This repository is a local-first, source-cited knowledge base management system, delivered primarily as a Claude Code plugin and a standalone Python CLI tool. It manages Obsidian vaults with a strong emphasis on data integrity, provenance tracking, and deterministic operations. The architecture is a monolithic Python library (`claude_obsidian/`) with a formal transaction system for all vault mutations, a robust lint engine, and a retrieval pipeline (BM25 + optional semantic reranking). It features a sophisticated skill/agent framework for AI integration across multiple hosts (Claude, Cursor, Windsurf, etc.). While primarily an application, it incorporates significant data engineering and research data management (RDM) patterns. The provenance ledger system (`ledgers.py`) enforces strict schemas for sources and claims, including canonical URL handling, content-addressed identity, and evidence validation rules. The retrieval pipeline implements Anthropic's Contextual Retrieval pattern. This hybrid nature makes it a powerful tool for both knowledge management and structured research workflows. The codebase demonstrates exceptionally high craftsmanship in its transaction system, defensive I/O, and deterministic analysis tools. It is actively maintained with a comprehensive test suite and a formal release process. Its primary limitation is platform dependency on Linux/macOS for write operations (WSL required for Windows).
Humanizer is a skill (prompt) for AI agents that rewrites AI-generated text to sound human-written without altering factual content. It is built on Wikipedia's 'Signs of AI writing' guide and provides 26 numbered patterns grouped into six categories (staging, rhythm, inflation, formatting, leftovers, wrong reader). The skill is distributed as a single markdown file (SKILL.md) with YAML metadata, installable via plugin manifests for Claude Code, Cursor, and other agents through the Skills CLI. The repository also includes a validation script, issue templates, and CI workflows to maintain consistency across package files. While not a traditional software application, it functions as a tool that agents execute, with clear entry points (/humanizer command) and a well-defined workflow (mark tells, draft rewrite, check, finalize). The codebase is meticulously maintained with active issue triage, regular releases, and automated validation.
This is a mature, actively maintained AI agent skill called 'last30days' that enables agents (Claude Code, Codex, Grok, Gemini CLI, MCP hosts) to research any topic by aggregating content from 20+ social and news platforms (Reddit, X, YouTube, TikTok, Instagram, Hacker News, Polymarket, GitHub, arXiv, Techmeme, Digg, and more) over a rolling 30-day window. The system is primarily a CLI engine (Python) with a companion Go MCP server for Claude Desktop. It employs a sophisticated pipeline: query planning by intent, parallel retrieval from multiple backends (keyless APIs, paid scrapers, CLI tools, LLM-based search), source-specific normalization, engagement-weighted relevance scoring, cross-source clustering, and deterministic fusion (weighted RRF) with per-author caps and diversity floors. Output is rendered as structured JSON, compact text, or self-contained HTML with optional publishing and Atom feeds. The codebase emphasizes security (credential hygiene, no browser cookie reads in unattended mode), determinism (fixture-based evaluation harness with grounding/recency/coherence scores), and graceful degradation (per-source fallback chains, never-raise error envelopes). While classified as an application (it's a skill/plugin for agent hosts), it exhibits strong data engineering traits: source adapters, normalization pipelines, scoring models, and an offline evaluation framework.
The Agentic Startup repository is a spec-driven development (SDD) framework for Claude Code that enables multi-agent AI collaboration for software development. It provides a structured workflow: specify → validate → implement → test → review → document, with optional skills for analysis, refactoring, debugging, and constitution enforcement. The framework uses three implementation tiers (Direct, Incremental, Factory) selected by an automatic complexity classifier, and enforces quality gates through validation checks, drift detection, and constitution-based governance rules (L1/L2/L3 levels). Key features include progressive disclosure for context efficiency, information barriers to prevent bias, and automatic documentation generation. The system is designed as a plugin-based architecture with 'start' (core workflow) and 'team' (specialized agents) components, storing specifications in .start/specs/ and generating documentation in docs/.
Claude Delegator is a Claude Code plugin that provides GPT (via Codex CLI) and Gemini (via Gemini CLI) as specialized expert subagents. It offers five domain experts (Architect, Plan Reviewer, Scope Analyst, Code Reviewer, Security Analyst) that can advise or implement based on task requirements. The plugin uses MCP (Model Context Protocol) to connect to external CLIs, featuring sophisticated delegation logic with proactive triggers, session management (single-shot and multi-turn), and response synthesis. A key innovation is the zero-dependency Gemini MCP bridge that wraps the Gemini CLI in a standard MCP interface.
This repository is a comprehensive plugin marketplace and reference implementation for legal practice automation using Anthropic's Claude AI. It contains 12 first-party plugins (commercial, corporate, employment, privacy, product, regulatory, AI governance, IP, litigation, legal clinic, law student, and a builder hub) plus one vendor plugin from Thomson Reuters. Each plugin provides a set of 'skills' (prompt-engineered workflows) invoked via slash commands, a cold-start interview to configure the AI to a specific legal professional's role and preferences, and optional scheduled agents. The repo also includes five managed-agent cookbooks demonstrating multi-agent orchestration with tool isolation (read-only subagents, write leaf, orchestrator with no write access). While the vast majority of content is markdown prompt files, the repository also contains reusable Python and shell scripts for deployment, validation, and linting of agent configurations. The system is designed to be deployed on Claude Code or Claude Cowork, with MCP connectors for legal research tools, document management, and other integrations. It emphasizes citation provenance, injection defense, and consequential-action gates for non-lawyer users.
This repository is a Claude Code plugin and design system library for generating zero-dependency HTML presentations. It provides a structured workflow (SKILL.md) for an AI agent to create single-file slide decks with inline CSS/JS, featuring 34+ curated design templates (bold-template-pack) with detailed color palettes, typography scales, component definitions, and CJK internationalization guidance. The core runtime component is a reusable `<deck-stage>` web component that handles slide navigation, keyboard controls, auto-scaling, print support, and speaker notes. Supporting scripts enable Vercel deployment, PDF export via Playwright, and PowerPoint-to-JSON extraction. The repository is primarily a design specification library consumed by an AI coding agent, not a standalone application. It exhibits a hybrid nature: the templates are extensive design documentation (not executable code), while the plugin infrastructure and web component are functional code. The design philosophy emphasizes anti-generic aesthetics, fixed 16:9 stage scaling, and progressive disclosure of supporting files. Notable duplication exists between root and plugin paths, and all templates are marked alpha.