Clarc v1.0: Workflow OS for Claude Code with 63 Agents and 249 Skills
What Clarc Does
Clarc is a plugin layer for Claude Code that installs once and provides a collection of specialized agents, skills, and commands. It was forked from everything-claude-code by Affaan Mustafa in January and has grown into a comprehensive workflow system.
Key Features
- 63 specialized subagents that delegate automatically based on task type: code review, TDD, security, architecture, infrastructure, ML, etc.
- 249 skills with domain knowledge loaded on-demand: TypeScript, Python, Go, Java, PostgreSQL, Terraform, DDD, hexagonal architecture, RAG, and more
- 178 slash commands for repeatable workflows including
/plan,/tdd,/finops-audit, and/chaos-experiment - 20 language rule sets with always-on coding standards baked into every session
- Learning loop with
/learn-evalto extract patterns from sessions into persistent instinct files and/evolveto promote them into permanent skills - Multi-editor support: Cursor (96 rule files), OpenCode (65 commands), Codex CLI
Installation and Setup
Install with: npx github:marvinrichter/clarc typescript (or python, go, java, etc.)
The tool clones to ~/.clarc/ and symlinks into ~/.claude/. Updates are handled via git pull.
Current Status
Version 1.0 is available but has rough edges. The learning flywheel is still maturing. The creator notes it's been their daily driver and they'd rather get it in front of people than keep polishing in private.
The creator is seeking feedback on missing stacks, confusing install flow, and whether agent delegation is too noisy or not enough.
📖 Read the full source: r/ClaudeAI
👀 See Also
OmniCoder-9B fine-tune shows strong performance for agentic coding on 8GB VRAM systems
A Reddit user tested OmniCoder-9B, a fine-tune of Qwen3.5-9B on Opus traces, with OpenCode and reported 40+ tokens per second speeds using Q4_K_M GGUF quantization at 100k context length on an 8GB VRAM system.
Superglue CLI: Let AI Agents Execute API Calls Without Pre-Built Tools
Superglue CLI provides a skill that teaches AI coding agents how to use its commands, handle authentication, build tools, and debug failures. Instead of creating pre-built tools for every API integration, agents can read API specs at runtime and plan multi-step calls.
Tendr Skill: Deterministic CLI Operations for Agent Memory Management
Tendr Skill is an Agent Skill that separates reasoning from execution for structured long-term memory, allowing agents to decide what needs changing while a CLI tool handles structural operations deterministically. It supports [[wikilinks]] and explicit semantic hierarchies across files.
Gemini 3.1 Pro in Multi-Agent Systems: High Design Quality, 20% Tool-Call Failure Rate
Developers building Bobr, an AI presentation generator with a multi-agent architecture, report Gemini 3.1 Pro produces impressive design output but suffers from a ~20% tool-call failure rate and garbled text corruption in production pipelines.