bambu-studio-ai
Bambu Lab 3D printer control and automation. Activate when user mentions: printer status, 3D printing, slice, analyze model, generate 3D, AMS filament, print monitor, Bambu Lab, or any 3D printing task. Full pi...
Reliable agent-to-agent communication protocol for transferring large payloads via shared files with pointer references and secret code verification. Triggered by explicit 'AgentRelay:' prefix in messages.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install extraterrest/agentrelayInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Reliable Agent-to-Agent Communication Protocol — Solves sessions_send timeout issues for large payloads using shared files + short message pointers.
When you see messages like the following, immediately use this Skill to handle:
Please use AgentRelay skill to handle this message:
REQ,r1_r,s/r1_r.json,,
Or
📨 AgentRelay Protocol Message
Please use AgentRelay skill to handle:
- Message Type: REQ
- Event ID: r1_r
- File Pointer: s/r1_r.json
Key Trigger Phrases:
When you see these keywords, immediately execute the Commands below!
Step 1: Parse Message
python3 {baseDir}/run_relay.py receive "REQ,r1_r,s/r1_r.json,,"
Example output:
{
"type": "REQ",
"event_id": "r1_r",
"content": {"task": "write_poem", "sender_color": "red"},
"secret": "ABC123"
}
Step 2: Understand Task and Execute
Check the content field to understand what needs to be done (e.g., write poem, analyze data, generate report).
Step 3: Update Result
python3 {baseDir}/run_relay.py complete r1_r "Task completed" "agent:red:red"
Step 4: Send CMP Confirmation
# generate CMP message (done automatically by run_relay.py complete)
# Output: CMP,r1_r,,,ABC123
# Then send via sessions_send
sessions_send(target='agent:red:red', message='CMP,r1_r,,,ABC123')
receive <csv_message>Parse AgentRelay CSV message and read shared file content.
Parameters:
csv_message: CSV format message (without AgentRelay: prefix)Example:
python3 {baseDir}/run_relay.py receive "REQ,r1_r,s/r1_r.json,,"
Output (JSON):
{
"type": "REQ",
"event_id": "r1_r",
"ptr": "s/r1_r.json",
"content": {...},
"secret": "ABC123"
}
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
Reliable Agent-to-Agent Communication Protocol — Solves sessions_send timeout issues for large payloads using shared files + short message pointers.
When your agents need to send messages larger than 30 characters, sessions_send tends to timeout. AgentRelay provides the solution:
| Traditional Approach | AgentRelay Approach |
|---|---|
| ❌ Send large text directly → ⏰ Timeout | ✅ Write to file + send short pointer → Success |
| ❌ No verification if received | ✅ Secret Code mechanism ensures delivery |
| ❌ No audit trail | ✅ Complete transaction logs (4 entries/event) |
clawhub install agentrelay
from agentrelay import AgentRelayTool
# Prepare data
content = {"task": "write_poem", "theme": "spring"}
# Write to shared file and get CSV message
result = AgentRelayTool.send("yellow", "REQ", "hop1", content)
# Send to target agent
sessions_send(
target='agent:yellow:yellow',
message=f"AgentRelay: {result['csv_message']}"
)
# Use unified script to parse
python3 scripts/run_relay.py receive "REQ,hop1,s/hop1.json,,"
Output:
{
"type": "REQ",
"event_id": "hop1",
"content": {"task": "write_poem", ...},
"secret": "ABC123"
}
python3 scripts/run_relay.py complete hop1 "Task completed" "agent:red:red"
Output:
✅ Updated hop1
✅ CMP: CMP,hop1,,,ABC123
Sender Receiver
| |
|-- 1. REQ (with file ptr) --->|
| |-- receive()
| |-- 📍 LOG #1: REQ/RECEIVED
| |-- 📍 LOG #2: ACK/ACKNOWLEDGED
| |
|<-- 2. ACK (implicit confirm)-|
| |
|...
# AgentRelay 📨
**Reliable Agent-to-Agent Communication Protocol** — Solves `sessions_send` timeout issues for large payloads using shared files + short message pointers.
