ptc-orchestration
PTC Orchestration Skill
Use Programmatic Tool Calling (PTC) for efficient multi-tool workflows. PTC allows Claude to write Python code that orchestrates multiple tool calls, reducing:
- API round-trips (60% fewer calls)
- Context token usage (65% reduction)
- Execution time (53% faster)
When to Use
Activate this skill when the user needs:
- Multi-URL scraping: Fetch and compare multiple web pages
- Browser automation: Chain multiple browser actions (navigate → snapshot → click → extract)
- Tool orchestration: Any workflow with 3+ sequential tool calls
Available Commands
More from ilude/claude-code-config
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Guidelines for self-explanatory code and meaningful documentation. Activate when working with comments, docstrings, documentation, code clarity, API documentation, JSDoc, or discussing code commenting strategies. Guides on why over what, anti-patterns, decision frameworks, and language-specific examples.
12claude-code-workflow
Claude Code AI-assisted development workflow. Activate when discussing Claude Code usage, AI-assisted coding, prompting strategies, or Claude Code-specific patterns.
10css-workflow
CSS and styling workflow guidelines. Activate when working with CSS files (.css), Tailwind CSS, Stylelint, or styling-related tasks.
7api-design-patterns
Language-agnostic API design patterns covering REST and GraphQL, including resource naming, HTTP methods, status codes, versioning, pagination, filtering, authentication, error handling, and schema design. Activate when working with APIs, REST endpoints, GraphQL schemas, API documentation, OpenAPI/Swagger, JWT, OAuth2, endpoint design, API versioning, rate limiting, or GraphQL resolvers.
7container-workflow
Guidelines for containerized projects using Docker, Dockerfile, docker-compose, container, and containerization. Covers multi-stage builds, security, signal handling, entrypoint scripts, and deployment workflows.
6python-workflow
Python project workflow guidelines. Triggers: .py, pyproject.toml, uv, pip, pytest, Python. Covers package management, virtual environments, code style, type safety, testing, configuration, CQRS patterns, and Python-specific development tasks.
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