recall

/nemp:recall

Retrieve a memory by exact key or fuzzy search.

Usage

/nemp:recall

Arguments

• key-or-query: Either an exact memory key OR a natural language query to search memories

Instructions

When the user invokes /nemp:recall, follow these steps:

1. Load All Memories

Read from both storage locations and merge:

# Read project memories if exists
[ -f ".nemp/memories.json" ] && cat .nemp/memories.json

# Read global memories if exists
[ -f "$HOME/.nemp/memories.json" ] && cat $HOME/.nemp/memories.json

2. Search Strategy

Phase 1: Exact Key Match

• Look for a memory where key exactly matches the query
• If found, return immediately

Phase 2: Partial Key Match

• Look for memories where the key CONTAINS the query (case-insensitive)
• Example: query "bun" matches key "user-prefers-bun"

Phase 3: Value Search

• Search the value field for the query terms (case-insensitive)
• Rank by number of matching words

Phase 4: Fuzzy/Semantic Match (Basic)

• If no matches found, look for semantically related terms
• Example: "package manager" might match "npm", "bun", "yarn" mentions
• This is basic keyword expansion for now; semantic embeddings come later

3. Log the Read Operation

IMPORTANT: Always log read operations for audit trail.

After finding a match, append to .nemp/access.log:

echo "[$(date -u +%Y-%m-%dT%H:%M:%SZ)] READ key=<key> agent=${CLAUDE_AGENT_NAME:-main} query=<original-query>" >> .nemp/access.log

3b. Update Vitality Tracking

After logging to access.log, update the matched memory's vitality counters in memories.json:

1. Load the memory from the appropriate storage file (project or global)
2. If the memory lacks vitality fields, initialize with defaults first:
   • type: "fact"
   • confidence: {"score": 0.65, "source": "agent-inferred", "reason": "Pre-cortex memory"}
   • vitality: all counters set to 0, score: 50, state: "active", trend: "stable", last_read: null, decay_rate: 0.01
   • links: {"goals": [], "conflicts": [], "supersedes": null, "superseded_by": null, "causal": []}
3. Update these fields:

   vitality.reads += 1
   vitality.reads_7d += 1
   vitality.reads_30d += 1
   vitality.last_read = <current ISO-8601 timestamp>
   

4. Recalculate vitality.score using the formula:

   vitality = (
     (reads_7d × 15) +
     (reads_30d × 3) +
     (foresight_load_ratio × 20) +
     (agent_reference_ratio × 25) +
     (update_frequency × 10) +
     (goal_link_active × 15) -
     (correction_events × 10) -
     (days_since_last_read × decay_rate)
   )
   clamped to 0-100
   

   Where:
   • foresight_load_ratio = foresight_loads / (foresight_loads + foresight_skips), default 0 if both are 0
   • agent_reference_ratio = agent_references / reads, default 0 if reads is 0
   • update_frequency = update_count / max(1, days_since_created)
   • goal_link_active = 1 if links.goals has any active goal, else 0
5. Set vitality.state based on score:
   • 80-100: "thriving"
   • 50-79: "active"
   • 20-49: "fading"
   • 1-19: "dormant"
   • 0: "extinct"
6. Write the updated memory back to memories.json