This repository is the source of specify-cli, the flagship Python CLI of Spec Kit. In production it is a Typer-based developer tool that bootstraps projects for Spec-Driven Development: `specify init` scaffolds a `.specify/` structure, installs shared bash/PowerShell/Python helper scripts, and generates agent command/skill files into 37+ AI coding-tool directories (Claude, Copilot, Codex, Gemini, Cursor, Grok, Qwen, Tabnine, Goose, and more). Beyond scaffolding, the tool manages a layered ecosystem of extensions, presets, bundles, and YAML-defined workflows, plus a self-upgrade path that detects uv/pipx/uvx installations and pulls releases from the GitHub API.
Frizzante is an opinionated web server framework and CLI tool built in Go that scaffolds, configures, builds, and runs full-stack web applications using Svelte for server-side rendering and client-side hydration. The CLI provides a TUI menu system for project creation, dependency management (Go, Bun, Air, sqlc), development with live reload, building production binaries, testing, and more. The scaffolded project includes a complete web server with session management, SQLite database, guards, and a todo list example. The architecture separates the CLI layer (menus, actions, generations) from the scaffolded project's library (core, views, security, servers, routes). The codebase demonstrates strong Go engineering with build tags for conditional compilation, extensive use of embedded files, and a well-structured TUI using Bubble Tea.
This is a monorepo of ~100 Claude Code skills — self-contained plugins that extend Claude Code's capabilities across personal automation, research, content creation, development tooling, and communication. Each skill is a directory with a SKILL.md (trigger definition), scripts/, references/, and assets/. The architecture is plugin-based: Claude Code matches user requests to skill triggers and executes the associated scripts. Skills range from simple CLI wrappers (e.g., YouTube transcript extraction) to multi-step pipelines (e.g., PII redaction with confide, release orchestration with cull-release, interview-driven skill design with skill-studio). The codebase demonstrates strong patterns: reversible PII redaction with typed placeholders, exact permutation statistics, weighted scoring with Pareto frontiers, and structured TDD loops. However, it also has technical debt: hardcoded user paths, some deprecated library usage, external API coupling, and a few design-spec-only skills. The dominant character is application (CLI tools and agent plugins), though several skills involve data analysis (health queries, experiment evaluation, evidence grading).
This repository provides a comprehensive CLI toolkit and programmatic interface (Python SDK and notebook clients) for creating, deploying, managing, monitoring, and evaluating AI agents on Amazon Bedrock AgentCore. The system supports multiple agent frameworks (Strands, LangChain/LangGraph, CrewAI, AutoGen, OpenAI Agents, Google ADK) and infrastructure-as-code options (CDK, Terraform). Key capabilities include project scaffolding via Jinja2 templates, runtime lifecycle management (configure, launch, destroy, invoke), memory management (short-term/long-term, semantic, user preference), observability (CloudWatch-based trace and log querying with OpenTelemetry span parsing), evaluation (LLM-as-a-judge with built-in and custom evaluators), policy engine CRUD, gateway management (MCP, API key, Cognito OAuth), and identity federation setup. The codebase is well-structured with a clear three-layer architecture (CLI -> operations -> services), extensive test coverage, and consistent error handling. However, the project is explicitly deprecated in favor of the @aws/agentcore NPM CLI, meaning future development is minimal and users are encouraged to migrate. Despite the deprecation, the reusable abstractions (e.g., CloudWatch query builder, trace processor, strategy models, configuration schemas) demonstrate solid software craftsmanship.