Memanto Memory

MEMANTO Memory Skill

Detailed reference for using MEMANTO persistent memory effectively.

Memory Types: Decision Matrix

Confidence Levels

• 1.0 — Explicit user statement, verified fact, standing instruction
• 0.9-0.95 — Strong consensus, well-tested approach, clear team preference
• 0.8-0.85 — Observed pattern (3+ times), indirect but supported preference
• 0.7-0.75 — Emerging pattern (2 times), reasonable inference
• 0.6-0.65 — Single observation, uncertain interpretation
• < 0.6 — Don't store. Too uncertain.

Provenance Types

Always categorize the source of the memory. Valid options:

• explicit_statement — Directly stated by user
• inferred — Derived from behavior/context
• observed — Seen in action
• corrected — Updated after contradiction
• validated — Confirmed/verified
• imported — Brought in from an external source (file upload, sync, migration)

Source Types

Always specify the tool or agent creating the memory.

• For AI agents: Use the agent name (e.g., --source claude_code or --source cursor)
• Generic fallbacks when no specific writer applies: user, agent, tool, system
• Any label works, up to 64 letters, digits, ., _, or - (no spaces)

Tagging Best Practices

Use 2-5 tags per memory. Tags make memories findable.

Good: --tags "authentication,oauth,security" Good: --tags "bug-fix,namespace,commit-3f39351" Bad: --tags "important" (too generic) Bad: --tags "thing" (not descriptive)

Conventions:

• Lowercase with hyphens: bug-fix not BugFix
• Be specific: authentication-oauth not auth
• Include refs: commit-abc123 for git references

Patterns

Session Start

# recall — load raw context (instructions, decisions, goals) to guide this session
memanto recall "instructions decisions goals" --limit 20

# answer — get a direct synthesized summary of pending commitments
memanto answer "What are my pending commitments?"

After Important Work

memanto remember "Implemented X using approach Y because Z. Commit abc123." --type decision --tags "feature-x" --confidence 0.95 --provenance "inferred" --source "claude_code"
memanto remember "Learned that batch ops reduce API calls 100x." --type learning --tags "performance" --confidence 0.85 --provenance "observed" --source "claude_code"

When User Corrects You

memanto remember "User corrected: prefer pytest over unittest." --type learning --tags "correction,testing" --confidence 1.0 --provenance "corrected" --source "claude_code"

Choosing Between recall and answer

These are equal-priority tools. Pick the right one — do NOT always default to recall.

Decision rule: If your next step is "read these memories and act" → recall. If your next step is "answer this question directly" → answer. Both save tokens equally — answer synthesizes so you don't have to.

# Use recall — need raw context to work from
memanto recall "authentication approach" --limit 10

# Use answer — need a direct synthesized answer
memanto answer "What auth approach did we decide on and why?"

Pitfalls to Avoid

1. Memory hoarding — Ask "Will this matter in a week?" before storing
2. Vague content — Bad: "better performance" → Good: "API response < 200ms"
3. No context — Bad: "fixed bug" → Good: "Fixed OAuth expiry bug. Commit abc123."
4. Duplicates — Search first (memanto recall), then store if not found
5. Missing tags — Always include tags for retrieval

recall vs answer: Choose the Right Tool

Equal priority — do NOT always default to recall. Pick based on what you need next:

Short rule: need context to work from → recall. Need a ready answer → answer. Both save the agent tokens and time — answer synthesizes so you don't have to read and merge manually.

Command Reference

# Store memory
memanto remember "content" --type TYPE --tags "tag1,tag2" --confidence 0.9 --provenance "inferred" --source "claude_code"

# Raw memory search (use for context-building, multi-step tasks)
memanto recall "query" --limit 10 --type TYPE --min-similarity 0.8

# Temporal recall variants (no query needed)
memanto recall --recent --limit 10                 # newest first
memanto recall --as-of "2026-01-15"                # state at a point in time
memanto recall --changed-since "last 7 days"       # what changed since

# Synthesized answer (use for direct questions, "what did we decide about X?")
memanto answer "question"

# Sync memories to project
memanto memory sync --project-dir .