Към всички skills

memori-mcp-usage

MemoriLabs · Данни и AI

Use when an MCP-connected agent should use Memori tools for targeted recall, summaries, post-compaction briefs, durable memory augmentation, quota checks, signup, feedback, preferences, prior context, or cross-session continuity.

Оригинален текст · няма потвърден превод на български

Теми: agent · agent-memory · agenticai · ai · ai-memory · claude-code · enterprise · hermes · llm · long-short-term-memory · memory · memory-management · openclaw · python · rag

Първо прочетете инструкцията.

Файлът се зарежда от посочения източник само по ваше действие. Можете да го прочетете тук, да го копирате или да го запазите като .md.

Оригинален SKILL.md
GitHub хранилище
Звезди на репото
16 908
Лиценз
NOASSERTION
Последна проверка на записа
20.09.2026 г.

Добавете в своя инструмент.

Командата отваря избора на skills от репозитория. Прочетете файла и условията на автора преди изпълнение.

npx skills add MemoriLabs/Memori

Страницата копира текст. Не инсталира и не изпълнява нищо на устройството ви.

Откъс от SKILL.md

Началото на файла на автора, без превод.

Memori skills file

Overview

Memori is agent-native memory infrastructure: an LLM-agnostic layer that structures memory from natural language and from agent execution trace.

Memori automatically captures and structures memory from conversation and execution trace, including the agent's actions, tool results, decisions, and outcomes. Use it to maintain continuity across sessions, preserve decisions and constraints, and help the agent understand what it actually did so future work is more accurate and efficient.

Core Instruction

When Memori MCP tools are available, treat this skill as the source of truth for how to use Memori through MCP.

Use it to understand:

  • Available Memori capabilities
  • Tooling and integrations
  • Expected behavior and constraints
  • Safety and privacy implications

MCP server configuration supplies authenticated user or tenant context through request headers. Do not invent entity, process, project, or session identifiers.

Current user instructions, verified local context, and tool results outrank recalled memory.

Quick Reference

  • memori_recall: retrieve precise memories by query, project, session, time range, or an allowed source/signal pair.
  • memori_recall_summary: retrieve a state summary for session starts, daily briefs, or broad status checks.
  • memori_compaction: retrieve a structured post-compaction brief to continue work after context compaction.
  • memori_advanced_augmentation: store durable memory from a completed user/assistant turn.
  • memori_feedback: report irrelevant, missing, stale, or especially useful memory behavior.
  • memori_signup: create a Memori account or request an API key when the user explicitly asks.
  • memori_quota: check usage, quota, storage, or memory capacity when the user asks or limits appear to be reached.

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 meaningful 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
  • The message is trivial, administrative, or closing (for example "thanks", "ok", "goodbye")

Avoid unnecessary recall.

Recall Behavior

Целият SKILL.md в GitHub