
beam-connect
Connect to Beam AI workspace for agent management. Load when user mentions 'beam', 'beam agent', 'beam task', 'beam analytics', 'list agents', 'create task', or any Beam AI operations. Meta-skill that validates config, discovers agents, and routes to appropriate operations.
"Connect to Beam AI workspace for agent management. Load when user mentions 'beam', 'beam agent', 'beam task', 'beam analytics', 'list agents', 'create task', or any Beam AI operations. Meta-skill that validates config, discovers agents, and routes to appropriate operations."
Beam Connect
User-facing meta-skill for Beam AI workspace integration.
Purpose
Single entry point for all Beam AI operations:
- Discover workspace agents
- Create and manage tasks
- Monitor analytics and performance
- Debug failed executions
- Optimize tool configurations
Follows the master/connect pattern - references beam-master for shared scripts and references.
Trigger Phrases
Load this skill when user says:
- "beam" / "beam ai"
- "list agents" / "show beam agents"
- "create beam task" / "run agent task"
- "beam analytics" / "agent performance"
- "beam task status"
- Any agent name from cached context
Pre-Flight Check (ALWAYS RUN FIRST)
Before ANY Beam operation, validate configuration:
python 00-system/skills/beam/beam-master/scripts/check_beam_config.py --json
Handle Config Status
ai_action |
What to Do |
|---|---|
proceed_with_operation |
Config OK → Continue |
prompt_for_api_key |
Ask user for API key, save to .env |
prompt_for_workspace_id |
Ask user for workspace ID, save to .env |
run_setup_wizard |
Run interactive setup |
If Setup Needed
I need to set up Beam AI integration first.
To get your credentials:
1. Log into Beam AI (app.beam.ai)
2. Go to Settings → API Keys
3. Create a new API key
4. Also get your Workspace ID from Settings → Workspace
Please provide:
1. Your Beam API key:
After user provides key:
# Write to .env
BEAM_API_KEY=xxx
BEAM_WORKSPACE_ID=workspace-id
# Re-run config check to verify
python 00-system/skills/beam/beam-master/scripts/check_beam_config.py --json
Workflows
Workflow 0: Config Check (Auto)
Trigger: Before any operation
Script: check_beam_config.py --json
Output: Config status, required actions
Workflow 1: List Agents
Trigger: "list agents", "show beam agents", "my agents"
python 00-system/skills/beam/beam-master/scripts/list_agents.py --json
Display Format:
Found 5 agents in your workspace:
1. Customer Support Agent
ID: abc-123-def
Type: beam-os
Created: 2024-01-15
2. Email Processor
ID: ghi-456-jkl
...
Cache agents for future reference:
- Store agent list in context
- User can reference by name: "run task for Customer Support"
Workflow 2: Get Agent Graph
Trigger: "get agent graph", "show agent workflow", "agent config for X"
python 00-system/skills/beam/beam-master/scripts/get_agent_graph.py --agent-id AGENT_ID --json
Display: Show nodes, connections, entry/exit points
Workflow 3: Create Task
Trigger: "create task", "run agent", "execute agent X"
Required: Agent ID, task query
Optional: URLs to parse, context files
python 00-system/skills/beam/beam-master/scripts/create_task.py \
--agent-id AGENT_ID \
--query "Task description" \
--json
Follow-up: Offer to monitor task progress
python 00-system/skills/beam/beam-master/scripts/get_task_updates.py --task-id TASK_ID
Workflow 4: Get Analytics
Trigger: "analytics", "agent performance", "how is X performing"
python 00-system/skills/beam/beam-master/scripts/get_analytics.py \
--agent-id AGENT_ID \
--json
Display:
Analytics for Customer Support Agent (Last 30 days)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Tasks: 150 total (+15.5%)
├─ Completed: 135 (+12.3%)
└─ Failed: 15 (-5.2%)
Performance:
├─ Avg Eval Score: 87.5 (+4.5%)
├─ Avg Runtime: 45.7s (-8.7%)
└─ Positive Feedback: 120
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Workflow 5: Task Management
Trigger: "task status", "retry task", "approve task"
Get Task Details:
python 00-system/skills/beam/beam-master/scripts/get_task.py --task-id TASK_ID --json
