextualized
- User understands where the approach came from
- Result quality matches or exceeds original plugin
Transparency
Always inform user:
- Which plugins were analyzed
- What patterns were extracted
- How the skill was adapted
- Why this approach was chosen
- Any limitations of the adaptation
Example Usage
User: "I need to validate JSON schemas in my project"
Skill Adapter Process:
1. Searches plugins for JSON validation
2. Finds: schema-validator, json-lint-enforcer
3. Extracts: ajv library usage, error formatting patterns
4. Adapts: Uses available tools (jq, node, python)
5. Applies: Validates user's schemas with detailed errors
6. Reports: "I adapted the schema-validator approach using jq
for validation and added custom error formatting"
Meta-Learning
Skill Adapter improves by:
- Tracking which plugins solve which tasks best
- Learning which patterns are most reusable
- Noting which adaptations work well
- Building a mental model of the marketplace
- Understanding plugin ecosystem relationships
In essence: Skill Adapter is a meta-skill that makes the entire plugin marketplace available as a learning resource, extracting and applying capabilities on-demand to solve user tasks efficiently.
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