Remark: A Markdown Annotation Tool for Claude Code Workflows
What Remark Does
Remark addresses a specific friction point when using Claude Code: reviewing spec or instruction files and leaving feedback for the agent. The developer behind it found that pasting notes into chat disconnects feedback from the file, while leaving notes directly in markdown is messy because the agent either reads them as content or strips them.
Key Features and Commands
The tool is a native macOS application with these specific capabilities:
- Annotate any Markdown file inline by highlighting sections and adding comments
- Export annotations with
remark export file.md- this generates a JSON list containing exactly what was flagged, where in the file, and the surrounding context - Clear resolved annotations with
remark resolve - Local-only operation - nothing leaves your machine
Claude Code Integration
The Claude Code integration works through a skill system:
- Run
remark install-skillto install a skill in your.claude/skills/directory - The skill covers the annotation format, including how to read exports, how to mark annotations resolved, and how to handle partial matches when the file has changed since review
Technical Details
The tool was built with Claude Code, which wrote most of the Rust backend and the re-anchoring algorithm. It's available for macOS with a 7-day free trial, then a $17 one-time purchase. Installation options include:
- Direct download from getremark.app
- Homebrew:
brew install mfreiwald/tap/remark
This type of tool is useful for developers who regularly review and provide feedback on Claude Code instruction files, offering a structured way to maintain feedback context within the actual files being reviewed.
📖 Read the full source: r/ClaudeAI
👀 See Also
OpenClaw Agent Maintains Memory When Switching from Claude Subscription to API
A developer reports successfully migrating their OpenClaw setup from a Claude subscription to API key without losing agent memory, using the mengram-memory skill that saves to an external layer. The agent retained ~100+ learned facts, evolved procedures, and episodic memories.
LORE.md: An Open Standard for Extracting Structured Knowledge from AI Conversations
LORE.md is an open standard for extracting durable knowledge from AI conversations into a structured format. It captures decisions with rationale, insights, patterns, open questions, and next steps, with everything linking across sessions.
SubQ: A Sub-Quadratic LLM with 12M-Token Context Window
SubQ is a fully sub-quadratic sparse-attention LLM offering a 12M-token context window at 150 tokens/s, with SWE-Bench Verified 81.8% and RULER @ 128K 95.0%. It reduces attention compute ~1000× compared to transformers.
Marmy: A Self-Hosted Mobile App for Managing Multiple AI Coding Agent Sessions
Marmy is an open-source, self-hosted tool built with Claude Code that lets you manage multiple AI coding agent sessions from your phone. It features a Rust agent for your machines, an iOS app, file browsing with syntax highlighting, push notifications, and a manager-agent architecture.