Retry Failed Task:
python 00-system/skills/beam/beam-master/scripts/retry_task.py --task-id TASK_ID
Approve HITL Task:
python 00-system/skills/beam/beam-master/scripts/approve_task.py --task-id TASK_ID
Provide User Input:
python 00-system/skills/beam/beam-master/scripts/provide_user_input.py \
--task-id TASK_ID \
--input "User response"
Rate Task Output:
python 00-system/skills/beam/beam-master/scripts/rate_task_output.py \
--task-id TASK_ID \
--node-id NODE_ID \
--rating positive \
--feedback "Worked well"
Workflow 6: Test & Update Nodes
Trigger: "test node", "update node config"
Test Node:
python 00-system/skills/beam/beam-master/scripts/test_graph_node.py \
--agent-id AGENT \
--node-id NODE \
--graph-id GRAPH \
--input '{"key": "value"}'
Update Node:
python 00-system/skills/beam/beam-master/scripts/update_graph_node.py \
--node-id NODE \
--objective "New objective"
Workflow 7: Tool Optimization
Trigger: "optimize tool", "improve tool performance"
Start Optimization:
python 00-system/skills/beam/beam-master/scripts/optimize_tool.py --tool TOOL_NAME
Check Status:
python 00-system/skills/beam/beam-master/scripts/get_optimization_status.py --thread-id THREAD
Smart Routing
When user mentions:
| Phrase | Route To |
|---|---|
| "list agents", "show agents" | Workflow 1 |
| "agent graph", "agent workflow" | Workflow 2 |
| "create task", "run task", "execute" | Workflow 3 |
| "analytics", "performance", "metrics" | Workflow 4 |
| "task status", "retry", "approve" | Workflow 5 |
| "test node", "update node" | Workflow 6 |
| "optimize tool" | Workflow 7 |
| Agent name (from cache) | Show agent details, offer actions |
Error Handling
Common Errors:
| Error | Solution |
|---|---|
| 401 Unauthorized | Token expired - re-authenticate |
| 403 Forbidden | Check workspace permissions |
| 404 Not Found | Verify agent/task ID |
| Rate Limited | Wait and retry |
On Error:
- Load:
beam-master/references/error-handling.md - Display user-friendly message
- Offer fix if possible
Context Caching
After listing agents, cache for session:
# Store in conversation context
agents_cache = [
{"name": "Customer Support", "id": "abc-123"},
{"name": "Email Processor", "id": "def-456"}
]
When user says "run Customer Support", match to cached agent ID.
Integration with Other Beam Skills
This skill can hand off to specialized skills:
| Skill | When to Use |
|---|---|
beam-list-agents |
Detailed agent listing |
beam-get-agent-graph |
Deep graph analysis |
beam-get-agent-analytics |
Extended analytics |
beam-create-agent-task |
Task creation with monitoring |
beam-debug-issue-tasks |
Debug via Langfuse |
Example Interactions
User: "list my beam agents"
AI:
Let me check your Beam configuration first...
✅ Configuration valid
Found 3 agents in your workspace:
1. Customer Support Agent
ID: abc-123-def
Description: Handles customer inquiries
2. Email Processor
ID: ghi-456-jkl
Description: Processes incoming emails
3. Report Generator
ID: mno-789-pqr
Description: Creates weekly reports
What would you like to do? Options:
- "get analytics for Customer Support"
- "create task for Email Processor"
- "show graph for Report Generator"
User: "create task for Customer Support: Process the latest support ticket"
AI:
Creating task for Customer Support Agent...
✅ Task Created!
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Task ID: AGE-785
Status: QUEUED
Query: Process the latest support ticket
Would you like me to monitor this task for updates?
Version
Version: 1.0
Created: 2025-12-11
Status: Production Ready
You Might Also Like
Related Skills

gog
Google Workspace CLI for Gmail, Calendar, Drive, Contacts, Sheets, and Docs.
openclaw
orpc-contract-first
Guide for implementing oRPC contract-first API patterns in Dify frontend. Triggers when creating new API contracts, adding service endpoints, integrating TanStack Query with typed contracts, or migrating legacy service calls to oRPC. Use for all API layer work in web/contract and web/service directories.
langgenius
