Memori

Memori skills file

You have access to Memori, a structured long-term memory system.

Memori automatically captures what happens (via advanced augmentation) and allows you to retrieve it on demand (via agent-controlled recall). Use it to maintain continuity across sessions, preserve decisions and constraints, and avoid repeating work.

When to use Memori

Use Memori when:

  • The task depends on prior context
  • The user refers to previous sessions or decisions
  • You need known constraints, preferences, or patterns
  • You are starting a session and need current state
  • You want to understand what has already been done

When not to use Memori

Do not use Memori when:

  • The task is fully self-contained
  • The answer depends only on the current prompt
  • No historical context is required
  • The query is simple or one-off

Avoid unnecessary recall.

Recall behavior

Recall is agent-controlled and intentional.

Prefer targeted recall over broad queries.

Supported parameters (recall only)

  • entity_id → user, agent, or system context
  • project_id → project or workspace context
  • session_id → specific session
  • date_start / date_end → time-bounded recall
  • source → type of memory
  • signal → how the memory was derived

Note: If a session_id is provided, a project_id must also be provided. All timestamps are stored in UTC.

Memory filters

  • source:

    • constraint
    • decision
    • execution
    • fact
    • insight
    • instruction
    • status
    • strategy
    • task

  • signal:

    • commit
    • discovery
    • failure
    • inference
    • pattern
    • result
    • update
    • verification

Use source and signal to prioritize high-signal memory when possible.

Default behavior (recall)

  • No date range → all-time memory
  • Use time bounds when narrowing results is necessary

Best practices

  • Start narrow (entity + project)
  • Add time bounds only when needed
  • Use source and signal to refine results
  • Expand scope only if needed
  • Do not recall on every turn

Summary behavior

Summaries are used for state awareness, not precise retrieval.

Use:

  • memori_recall_summary

Supported parameters (summaries)

  • project_id
  • session_id
  • date_start
  • date_end

Summaries do not support source or signal.

Default behavior (summaries)

  • No date range → last 24 hours

Daily brief behavior

At the start of a meaningful session, retrieve a structured summary.

Use the daily brief to understand:

  • Current state
  • Prior decisions
  • Constraints
  • Open work

Expected daily brief structure

  • Today at a glance
  • Top 3 next actions
  • Top 3 risks
  • Verify before acting
  • Recent decisions
  • Mission stack
  • Hard constraints
  • Current status
  • Open loops
  • Known failures and anti-patterns
  • Staleness warnings

Treat this as the working state of the system.

Typical workflow

  1. Start of session → retrieve summary
  2. During task → use targeted recall
  3. When memory is missing or incorrect → send feedback
  4. When limits are reached → degrade gracefully

Safety and correctness

  • Do not invent memory
  • Do not assume memory is correct if it conflicts with the user
  • Verify before acting when needed
  • Treat recent instructions as higher priority than recalled memory

Memori system guidance

This section defines how you should interact with Memori beyond basic recall.

1. Feedback (memori_feedback)

You are equipped with the memori_feedback tool to improve memory quality over time.

You may send feedback at any time, and should do so at the end of a session when appropriate.

Feedback should be sent when:

  • Recall results are irrelevant or missing key context
  • Important decisions or constraints were not captured
  • Memory quality degrades across sessions
  • Something works particularly well and should be reinforced

Examples:

  • "Send feedback that recall missed a pricing constraint."
  • "Tell Memori the daily brief was accurate."
  • "Submit a bug report: you didn’t remember my preferred language."

Purpose

Feedback improves:

  • Memory extraction quality
  • Recall relevance
  • Summary accuracy

2. Updates

Memori evolves over time (new features, improved recall, better summaries).

When updates are exposed:

  • Check for updates via system message or tool
  • Adapt behavior to use new capabilities

When an update is detected:

  • Prefer newer recall patterns when available
  • Use improved summaries or classification outputs
  • Continue operating normally if no changes are required

3. Quota awareness and upgrades

Memori enforces usage limits (e.g., storage, recall volume, API usage).

When limits are reached or nearing:

a. Degrade gracefully

  • Reduce recall scope (shorter time ranges)
  • Prioritize high-signal memory (decisions, constraints, key facts)
  • Avoid unnecessary or repeated recall calls

b. Inform the human/operator

Clearly communicate when limits impact performance.

Example:

“Memory limits have been reached. I can continue with limited recall, or you can upgrade to restore full functionality.”

c. Suggest upgrades appropriately

  • Only prompt when performance is affected
  • Avoid repetitive or disruptive messaging
  • Keep messaging neutral and helpful