## 🎯 When to Use This Skill
**When you see messages like the following**, immediately use this Skill to handle:
```
Please use AgentRelay skill to handle this message:
REQ,r1_r,s/r1_r.json,,
```
Or
```
📨 AgentRelay Protocol Message
Please use AgentRelay skill to handle:
- Message Type: REQ
- Event ID: r1_r
- File Pointer: s/r1_r.json
```
**Key Trigger Phrases**:
- "use AgentRelay skill to handle"
- "AgentRelay protocol message"
- "Use AgentRelay"
When you see these keywords, **immediately execute the Commands below**!
## 🚀 Quick Start
### Standard Flow After Receiving AgentRelay Message
**Step 1: Parse Message**
```bash
python3 {baseDir}/run_relay.py receive "REQ,r1_r,s/r1_r.json,,"
```
Example output:
```json
{
"type": "REQ",
"event_id": "r1_r",
"content": {"task": "write_poem", "sender_color": "red"},
"secret": "ABC123"
}
```
**Step 2: Understand Task and Execute**
Check the `content` field to understand what needs to be done (e.g., write poem, analyze data, generate report).
**Step 3: Update Result**
```bash
python3 {baseDir}/run_relay.py complete r1_r "Task completed" "agent:red:red"
```
**Step 4: Send CMP Confirmation**
```bash
# generate CMP message (done automatically by run_relay.py complete)
# Output: CMP,r1_r,,,ABC123
# Then send via sessions_send
sessions_send(target='agent:red:red', message='CMP,r1_r,,,ABC123')
```
---
## 📚 Commands
### `receive <csv_message>`
Parse AgentRelay CSV message and read shared file content.
**Parameters**:
- `csv_message`: CSV format message (without `AgentRelay:` prefix)
**Example**:
```bash
python3 {baseDir}/run_relay.py receive "REQ,r1_r,s/r1_r.json,,"
```
**Output** (JSON):
```json
{
"type": "REQ",
"event_id": "r1_r",
"ptr": "s/r1_r.json",
"content": {...},
"secret": "ABC123"
}
```
---
### `update <event_i...# AgentRelay 📨
**Reliable Agent-to-Agent Communication Protocol** — Solves `sessions_send` timeout issues for large payloads using shared files + short message pointers.
---
## 🎯 Core Value
When your agents need to send messages **larger than 30 characters**, `sessions_send` tends to timeout. AgentRelay provides the solution:
| Traditional Approach | AgentRelay Approach |
|---------------------|---------------------|
| ❌ Send large text directly → ⏰ Timeout | ✅ Write to file + send short pointer → Success |
| ❌ No verification if received | ✅ Secret Code mechanism ensures delivery |
| ❌ No audit trail | ✅ Complete transaction logs (4 entries/event) |
---
## 🚀 Quick Start
### 1️⃣ Install
```bash
clawhub install agentrelay
```
### 2️⃣ Send Message
```python
from agentrelay import AgentRelayTool
# Prepare data
content = {"task": "write_poem", "theme": "spring"}
# Write to shared file and get CSV message
result = AgentRelayTool.send("yellow", "REQ", "hop1", content)
# Send to target agent
sessions_send(
target='agent:yellow:yellow',
message=f"AgentRelay: {result['csv_message']}"
)
```
### 3️⃣ Receive Message
```bash
# Use unified script to parse
python3 scripts/run_relay.py receive "REQ,hop1,s/hop1.json,,"
```
Output:
```json
{
"type": "REQ",
"event_id": "hop1",
"content": {"task": "write_poem", ...},
"secret": "ABC123"
}
```
### 4️⃣ Complete Task and Reply
```bash
python3 scripts/run_relay.py complete hop1 "Task completed" "agent:red:red"
```
Output:
```
✅ Updated hop1
✅ CMP: CMP,hop1,,,ABC123
```
---
## 🔄 Complete Flow
```
Sender Receiver
| |
|-- 1. REQ (with file ptr) --->|
| |-- receive()
| |-- 📍 LOG #1: REQ/RECEIVED
| |-- 📍 LOG #2: ACK/ACKNOWLEDGED
| |
|<-- 2. ACK (implicit confirm)-|
| |
|...Bambu Lab 3D printer control and automation. Activate when user mentions: printer status, 3D printing, slice, analyze model, generate 3D, AMS filament, print monitor, Bambu Lab, or any 3D printing task. Full pi...
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