agents-remember-md
Agents working across multiple coding sessions lose context about design decisions, past failures, and project constraints.
Persistent memory for AI coding agents. Captures what code can't say on its own! No vector search, context bloat, or stale docs.
- Remembering which refactoring approaches failed in previous sprints
- Tracking API integration quirks discovered during development
- Preserving architectural decisions across multi-session feature builds
Agents working across multiple coding sessions lose context about design decisions, past failures, and project constraints. This tool lets them retain stateful memory of what happened, reducing redundant work and preventing repeated mistakes.
Teams running autonomous or semi-autonomous coding agents that span multiple tasks or sessions and need continuity without managing vector databases.
https://github.com/Foxfire1st/agents-remember-md
By Foxfire1st
How to Get It
claude plugins install Foxfire1st/agents-remember-md
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me remembering which refactoring approaches failed in previous sprints
Trust Signals Auto-scanned
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 27 GitHub stars; 5 contributors; last commit 1d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 27 GitHub stars; 5 contributors; last commit 1d ago; license MIT.