This repository is a collection of Claude/Anthropic skills and platform documentation rather than a standalone application. It contains skill definitions (SKILL.md files), MCP server evaluation guidance, managed-agents documentation, and supporting tooling such as schema definitions and build scripts. The dominant character is developer-facing content and reusable patterns for building LLM agents, with some executable scripts for validation and report generation. It provides structured output schemas for evaluation pipelines (grading, benchmark, comparison, analysis), a validator hierarchy for XML/XSD-based skill files, and a security-conscious file I/O example in build-report-lite.mjs. It also documents managed agents, platform availability, and MCP best practices. The repository is not a data research project; there are no notebooks, data pipelines, or model training scripts. Maintenance is active, but technical drift is medium due to version-sensitive SDK references, manually maintained platform availability tables, and multiple language-specific examples that must be kept in sync. The code and schemas are generally well-structured and reusable, though some paths are hardcoded and some documentation is tightly coupled to generator scripts.

This repository is the official open-source companion to Anthropic's Claude Code—an agentic AI coding assistant that operates in the terminal. It is not the core Claude Code binary (distributed separately via npm/brew/install scripts), but rather the plugin ecosystem, example configurations, CI automation scripts, and infrastructure-as-code templates that extend and support the tool. The repo contains 13 first-party plugins (e.g., security-guidance, code-review, feature-dev, commit-commands, pr-review-toolkit, hookify, plugin-dev), each defining hooks, commands, agents, and skills that integrate with Claude Code's extensibility framework. It also provides production-grade Terraform modules for deploying a Claude Code Gateway on AWS (ECS Fargate + RDS + Bedrock) and GCP (Cloud Run + Cloud SQL + Vertex AI), along with enterprise MDM settings (macOS plist/mobileconfig, Windows ADMX, Intune scripts) and managed settings templates. A suite of GitHub Actions workflows handles automated issue triage, duplicate detection, lifecycle management, and code review, all using Claude Code itself as the automation engine. The repository is primarily a configuration and extension catalog rather than a standalone application; its value lies in demonstrating the plugin architecture and providing reusable patterns for AI-assisted development workflows.

This repository is a reference architecture and plugin collection for deploying AI agents in financial services using Anthropic's Claude platform. It defines 10+ named agents (e.g., Pitch Agent, Earnings Reviewer, KYC Screener) and 100+ skills that guide Claude to produce institutional-grade financial documents: Excel valuation models (DCF, LBO, comps), PowerPoint pitch decks, Word research reports, and HTML earnings previews. The architecture follows a dual-delivery model: agents can be installed as Claude Cowork plugins via marketplace registration, or deployed headlessly via the Managed Agents API (agent.yaml manifests in managed-agent-cookbooks). Skills are authored in vertical plugins organized by domain (investment banking, equity research, private equity, wealth management) and synced into agent bundles. The repository also includes a Microsoft 365 add-in installer (claude-for-msft-365-install) for deploying Claude into Excel, Word, PowerPoint, and Outlook. Data flows rely heavily on MCP servers (LSEG, S&P Global, Daloopa, FactSet) and SEC EDGAR for financial data, with strict citation and formula-over-hardcode conventions. The repo is primarily prompt engineering and configuration rather than application runtime code, but it includes several reusable Python scripts for skill scaffolding, document validation, and cross-reference linting.

This is the official curated marketplace and development toolkit for Claude Code plugins, maintained by Anthropic. It contains both first-party plugins (e.g., claude-security, code-modernization, hookify, skill-creator, security-guidance) and third-party channel integrations (Discord, iMessage, Telegram, GitHub, Linear, etc.). The repository serves dual roles: as a plugin registry with standardized packaging (SKILL.md, agent definitions, hooks, commands, MCP servers) and as a meta-development kit providing tools for authoring and validating new plugins. The codebase is predominantly instructional content for Claude Code (markdown workflows, agent system prompts, skill references) orchestrated through hooks, workflows, and commands. While many plugins contain only reference documentation and no executable code, security-critical plugins like claude-security and security-guidance include sophisticated Python/JavaScript logic for vulnerability scanning, patch generation, session state management, and git diff analysis. The CI pipeline enforces licensing (Apache 2.0), validates plugin structure, checks MCP URL liveness, and manages SHA-pinned external plugin versions. The project is actively maintained but exhibits technical drift from duplicated access-control logic across channel servers, hardcoded model references, and reliance on Claude Code CLI internals that may change between versions.

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 is a cross-platform sandbox runtime library developed by Anthropic for securely executing untrusted commands within restricted environments. It is designed to be embedded by AI agent runtimes (such as Claude Code) to enforce network and filesystem access controls, perform TLS-terminating HTTP/SOCKS proxying, and mask credentials like API keys and AWS SigV4 secrets. The system operates as a filtering forward proxy with an optional external 'decider' process for per-request allow/deny/body-inspection verdicts, and it supports Linux (via bubblewrap + seccomp), macOS (via Seatbelt profiles), and Windows (via WFP and a Rust helper). The repository is primarily an application library with a CLI tool (`srt`), not a data or research project. It demonstrates high engineering quality with extensive test coverage, careful security invariants, and thoughtful handling of platform edge cases. However, its complexity is extreme—spanning three OS backends, custom proxy servers, TLS MITM, credential injection, and violation monitoring—and it carries significant drift risks from external binary dependencies, runtime-specific workarounds, and a large test surface with conditional skips.