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Complete guide to the AgenticFleet memory system. Read this first.
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
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Comprehensive guide for initializing or reorganizing agent memory and project context. Use when setting up a new project, when the user asks you to learn about the codebase, or when you need to create effective memory blocks for project conventions, preferences, and workflows.
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Context-aware development assistant for AgenticFleet with auto-learning and dual memory (NeonDB + ChromaDB). Handles development workflows with intelligent context management.
| name | memory-system |
| description | Complete guide to the AgenticFleet memory system. Read this first. |
A two-tier memory architecture enabling agents to learn, remember, and improve over time.
Initialize (first time only):
uv run python .fleet/context/scripts/memory_manager.py init
Setup Chroma Cloud (after editing config with your API key):
uv run python .fleet/context/scripts/memory_manager.py setup-chroma
Verify Status:
uv run python .fleet/context/scripts/memory_manager.py status
Read Core Context (always do this first):
.fleet/context/core/project.md - Project architecture.fleet/context/core/human.md - User preferences.fleet/context/core/persona.md - Agent guidelinesSearch Memory when you need information:
uv run python .fleet/context/scripts/memory_manager.py recall "your query"
Create Skills after solving problems:
uv run python .fleet/context/scripts/memory_manager.py learn --file .fleet/context/skills/new-skill.md
Location: .fleet/context/core/
| Block | Purpose |
|---|---|
project.md | Architecture, tech stack, conventions |
human.md | User preferences, communication style |
persona.md | Agent role, tone, guidelines |
Location: .fleet/context/blocks/
| Category | Blocks |
|---|---|
project/ | commands, architecture, conventions, gotchas |
workflows/ | git, review |
decisions/ | ADR-style decision records |
Location: .fleet/context/skills/
Learned patterns and solutions. Indexed to Chroma for semantic search.
Collections: semantic, procedural, episodic
Enables fuzzy search across all indexed content.
/init # Initialize memory system
/learn # Learn a new skill
/recall # Search memory semantically
/reflect # Reflect on session, consolidate learnings
# Initialize system (creates local files)
uv run python .fleet/context/scripts/memory_manager.py init
# Setup Chroma Cloud collections
uv run python .fleet/context/scripts/memory_manager.py setup-chroma
# Check connection and collection status
uv run python .fleet/context/scripts/memory_manager.py status
# Semantic search across all collections
uv run python .fleet/context/scripts/memory_manager.py recall "query"
# Index skill to Chroma procedural collection
uv run python .fleet/context/scripts/memory_manager.py learn --file <path>
# Archive session to episodic collection
uv run python .fleet/context/scripts/memory_manager.py reflect
All memory blocks use Letta-style frontmatter:
---
label: block-name
description: What this block contains and when to use it.
limit: 5000 # Character limit
scope: core|project|workflows|decisions
updated: 2024-12-29
---
# Content here...
/recall to search for relevant skillshuman.md if you learn user preferences/reflect to consolidate learnings/learn.fleet/context/
├── SKILL.md # This file (entry point)
├── MEMORY.md # Detailed documentation
├── core/ # Core memory blocks
├── blocks/ # Topic-scoped blocks
│ ├── project/
│ ├── workflows/
│ └── decisions/
├── skills/ # Learned skills
├── system/ # Agent skill definitions
├── scripts/ # Python memory engine
└── .chroma/ # Chroma Cloud config
MEMORY.md - Detailed setup and architectureskills/README.md - How to create skillsskills/SKILL_TEMPLATE.md - Skill templateblocks/decisions/001-memory-system.md - Architecture decision record