parcadei/continuous-claude-v3

Run comprehensive health checks on all Claude Code components.

Source details, install context, and public review data are available on the full page.

Show a beautiful dashboard with token usage, actual API costs, TLDR savings, and hook activity.

Note: The current year is 2025. When validating tech choices, check against 2024-2025 best practices.

Build AI agents in Python using the Agentica framework. Agents can implement functions, maintain state, use tools, and coordinate with each other.

Complete reference for running Agentica SDK with a local Claude proxy. This enables Python agents to use Claude CLI as their inference backend.

Run QLTY checks during code writing to catch issues early.

When implementing SDK features or debugging provider-specific issues, check reference implementations.

Use the most token-efficient search tool for each query type.

Use the most token-efficient search tool for each query type.

Show users how Continuous Claude works - the opinionated setup with hooks, memory, and coordination.

Orchestrate TDD migrations with agents doing all work. Main context stays clean.

Use this skill after user selects an Agentica pattern.

When building infrastructure components, ensure they're actually invoked in the execution path.

Search Mathlib for lemmas by type signature pattern.

Search across 3000+ packages (npm, PyPI, Crates, Go) and indexed sources for documentation and code examples.

Cognitive prosthetics for unit-aware computation. Use Pint for converting between units, performing unit arithmetic, checking dimensional compatibility, and simplifying compound units.

Friendly onboarding when users ask about capabilities.

Source details, install context, and public review data are available on the full page.