nhadaututtheky/.claude-plugin
.claude-plugin/SKILL.md
# Neural Memory Persistent memory for AI agents — stores experiences as interconnected neurons, recalls through spreading activation. ## Session Lifecycle 1. **Start**: `nmem_recap()` → `nmem_recall("<project> <topic>")` 2. **During**: `nmem_remember(...)` after each completed task 3. **End**: `nmem_auto(action="process", text="brief summary")` 4. **Emergency**: `nmem_auto(action="flush", text="...")` before /compact ## Save — When & How ``` nmem_remember(content="Chose X over Y because Z",
$ install --global
skillsauthnpx skillsauth add nhadaututtheky/neural-memory .claude-pluginInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Last scanned: Apr 9, 2026, 2:02 AM24.9s8 files scanned
SKILL.md
Neural Memory
Persistent memory for AI agents — stores experiences as interconnected neurons, recalls through spreading activation.
Session Lifecycle
- Start:
nmem_recap()→nmem_recall("<project> <topic>") - During:
nmem_remember(...)after each completed task - End:
nmem_auto(action="process", text="brief summary") - Emergency:
nmem_auto(action="flush", text="...")before /compact
Save — When & How
nmem_remember(content="Chose X over Y because Z", type="decision", priority=7, tags=["project", "topic"])
| Signal | type | priority | |--------|------|----------| | Chose between alternatives | decision | 7 | | Fixed a bug (root cause + fix) | error | 7 | | Discovered a pattern | insight | 6 | | Learned user preference | preference | 8 | | Established a process | workflow | 6 | | Reusable fact | fact | 5 | | User instruction | instruction | 8 |
Quality (system scores 0-10 automatically):
- Causal language: "X because Y", "chose X over Y", "root cause was X"
- Include specifics: file paths, versions, error traces
- 50-300 chars optimal. >500 chars penalized — split instead.
- Scratch notes:
ephemeral=true(24h, never synced) - Do NOT save: routine file reads, things in git, duplicates
Recall
nmem_recall(query="project auth bug") # depth auto-detected
- Causal queries ("why", "because", "caused") activate cause-effect chains
- Fixes auto-supersede errors (old errors demoted when fix is stored)
- Prefix queries with project name for accuracy
Smart Behaviors (automatic)
- Quality scoring: specificity, structure, brevity scored per memory
- Dedup: similar memories flagged — use nmem_edit instead of duplicating
- Causal synapses: fixes create RESOLVED_BY links, demote old errors
- Stale detection: old-version references get -20% retrieval penalty
- Cold demotion: 0 access in 30d → cold; 90d → prune candidate (pinned exempt)
- SimHash merge: content-similar memories consolidated; 5+ group → summary fiber
Key Tools
| Tool | When |
|------|------|
| nmem_recall | Query memories (depth auto-detected) |
| nmem_context | Load recent memories at session start |
| nmem_recap | Resume session (level=1-3, topic="X") |
| nmem_session | Track session state (get/set/end) |
| nmem_edit | Fix wrong type/content/priority |
| nmem_forget | Remove outdated memories (soft/hard) |
| nmem_index | Scan codebase into memory graph |
| nmem_train | Train docs into permanent knowledge |
| nmem_health | Brain grade + top penalties to fix |
| nmem_explain | Trace path between two concepts |
| nmem_cognitive | Hypotheses + predictions dashboard |
All tools: compact=true saves 60-80% tokens.
Links
- GitHub
- Documentation
- VS Code Extension
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