pkg-memory-bridge
Bridge to PKG systems (Mem0, Graphiti, Solid PODs, Logseq) for individuated information indices
Best use case
pkg-memory-bridge is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Bridge to PKG systems (Mem0, Graphiti, Solid PODs, Logseq) for individuated information indices
Teams using pkg-memory-bridge should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/pkg-memory-bridge/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How pkg-memory-bridge Compares
| Feature / Agent | pkg-memory-bridge | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Bridge to PKG systems (Mem0, Graphiti, Solid PODs, Logseq) for individuated information indices
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# PKG Memory Bridge Skill
Connects music-topos to external Personal Knowledge Graph systems.
## GF(3) Triads
```
shadow-goblin (-1) ⊗ pkg-memory-bridge (0) ⊗ gay-mcp (+1) = 0 ✓ [Memory Trace]
temporal-coalgebra (-1) ⊗ pkg-memory-bridge (0) ⊗ agent-o-rama (+1) = 0 ✓ [Temporal KG]
keychain-secure (-1) ⊗ pkg-memory-bridge (0) ⊗ pulse-mcp-stream (+1) = 0 ✓ [Auth + Stream]
```
## Supported Systems
| System | API | Use Case |
|--------|-----|----------|
| Mem0 | `pip install mem0ai` | LLM agent memory |
| Graphiti | MCP Server | Temporal knowledge graph |
| Solid POD | REST/SPARQL | Decentralized personal data |
| Logseq | Local DB | Block-level PKB |
## Quick Integration
```python
from mem0 import Memory
m = Memory()
m.add("User prefers GF(3) balanced triads", user_id="bmorphism")
results = m.search("color conservation", user_id="bmorphism")
```
## Graphiti MCP
```bash
# Add to .mcp.json
{"mcpServers": {"graphiti": {"command": "uvx", "args": ["graphiti-mcp"]}}}
```
## Key Researchers
- Krisztian Balog (PKG ecosystem)
- Gordon Bell (MyLifeBits/memex)
- Mem0 team (Prateek Chhikara, Taranjeet Singh)
- Zep/Graphiti (temporal KG)
## Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
### Graph Theory
- **networkx** [○] via bicomodule
- Universal graph hub
### Bibliography References
- `general`: 734 citations in bib.duckdb
## Cat# Integration
This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:
```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```
### GF(3) Naturality
The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```
This ensures compositional coherence in the Cat# equipment structure.Related Skills
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