Why Use This
This skill provides specialized capabilities for Qredence's codebase.
Use Cases
- Developing new features in the Qredence repository
- Refactoring existing code to follow Qredence standards
- Understanding and working with Qredence's codebase structure
Install Guide
2 steps - 1
- 2
Install inside Ananke
Click Install Skill, paste the link below, then press Install.
https://github.com/Qredence/agentic-fleet/tree/main/.fleet/context
Skill Snapshot
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Valid SKILL.md
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Source & Community
Updated At Jan 19, 2026, 03:09 AM
Skill Stats
SKILL.md 171 Lines
Total Files 1
Total Size 0 B
License NOASSERTION
---
name: memory-system
description: Complete guide to the AgenticFleet memory system. Read this first.
---
# AgenticFleet Memory System
A two-tier memory architecture enabling agents to learn, remember, and improve over time.
## Quick Start
1. **Initialize** (first time only):
```bash
uv run python .fleet/context/scripts/memory_manager.py init
```
2. **Setup Chroma Cloud** (after editing config with your API key):
```bash
uv run python .fleet/context/scripts/memory_manager.py setup-chroma
```
3. **Verify Status**:
```bash
uv run python .fleet/context/scripts/memory_manager.py status
```
4. **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 guidelines
5. **Search Memory** when you need information:
```bash
uv run python .fleet/context/scripts/memory_manager.py recall "your query"
```
6. **Create Skills** after solving problems:
```bash
uv run python .fleet/context/scripts/memory_manager.py learn --file .fleet/context/skills/new-skill.md
```
## Memory Hierarchy
### Core Memory (Always In-Context)
Location: `.fleet/context/core/`
| Block | Purpose |
| ------------ | ------------------------------------- |
| `project.md` | Architecture, tech stack, conventions |
| `human.md` | User preferences, communication style |
| `persona.md` | Agent role, tone, guidelines |
### Topic Blocks (Reference On-Demand)
Location: `.fleet/context/blocks/`
| Category | Blocks |
| ------------ | -------------------------------------------- |
| `project/` | commands, architecture, conventions, gotchas |
| `workflows/` | git, review |
| `decisions/` | ADR-style decision records |
### Skills (Procedural Memory)
Location: `.fleet/context/skills/`
Learned patterns and solutions. Indexed to Chroma for semantic search.
### Chroma Cloud (Semantic Search)
Collections: `semantic`, `procedural`, `episodic`
Enables fuzzy search across all indexed content.
## Commands
### Claude Code Commands
```
/init # Initialize memory system
/learn # Learn a new skill
/recall # Search memory semantically
/reflect # Reflect on session, consolidate learnings
```
### CLI Commands
```bash
# 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
```
## Block Format
All memory blocks use Letta-style frontmatter:
```yaml
---
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...
```
## Workflow
### Starting a Session
1. Read core blocks (project, human, persona)
2. Check relevant topic blocks if needed
3. Use `/recall` to search for relevant skills
### During Work
1. Reference blocks as needed
2. Update `human.md` if you learn user preferences
3. Note patterns worth remembering
### Ending a Session
1. Use `/reflect` to consolidate learnings
2. Create skills for reusable solutions
3. Index new skills with `/learn`
## File Structure
```
.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
```
## Related Documentation
- `MEMORY.md` - Detailed setup and architecture
- `skills/README.md` - How to create skills
- `skills/SKILL_TEMPLATE.md` - Skill template
- `blocks/decisions/001-memory-system.md` - Architecture decision record