beam-ai-team/beam-agent-manager

Beam Agent Manager

Orchestrate Beam agent graph operations — creation, structural changes, prompt optimization, and deployment. Routes to the right child skill based on user intent. For runtime operations (tasks, analytics, HITL, debugging), use beam-connect instead.

Decision Tree — What Does the User Want?

User wants to...
│
├── CREATE a new agent
│   ├── From YAML/JSON spec (quick deploy, spec already defined)
│   │   └── create-beam-agent (POST /agent-graphs/complete)
│   │
│   ├── From business requirements (full lifecycle: design → deploy → validate)
│   │   └── beam-graph-creator (spec → Miro flowchart → nodes → PUT/PATCH → test)
│   │       Handles any topology: linear, branching, convergence
│   │       Also use for design-only (Steps 1-5, skip deployment)
│   │
│   └── Simple POST with prompt only
│       └── beam-api-reader (create_agent_from_prompt.py)
│
├── MODIFY graph structure (add/remove nodes or edges)
│   └── 1. get-beam-agent-graph (fetch + backup)
│       2. beam-put-payload-builder (GET→PUT payload)
│       3. PUT /agent-graphs/{agentId}
│       4. PATCH prompts/models/params
│       5. Publish
│
├── UPDATE prompts, models, or params (no structural change)
│   └── PATCH directly (see Workflows below) → Publish
│
├── OPTIMIZE prompts via APE loop
│   └── beam-ape-optimizer (test → critique → edit → redeploy)
│
├── EXTRACT nodes to files
│   └── graph-slicer
│
└── CHOOSE a model for a node
    └── select-llm-model

Skill Priority Rules

| Scenario | Use This | NOT This | Why | |----------|----------|----------|-----| | User has YAML spec, wants to deploy | create-beam-agent | beam-graph-creator | No design phase needed | | User has business requirements | beam-graph-creator | create-beam-agent | Needs design phase | | User wants design files only, no API | beam-graph-creator Steps 1-5 | create-beam-agent | No deployment | | User wants to improve prompt accuracy | beam-ape-optimizer | Manual PATCH | Systematic with test data |

Relationship to beam-connect

| Domain | Skill | Examples | |--------|-------|---------| | Build-time (graph ops) | beam-agent-manager | Create agent, add nodes, update prompts, optimize, publish | | Runtime (task ops) | beam-connect | Create tasks, check status, analytics, HITL, debugging, retry |

Core Rule: PUT vs PATCH

This is the most important decision in any Beam graph operation:

| I want to... | Use | Why | |--------------|-----|-----| | Add/remove nodes or edges | PUT (full graph) | Only way to change structure | | Update a prompt | PATCH /nodes/{nodeId}/prompt | Propagates to effective config | | Update a model | PATCH /agent-graphs/update-node | Set preferredModel in toolConfiguration | | Update params | PATCH /nodes/{nodeId}/input-output-params | Propagates correctly | | Publish | PATCH /agent-graphs/{graphId}/publish | Always required after any change |

PUT does NOT propagate prompts/models/params to originalTool. Always PATCH after PUT.

Workflows

Update Prompt/Model/Params

1. PATCH prompt/model/params
2. Publish: PATCH /agent-graphs/{graphId}/publish
3. GET fresh graph (UUIDs regenerated after publish)

Structural Change (Add Nodes/Edges)

1. GET current graph → save backup
2. Build PUT payload: use beam-put-payload-builder
3. PUT /agent-graphs/{agentId}
4. PATCH prompts, models, params for changed nodes
5. Publish
6. GET fresh graph

Multi-Node Param Update

1. Order: upstream → downstream (UUIDs regenerate on each PATCH)
2. PATCH node A params → GET fresh graph → PATCH node B params → ...
3. Publish

Backup & Restore

1. GET graph → save as backup JSON
2. Make changes
3. Rollback: beam-put-payload-builder --from-file backup.json

API Rules Quick Reference

Key rules to remember (full details in references/api-rules.md):

• Publishing regenerates all node UUIDs — always GET fresh graph after publish
• Empty arrays destroy data — inputParams: [] deletes all inputs, empty edges destroy topology
• Edge mirroring required — every edge in source's childEdges[] AND target's parentEdges[]
• No fallback models via API — only settable in Beam UI
• autoRetryWhenAccuracyLessThan >= 50 — API rejects lower values
• Filter signature images from .msg files — small images cause tasks to hang

For node configuration rules, linking formats, GET quirks, prompt authoring rules, and authentication: consult references/api-rules.md.

Error Handling

| Error | Likely Cause | Fix | |-------|-------------|-----| | PUT returns 400 | Missing required fields on node (retry/batch fields, reloadProps, remoteOptions) | Consult api-rules.md → Node Configuration | | PATCH returns 200 but no effect | Patching auto-created entry node (silently ignored) | Don't PATCH entry nodes — they're structural markers | | GET crashes with Cannot set properties of null | toolFunctionName doesn't match registered tool | Use GPTAction_EmptyTool as base tool | | Node prompt is empty after PUT | PUT doesn't propagate to originalTool | PATCH prompt after PUT | | Task stuck in IN_PROGRESS | Signature images in attachments | Filter image001.png etc. from .msg files | | Model silently changed to Gemini 3 PRO | Invalid model string | Use exact enterprise model names |

References

• api-rules.md — Full API behavioral rules, constraints, and gotchas
• beam-api-swagger.json — Source of truth for request body schemas (in workspace plan/ folder)