add-mnemon
FeaturedAdd persistent graph-based memory via mnemon. Agents recall past context before responding and remember insights after each turn.
Install
Quality Score: 93/100
Skill Content
Details
- Author
- nanocoai
- Repository
- nanocoai/nanoclaw
- Created
- 5 months ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
mnemos-setup
Setup mnemos persistent memory with mnemo-server. Triggers: "set up mnemos", "install mnemo plugin", "configure memory plugin", "configure openclaw memory", "configure opencode memory", "configure claude code memory".
mnemo-memory
Use mnemo as the only persistent memory for an initialized project. Use when starting or resuming work, recovering context after compaction, recalling prior decisions, saving important decisions or fixes, recording conventions or user preferences, and closing a task or session. Always verify a valid .mnemo marker first; never fall back to native, file-based, or plaintext memory.
agent-recall
Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface (18 tools) available with --full flag. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.