EverMemory

EverMemory is the deterministic memory plugin for OpenClaw. It gives the agent persistent memory, user understanding, and governed self-improvement without hiding the storage or decision process.

What to do first

• - When the user is new to EverMemory, start with onboarding.
• When the user asks to remember something important, store it with an explicit kind.
• When the user asks for prior context, recall before answering.
• When the user asks for debugging, auditing, cleanup, backup, or recovery, use the governance and IO tools instead of guessing.

Core model

Layer 1: Memory

• - Store durable facts, decisions, preferences, constraints, lessons, and project context.
• Recall by keyword, structured filters, or hybrid retrieval.
• Archive stale or superseded memories and restore them with review/apply gates.

Layer 2: Understanding

• - Build a user profile from explicit statements and stable interaction patterns.
• Track behavior rules and preference hints that can shape future responses.
• Generate session briefings so a new session starts with continuity.

Layer 3: Proactivity

• - Extract intent and reflections from interaction history.
• Consolidate duplicate or stale memories.
• Explain why a write, recall, archive, or rule action happened.

Tool map

EverMemory has 16 core capabilities. In the current OpenClaw plugin, 15 are exposed as tool commands, and onboarding is registered as profile_onboard. Smartness exists in the SDK/status layer but is not currently registered as a standalone OpenClaw tool.

Capability	OpenClaw tool name	When to use
Store memory	INLINECODE1	User asks to remember a fact, decision, preference, or lesson
Recall memory

evermemory_recall | User asks what happened before, what they prefer, or what was decided |
| Consolidate memory | evermemory_consolidate | Cleanup, dedupe, archive stale memory |
| Status | evermemory_status | Inspect counts, DB path, activity, continuity KPIs |
| Smartness report | Not host-registered | Mention as internal/SDK capability, do not invent a tool call |
| Session briefing | evermemory_briefing | Generate startup continuity context |
| Rules | evermemory_rules | Read or manage promoted behavior rules |
| Profile | evermemory_profile | Read or recompute user profile |
| Explainability | evermemory_explain | Audit why EverMemory wrote, recalled, restored, or promoted something |
| Export | evermemory_export | Backup memory to snapshot or text export |
| Import | evermemory_import | Review or apply imported snapshot/text |
| Archive review | evermemory_review | Inspect archived or superseded items before restore |
| Restore | evermemory_restore | Recover archived memory with review/apply |
| Intent analysis | evermemory_intent | Analyze the likely user intent for a message |
| Reflection | evermemory_reflect | Generate lessons, warnings, or candidate rules |
| Onboarding | profile_onboard | First-run questionnaire and initial profile setup |

Tool usage guidance

evermemory_store

Use for explicit long-term facts. Prefer concise, high-value content and a correct kind.

Example:

CODEBLOCK0

Store when the user says:

• - "记住这个决定"
• "以后按这个偏好来"
• "这个坑以后别再踩"

evermemory_recall

Use before answering when the user asks about prior context, preferences, constraints, or project continuity.

Example:

CODEBLOCK1

evermemory_status

Use for health checks and operator-style visibility. It returns memory counts, archive counts, profile/rule/reflection state, recent debug activity, and continuity KPIs.

evermemory_briefing

Use at session start or when the user asks for a summary of who they are, current constraints, and active project context.

profile_onboard

Use for first-run setup. Ask the questions, collect answers, then submit them. Do not skip onboarding if no profile exists and the user wants personalized memory behavior.

evermemory_profile

Use to inspect current user understanding. Prefer recompute: true when the user asks for a refreshed profile after many new interactions.

evermemory_rules

Use for behavior rules and guardrails. Prefer read/review paths before mutating rules.

evermemory_explain

Use when the user asks "why did you remember this", "why was this recalled", "why was this archived", or "why did this rule trigger".

evermemory_export and evermemory_import

• - Export for backup or migration.
• Import with mode: "review" first.
• Only use apply after the user clearly confirms.

evermemory_review and evermemory_restore

• - Review archived memory before restoring.
• Prefer mode: "review" first.
• Restore only the specific IDs the user approves.

evermemory_intent, evermemory_reflect, evermemory_consolidate

Use these as maintenance and self-improvement tools:

• - evermemory_intent for intent labeling and routing insight.
• INLINECODE36 for lessons, warnings, and candidate rules.
• INLINECODE37 for dedupe and stale-memory cleanup.

Recommended workflows

First use

CODEBLOCK2

Remember a decision

CODEBLOCK3

Recall previous context

CODEBLOCK4

Export backup

CODEBLOCK5

Recovery

CODEBLOCK6

Guardrails

• - Do not claim a standalone evermemory_smartness tool exists unless the host actually registers it.
• In the current repository, onboarding is profile_onboard, not evermemory_onboard.
• Prefer review before apply for import and restore.
• Recall before answering if the user explicitly asks about previous decisions, preferences, or history.
• Store only durable, high-signal information. Avoid writing transient chatter as memory.
• When a tool returns governed results, explain them plainly instead of exposing raw internals unless the user asks.

Configuration notes

Common environment variables for semantic retrieval:

• - EVERMEMORY_EMBEDDING_PROVIDER: local, openai, or INLINECODE46
• INLINECODE47: local embedding model, default INLINECODE48
• INLINECODE49: required when the embedding provider uses OpenAI

Common plugin config fields:

• - INLINECODE50
• INLINECODE51
• INLINECODE52
• INLINECODE53
• INLINECODE54
• INLINECODE55
• INLINECODE56
• INLINECODE57
• INLINECODE58