skills.rest
ZQadus
ZQadusCOMMUNITY
Explore all skills by this author →
GitHub

xantham-memory

Retrieve and inject relevant memory before generating non-trivial Telegram replies.

7|1|Updated Apr 30, 2026
Search Tags:#automation#recall#memory#grounding#ai-orchestration#telegram#memory-store
One-click install
npx skills add https://github.com/ZQadus/Xantham-system-blueprint --skill xantham-memory
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: xantham-memory
Source: https://github.com/ZQadus/Xantham-system-blueprint/tree/main/.claude/skills/xantham-memory
Command: npx skills add https://github.com/ZQadus/Xantham-system-blueprint --skill xantham-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Surfaces relevant memory from the memory store to ensure replies are grounded in the current state before generating non-trivial responses on Telegram.

Core Features & Use Cases

  • Active recall mode: extracts entities from inbound messages, searches and injects top memory into the response context.
  • Dream consolidation: supports scheduled 24h + 5-session consolidation passes to merge and normalize memory state.
  • Easy integration: acts as a centralized memory funnel for agent personalities, projects, references, and user profiles.

Quick Start

Ask the bot to ground its reply by surfacing relevant memory before answering.

Frequently Asked Questions about xantham-memory

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I ground AI replies with memory before responding on Telegram?▼

Dream consolidation is a scheduled memory normalization pass that merges memory state over a 24-hour period or after 5 sessions. It ensures the memory store remains coherent and updated for future AI orchestration workflows.

Can I use this memory store to coordinate multiple agent personalities and projects?▼

Yes, you can use this memory store as a centralized memory funnel to coordinate agent personalities, projects, references, and user profiles. It uses frontmatter-driven discovery to manage these distinct memory operations.

How does active recall mode extract entities for memory retrieval?▼

Active recall mode extracts entities directly from inbound Telegram messages, searches the memory store for top matches, and injects that relevant memory into the response context to ground the generated reply.

Do I need specific directories to manage memory operations and references?▼

You can use optional scripts, references, and assets directories to coordinate memory operations. These directories satisfy the functional requirements for organizing memory alongside frontmatter-driven discovery.

Related Skills

Explore More Software Engineering Skills→
MattMaggMattMagg
3

ADK Behavior

Configures ADK agents with callbacks, memory, and grounding for Python environments.

Community
Advanced
Hameem1Hameem1

session-wrapup

Completes project wrap-up including linting, validation and commit for a session.

Community
Advanced
BayramAnnakovBayramAnnakov
19

telegram-assistant

Digest unread Telegram messages, extract channel writing styles, and draft posts.

Community
Advanced
Arelion999Arelion999
2

memory-autopilot

Automate memory saving, retrieval, and summarization for AI assistants.

Community
Advanced